茨城大学重点研究「地域に密着した世界的 ICT イノベーションの創出」

茨城大学工学部附属
ICT グローカル教育研究センター
２０１８年度報告書

茨城大学重点研究プロジェクト「地域に密着した世界的 ICT イノベーションの創出」
平成 30 年度報告書刊行にあたって

プロジェクト代表

黒澤 馨

ICT グローカル教育研究センターは，平成 26 年 7 月に 5 つ目の工学部附属教育研究セン
ターとして活動を開始しました．本センターは，「情報セキュリティ・インテリジェント分野」・「社会・環境インフラ分野」・「ビッグデータ活用分野」・「ソーシャルコミュニティ・弱者支援分野」の 4 分野で構成され，各分野における『地域に密着した世界的
ICT イノベーションの創出』を目指しています．

当センターの平成 30 年度の研究業績は，特許 5 件，学術誌論文 10 件、国際会議発表 50
件，招待講演 2 件、その他（研究会等）56 件，競争的資金獲得（科学研究費補助金）15 件でした．

今後も，地域密着型の世界的 ICT イノベーションを創出する研究開発の推進に戦略的に取り組みながら，theory meets practice を実現するため，グローバル（世界的規模）な視点とローカル（地域的）な視点をもって地域課題の解決に取り組んでいきます．

本冊子は，重点研究「地域に密着した世界的 ICT イノベーションの創出」における当センター構成員の平成 30 年度の成果を中心にまとめましたので，是非ご一読頂けましたら幸甚に存じます．

構成員一同，茨城大学重点研究として地域社会の更なる発展に貢献していく所存でございますので，今後も引き続き，当センターへのご理解とご支援を宜しくお願い申し上げます．

「地域に密着した世界的 ICT イノベーションの創出」
プロジェクト参加教員（１）情報セキュリティ・インテリジェント分野における研究開発
黒澤馨（工学部情報工学科・教授）

大瀧保広 （IT 基盤センター・准教授）
藤芳明生 （工学部情報工学科・准教授）
米山一樹 （工学部情報工学科・准教授）
芝軒太郎 （工学部情報工学科・講師）（２）社会・環境インフラ分野における研究開発
上田賀一 （工学部情報工学科・教授）
桑原祐史 （工学部都市システム工学科・教授）
齋藤修（工学部・特命教授）

外岡秀行 （工学部情報工学科・教授）
羽渕裕真 （工学部情報工学科・教授）
山田稔（工学部都市システム工学科・教授）

原口春海 （工学部情報工学科・准教授）
小澤佑介 （工学部情報工学科・助教）
高橋竜一 （工学部情報工学科・助教）
堀田大貴 （工学部情報工学科・助教）（３）ビッグデータ活用分野における研究開発
新納浩幸 （工学部情報工学科・教授）
笹井一人 （工学部情報工学科・准教授）
岡田信一郎（工学部情報工学科・講師）
古宮嘉那子（工学部情報工学科・講師）
佐々木稔 （工学部情報工学科・講師）（４）ソーシャルコミュニティ・弱者支援分野における研究開発
鎌田賢（工学部情報工学科・教授）

米倉達広 （工学部情報工学科・教授）
野口宏（IT 基盤センター・准教授）

小花聖輝 （工学部共通講座・助教）

－目次－

１．活動概要２． 研究報告【代表的な論文】
1. Wakaha Ogata, Kaoru Kurosawa: No-Dictionary Searchable Symmetric
Encryption. IEICE Transactions 102-A(1): 114-124 (2019)

2. Yusuke Matsuda, Yusuke Kozawa and Yohtaro Umeda: "Experimental
Evaluation of Hybrid PWM/DPAM Dimming Control Method for Digital
Color Shift Keying Using RGB-LED Array", Journal of Signal Processing,Vol. 22, No. 4, pp. 165-168, July 2018.

3. Taro Shibanoki, Masaki Watanabe, Go Nakamura, Takaaki Chin and Toshio
Tsuji, “A Training Method for the Speech Controlled Environmental
Control System Based on Candidate Word Discriminations”, Journalof Robotics, Networking and Artificial Life, Vol. 5, No. 2 (September2018), pp. 135-138, 2018.

３．プロジェクト業績

1. 活動概要

ICT グローカル教育研究センター

平成３０年度活動概要

１． 研究開発・資金獲得計画
１． 計画名：情報セキュリティ・インテリジェント分野における研究開発（１） 実施概要：
 クラウドにおける情報セキュリティに関する研究
 暗号プロトコルの設計論と安全性証明に関する研究 読字障害児童向け音声付教科書の開発
 共創型人間－機械インタフェースの提案と障害者支援（２） 実施予定時期： 平成 30 年 4 月 1 日～平成 31 年 3 月 31 日
（３） 実施体制
・
責任者：黒澤馨・
メンバ：大瀧保広，藤芳明生，米山一樹，芝軒太郎（４）資金獲得計画：科研費等の各種外部資金獲得を目指す（５）実施における課題：特になし
２． 計画名：社会・環境インフラ分野における研究開発（１） 実施概要：
 ITS のための高信頼化通信の研究
 組込みシステムの協調解析と品質計測手法の開発
 衛星リモートセンシングに関する研究 高齢者を支援するインタラクションシステムの研究
 総合防災管理支援システムの開発（２） 実施予定時期： 平成 30 年 4 月 1 日～平成 31 年 3 月 31 日
（３） 実施体制
・
責任者：上田賀一・
メンバ：桑原祐史，齋藤修，外岡秀行，羽渕裕真，山田稔，原口春海，小澤佑介，高橋竜一，堀田大貴（４）資金獲得計画：科研費等の各種外部資金獲得を目指す（５）実施における課題：特になし
３． 計画名：ビッグデータ活用分野における研究開発（１） 実施概要：
 機械学習や統計学を利用した自然言語処理 データベース学習のための支援システムの開発
 様々なデータからの特徴抽出、分類、検索に関する研究 機械学習を用いた知識処理の研究（２） 実施予定時期： 平成 30 年 4 月 1 日～平成 31 年 3 月 31 日
（３） 実施体制
・
責任者：新納浩幸
・
メンバ：岡田信一郎，古宮嘉那子，佐々木稔（４）資金獲得計画：科研費等の各種外部資金獲得を目指す（５）実施における課題：特になし
４． 計画名：ソーシャルコミュニティ・弱者支援分野における研究開発（１） 実施概要：
 画像の自然な拡大・縮小・変形のための関数の開発
 地域情報化の研究
 階層型データモデル機能・データベースデータモデル機能に関する研究（２） 実施予定時期： 平成 30 年 4 月 1 日～平成 31 年 3 月 31 日
（３） 実施体制
・
責任者：鎌田賢・
メンバ：米倉達広，野口宏，小花聖輝（４）資金獲得計画：科研費等の各種外部資金獲得を目指す

1

（５）実施における課題：特になし
５． 計画名：各種論文誌・国際会議等での研究発表（１） 実施概要：各種論文誌・国際会議等において研究発表を行う（２） 実施予定時期： 平成 30 年 4 月 1 日～平成 31 年 3 月 31 日
（３） 実施体制
・
責任者：黒澤馨・
メンバ：上田賀一，鎌田賢，桑原祐史，齋藤修，新納浩幸，外岡秀行，羽渕裕真，
山田稔，米倉達広，大瀧保広，藤芳明生，米山一樹，原口春海，岡田信一郎，
古宮嘉那子，佐々木稔，芝軒太郎，野口宏，小澤佑介，小花聖輝，
高橋竜一，堀田大貴（４）資金獲得計画：科研費等の各種外部資金獲得を目指す（５）実施における課題：特になし
６． 計画名：各種学会・国際会議等での委員（１） 実施概要：各種学会・国際会議等での委員として活動する（２） 実施予定時期： 平成 30 年 4 月 1 日～平成 31 年 3 月 31 日
（３） 実施体制
・
責任者：黒澤馨・
メンバ：上田賀一，鎌田賢，桑原祐史，齋藤修，新納浩幸，外岡秀行，羽渕裕真，
山田稔，米倉達広，大瀧保広，藤芳明生，米山一樹，原口春海，岡田信一郎，
古宮嘉那子，佐々木稔，芝軒太郎，野口宏，小澤佑介，小花聖輝，
高橋竜一，堀田大貴（４）資金獲得計画：特になし（５）実施における課題：特になし
７． 計画名：当教育研究センター構成メンバによる勉強会（１） 実施概要：当教育研究センター構成メンバによる勉強会を実施する（２） 実施予定時期： 平成 30 年 4 月 1 日～平成 31 年 3 月 31 日
（３） 実施体制
・
責任者：黒澤馨・
メンバ：上田賀一，鎌田賢，桑原祐史，齋藤修，新納浩幸，外岡秀行，羽渕裕真，
山田稔，米倉達広，大瀧保広，藤芳明生，米山一樹，原口春海，岡田信一郎，
古宮嘉那子，佐々木稔，芝軒太郎，野口宏，小澤佑介，小花聖輝，
高橋竜一，堀田大貴（４）資金獲得計画：特になし（５）実施における課題：特になし○実施結果（中間報告時と年度末に、実施結果を記載してください。）
１． 計画名：情報セキュリティ・インテリジェント分野における研究開発（１） 実施結果：
 クラウドにおける情報セキュリティに関する研究：アクセス情報も秘匿するキーワード検索可能暗号を研究開発
 暗号プロトコルの設計論と安全性証明に関する研究：エンドツーエンド暗号化通信の数理的安全性モデルを研究開発
 読字障害児童向け音声付教科書の開発：文字認知が困難な児童生徒の能動的読書を可能にするマルチモーダル教科書等を研究開発
 共創型人間－機械インタフェースの提案と障害者支援：双腕協調タスクモデルに基づく 5 指駆動型筋電電動義手の提案と義手処方支援を研究開発
２． 計画名：社会・環境インフラ分野における研究開発（１） 実施結果：
 ITS のための高信頼化通信の研究：疑似雑音符号系列による知的照明光通信ネットワークを研究開発

2

 組込みシステムの協調解析と品質計測手法の開発：社会インフラシステム向けソフトウェアプラットフォーム等を研究開発

 衛星リモートセンシングに関する研究：衛星データの評価検証技術，高付加価値を持つ衛星データの生成技術，衛星データの新たな利用技術等を研究開発
 衛星リモートセンシングデータを用いた地域環境変遷の情報化に関する研究：生活環境圏における CO2 濃度の地域性に着目した新たな緑地評価指標を研究開発
 総合防災管理支援システムの開発：大規模自然災害時の円滑な情報共有に資する市町村型共通基盤等を研究開発
 ディジタル変復調や光無線通信システム等の開発：海中可視光ワイヤレス給電通信のための高電力効率変調法を研究開発
３． 計画名：ビッグデータ活用分野における研究開発（１） 実施結果：
 機械学習や統計学を利用した自然言語処理：外れ値検出手法からの重み設定による共変量シフト下における語義曖昧性解消の領域適応等を研究開発 データベース学習のための支援システムの開発：SQL 実習支援システム、リレーショナルデータモデル演習システムによる実際の授業での運用
 様々なデータからの特徴抽出、分類、検索に関する研究：局所的な周辺文脈を利用した日本語の教師なし All-words 型語義曖昧性解消等を研究開発
 機械学習を用いた知識処理の研究：状況やデータの性質を意識して，大量なデータから，知識のパターンやルールを取り出して活用する方法等を研究開発
４． 計画名：ソーシャルコミュニティ・弱者支援分野における研究開発（１） 実施結果：
 画像の自然な拡大・縮小・変形のための関数の開発：可変張力つき 2 変数スプラインの導出とその画像補間等を研究開発
 地域情報化の研究：メディアを利用した地域の ICT 化推進と地域の情報発信等を研究開発
 階層型データモデル機能・データベースデータモデル機能に関する研究：分散キャンパスを用いたファイルバックアップシステム等を研究開発
 ウェブシステムや並列・分散処理等に関する研究：次世代コンピュータシステム等を研究開発

５． 計画名：各種論文誌・国際会議等での研究発表（１） 実施結果：
■特許:

5 件

■学術誌論文：10 件■国際会議論文：

50 件■招待講演：

2 件■その他（研究会等）： 56 件

６． 計画名：各種学会・国際会議等での委員
７．
（１） 実施結果：
教員名

内容等

3

黒澤馨教授ACNS 2018 プログラム委員

黒澤馨教授

Asiacrypt 2018 プログラム委員

黒澤馨教授

電子情報通信学会 安全・安心な生活とＩＣＴ研究専門委員会 専門委員

黒澤馨教授

IET Information Security, Associate Editor

黒澤馨教授

International Journal of Applied Cryptography, Associate Editor

黒澤馨教授

Journal of Mathematical Cryptology, Associate Editor

上田賀一教授

日本ソフトウェア科学会 FOSE2018 プログラム委員

鎌田賢教授

Associate editor, IEEE Transactions on Industrial Electronics

鎌田賢教授

Secretary of the journal, Sampling Theory in Signal and Image Processing

鎌田賢教授

Program committee, The 6th International Workshop on Web Services and Social Media

桑原祐史教授土木学会 地球環境委員会 委員

桑原祐史教授土木学会 地球環境委員会 地球環境研究論文集編集小委員会 委員

桑原祐史教授日本リモートセンシング学会 対外協力委員会 委員

桑原祐史教授日本リモートセンシング学会 対外協力委員会 JpGU 小委員会 委員長

桑原祐史教授日本リモートセンシング学会 国土防災リモートセンシング研究会 会長

桑原祐史教授日本沿岸域学会 論文編集委員会 委員

桑原祐史教授土木学会 茨城会 幹事

桑原祐史教授NPO 法人 CO 2 濃度マップ普及協会 理事

外岡秀行教授(国研)産業技術総合研究所 客員研究員

外岡秀行教授(一社)日本リモートセンシング学会 評議員

外岡秀行教授(一社)日本リモートセンシング学会 事務局情報管理担当

外岡秀行教授(一財)宇宙システム開発利用推進機構 ISS 搭載型ハイパースペクトルセンサ等研究開発技術委員会委員

羽渕裕真教授電子情報通信学会ワイドバンドシステム(WBS)研究専門委員会 顧問

羽渕裕真教授電子情報通信学会ＩＴＳ研究専門委員会 顧問

羽渕裕真教授電子情報通信学会東京支部 次期支部長

羽渕裕真教授IEEE Japan Chapter Treasure

羽渕裕真教授IEEE Tokyo Section Treasure

羽渕裕真教授IEEE ITS Tokyo Chapter 委員

羽渕裕真教授IEEE VTS Tokyo Chapter 委員

羽渕裕真教授Associate Editor, IEICE Transaction in Fundamentals, Special section on WideBand Systems

羽渕裕真教授Associate Editor, IEICE Transaction in Fundamentals, Special section on Intelligent Transport Systems

羽渕裕真教授Associate Editor, IEICE Transaction in Fundamentals, Special section on Signal Design and its Applications in Communications

羽渕裕真教授Technical Program Committee Member, IEEE Asia Pacific Wireless Communications Symposium (IEEE VCS APWCS2018)

羽渕裕真教授Technical Program Committee Member, International Conference on ITS Telecommunications (ITST 2018)

羽渕裕真教授Technical Program Committee Member, IEEE GLOBECOM Workshop on Optical Wireless Communications

羽渕裕真教授Technical Program Committee Member, 10th International Conference on Knowledge and Systems Engineering (KSE 2018)

羽渕裕真教授Technical Program Committee Member, 2nd International Conference on Electrical Engineering and Informatics（ICon EEI 2018）

羽渕裕真教授Technical Program Committee Member, IEEE International Conference on Communication, Networks and Satellite (COMNETSAT 2018)

4

教員名

内容等

羽渕裕真教授Technical Program Committee Member, International Conference on Advances in Computing, Communications and Informatics (ICACCI 2018)

羽渕裕真教授Technical Program Committee Member, International Conference on Control, Electronics, Renewable Energy and Communications (ICCEREC 2018)

羽渕裕真教授Technical Program Committee Member, International Conference on Advanced Technologies for Communications (ATC’18)

羽渕裕真教授Technical Program Committee Member, The 3rd International Conference on Recent Advances in Signal Processing, Telecommunications & Computing (SigTelCom2019)

羽渕裕真教授Technical Program Committee Member, IEEE ICC'19 - SPC Symposium

羽渕裕真教授地上テレビジョン放送の高度化技術に関する研究開発運営委員会（日本放送協会 放送技術研究所）

大瀧保広准教授

電子情報通信学会 情報セキュリティ研究専門委員会 委員

藤芳明生准教授

電子情報通信学会 英文論文誌 D 編集委員

米山一樹准教授

日本応用数理学会 数理的技法による情報セキュリティ(FAIS)研究部会 幹事

米山一樹准教授

日本応用数理学会 日本応用数理学会論文誌 編集委員

米山一樹准教授

電子情報通信学会 2019 年英文論文誌小特集編集委員会 編集幹事

米山一樹准教授

電子情報通信学会 2020 年英文論文誌小特集編集委員会 編集幹事

米山一樹准教授

Indocrypt2018 プログラム委員

米山一樹准教授

ACM ASIA Public-Key Cryptography Workshop 2018 プログラム委員

米山一樹准教授

ACM ASIA Public-Key Cryptography Workshop 2019 プログラム委員

岡田信一郎講師

電子情報通信学会 東京支部運営委員 支部委員

古宮嘉那子講師

ICT-IPSC 2018 プログラム委員

古宮嘉那子講師

電子情報通信学会 言語理解とコミュニケーション研究会 (NLC) 運営委員

古宮嘉那子講師

JCSSE 2018 プログラム委員

芝軒太郎講師

計測自動制御学会システムインテグレーション（SI）部門ロボティクス部会委員

芝軒太郎講師

日本ロボット学会会誌編集委員

野口宏准教授

学術情報処理研究編集委員

野口宏准教授水戸市個人情報保護運営委員審議会

教員名

内容等

小澤佑介助教TPC member for 8th IEEE Globecom Workshop on Optical Wireless Communications (OWC'18)

小澤佑介助教Secretary for 8th IEEE Globecom workshop on Optical Wireless Communications (OWC18)

小澤佑介助教日本フォトニクス協議会可視光通信分科会 幹事

小澤佑介助教電子情報通信学会ワイドバンドシステム(WBS)研究専門委員会 幹事

小澤佑介助教IEICE Guest Editor for the IEICE transactions on fundamentals special section on Wideband Systems

小澤佑介助教Publication chair for RISP International Workshop on Nonlinear Circuits, Communications and Signal Processing 2019 (NCSP2019)

小花聖輝助教WSSM-2018 Workshop Co-chair

小花聖輝助教電子情報通信学会 サイバーワールド時限研究専門委員会 幹事

新納浩幸教授自然言語処理学会理事

新納浩幸教授

言語処理学会第 25 回年次大会 大会副委員長

佐々木稔講師

情報処理学会論文誌データベース編集委員

5佐々木稔講師

情報処理学会自然言語処理研究会運営委員

佐々木稔講師

国際会議 SEMAPRO 2018 Technical Program Committee

佐々木稔講師International Journal On Advances in Intelligent Systems, Editorial Board

佐々木稔講師

ひたちものづくりサロン代表幹事

佐々木稔講師FM ひたち番組審議委員

髙橋竜一助教電子情報通信学会知能ソフトウェア工学研究専門委員会

幹事補佐

 外部資金獲得結果（継続研究課題を含む）
・継続研究課題
種別

教員

研究課題

基盤（C）

黒澤馨教授

アクセス情報も秘匿するキーワード検索可能暗
号（代表）

基盤（C）

桑原祐史教授基盤（C）

羽渕裕真教授

若手（B）

古宮嘉那子講師

基盤（A）

古宮嘉那子講師

科研費（国際共同研究加速基金）出型」共同研究

生活環境圏における CO2 濃度の地域性に着目した
新たな緑地評価指標の提案（代表）
疑似雑音符号系列による知的照明光通信ネットワークの創出（代表）
局所的な周辺文脈を利用した日本語の教師なし
All-words 型語義曖昧性解消（代表）
日本語歴史コーパスに対する統語・意味情報アノテーション（分担）
語義曖昧性解消結果と領域適応を利用した課題情報

古宮嘉那子講師

双腕協調タスクモデルに基づく 5 指駆動型筋電電

若手（B）

芝軒太郎講師

若手（B）

米山一樹准教授

若手（B）

小澤佑介助教・今年度新規採択課題種別
教員の抽出（代表）動義手の提案と義手処方支援（代表）
エンドツーエンド暗号化通信の数理的安全性モデ
ルに関する研究（代表）
海中可視光ワイヤレス給電通信のための高電力効率変調法に関する研究（代表）

研究課題
複数タスクのタグがついたコーパスによる語義曖昧性解消の基盤（C）

古宮嘉那子講師

基盤（C）

大瀧保広准教授

検索可能暗号の応用システムに関する研究

基盤（C）

佐々木稔講師

半教師あり学習を用いた語義曖昧性解消

転移学習

6

基盤（B）

藤芳明生准教授

基盤（B）

藤芳明生准教授

基盤（C）

上田賀一教授文字認知が困難な児童生徒の公平な学力評価を保証するマ
ルチモーダル問題の開発と評価（代表）障害特性に合わせデジタル教科書・教材を最適にバリアフリー化するシステムの研究(分担)
組込みシステムのモデルベース設計のためのハイブリッド
モデル検査手法の確立

・共同研究
教員名

共同研究課題桑原祐史教授生活環境圏における CO2 濃度の計測と実証桑原祐史教授平成 30 年度鳥獣被害防止対策に係る委託研究桑原祐史教授AI 技術を利用した水害対処の研究

桑原祐史教授沢渡川流域の雨量モニタリングに基づく精緻な流量解析手法の研究

古宮嘉那子講師
新納浩幸教授，古宮嘉那子講師，佐々木稔講師
米山一樹准教授

国立国語共同研究プロジェクト 「通時コーパスの構築と日本語史研究の新展開」
国立国語共同研究プロジェクト 「コーパスアノテーションの拡張・統合・自動化に関する基礎研究」
NTT セキュアプラットフォーム研究所 実運用に即したグループ鍵共有プロトコルの共同研究

米山一樹准教授

東芝 形式検証を用いた暗号プロトコルの安全性検証に関する研究

米山一樹准教授

富士通研究所 セキュリティ攻撃の動向調査

小澤佑介助教小澤佑介助教

新納浩幸教授新納浩幸教授日本フォトニクス協議会可視光通信分科会 フェーズドアレイ光学素子を用いた

光空間伝送装置の研究開発
海洋開発研究機構 イメージセンサ型可視光通信を用いた水中無線通信・測距技術の研究日立水戸エンジニアリング 画像認識技術を利用した作業効率改善に関する研究
アイシン・エィ・ダブリュ株式会社 「時系列モデリング手法の開発」
7

佐々木稔講師
上田賀一教授高橋竜一助教
湊淳教授
原口春海講師

大和証券投資信託委託株式会社「AI 運用のためのニューステキストからのアルファならびにセンチメント情報自動抽出」
日立 AMS「自動運転制御ソフトウェアのアーキテクチャに関する研究 」
サンテクノ「機械学習による検品ツール開発に関する予備検討」

・受託研究
教員名

受託研究課題桑原祐史教授気候変動に伴う沿岸地域の脆弱性評価と適応策の費用便益分析に関する研究

外岡秀行教授外岡秀行教授

藤芳明生准教授

ASTER の TIR データの品質管理に係る研究（(一財)宇宙システム開発利用推進機構）
平成 30 年度 地球観測用小型赤外カメラ(CIRC)に関する校正検証（(国研)宇宙航空研究開発機構/JAXA）
音声教材の効率的な製作方法等に関する調査研究（文部科学省，NPO 法人
テストと学習環境のユニバーサルデザイン研究機構より再委託）

・その他
・今年度新規採択課題種別
茨城大学女性エンパワー
メント支援制度研 究 推 進 経 費 （ Research

教員
原口春海講師

新納浩幸教授Booster）
・継続研究課題種別
茨城大学研究拠点認定

茨城大学推進研究プロ
ジェクト

教員
桑原祐史教授桑原祐史教授研究課題
鉄筋製造業における人的要因を考慮した作業者計画モデル
文書の埋め込み表現と双方向 LSTM を用いた翻訳文
書の訳語校正研究課題
分野横断型環境情報の生成・公開と観測技術の開発（代表）

少数民族村落の孤立回避を目的としたネパール国
中山間部の環境モニタリング（代表）

８． 計画名：当教育研究センター構成メンバによる勉強会
実施結果：
・平成 30 年 9 月に、全員参加型の勉強会を実施した．
２．人材育成8

１． 計画名：各種学会等での発表を通した学生の研究開発力と国際力の向上（１） 実施概要：本教育研究センターに関連する研究開発の学生による積極的な対外発表および国際会
議等への論文採択による学生の研究開発力と国際力の向上を図る（２） 実施予定時期：平成 30 年 4 月 1 日～平成 31 年 3 月 31 日
（３） 実施体制
・ 責任者：黒澤馨
・
メンバ：上田賀一，鎌田賢，桑原祐史，齋藤修，新納浩幸，外岡秀行，羽渕裕真，
山田稔，米倉達広，大瀧保広，藤芳明生，米山一樹，原口春海，岡田信一郎，
古宮嘉那子，佐々木稔，芝軒太郎，野口宏，小澤佑介，小花聖輝，
高橋竜一，堀田大貴（４） 資金獲得計画：科研費等の各種外部資金獲得を目指す（５） 実施における課題：特になし
２． 計画名：各種講座やセミナー等による地域人材の育成（１） 実施概要：地域への還元や地域への貢献を目的とし，各種講座やセミナー等を通して地域人材を育成し，ひとづくりを図る（２） 実施予定時期：平成 30 年 4 月 1 日～平成 31 年 3 月 31 日
（３） 実施体制
・ 責任者：黒澤馨
・
メンバ：上田賀一，鎌田賢，桑原祐史，齋藤修，新納浩幸，外岡秀行，羽渕裕真，
山田稔，米倉達広，大瀧保広，藤芳明生，米山一樹，原口春海，岡田信一郎，
古宮嘉那子，佐々木稔，芝軒太郎，野口宏，小澤佑介，小花聖輝，
高橋竜一，堀田大貴（４） 資金獲得計画：特になし（５） 実施における課題：特になし
３． 計画名：各種発表会等による技術講演・技術交流（１） 実施概要：本教育研究センターを構成する教員の各種研究開発技術について，各種発表会等による技術講演・技術交流を通して人材育成を図る（２） 実施予定時期：平成 30 年 4 月 1 日～平成 31 年 3 月 31 日
（３） 実施体制
・ 責任者：黒澤馨
・
メンバ：上田賀一，鎌田賢，桑原祐史，齋藤修，新納浩幸，外岡秀行，羽渕裕真，
山田稔，米倉達広，大瀧保広，藤芳明生，米山一樹，原口春海，岡田信一郎，
古宮嘉那子，佐々木稔，芝軒太郎，野口宏，小澤佑介，小花聖輝，
高橋竜一，堀田大貴（４） 資金獲得計画：特になし（５） 実施における課題：特になし○実施結果（中間報告時と年度末に、実施結果を記載してください。）
 計画名：各種学会等での発表を通した学生の研究開発力と国際力の向上


実施結果：下記論文誌・国際会議等で学生が発表を行った．

 国際会議論文：Akinaga Ueda, Hayato Tada, Kaoru Kurosawa: (Short Paper) How to Solve DLOG Problem
with Auxiliary Input. IWSEC 2018: 104-113
 国際会議論文：Hayato Tada, Akinaga Ueda, Kaoru Kurosawa: How to Prove KDM Security of BHHO.
IWSEC 2018: 281-296
 国 際 会 議 論 文 ： Hiroyuki Shinnou, Xinyu Zhao and Kanako Komiya, “Domain Adaptation Using a
Combination of Multiple Embeddings”, PACLIC 2018, Hong Kong, China, 1-3 December, 2018 (accepted).
 国際会議論文：Masaya Suzuki, Kanako Komiya, Minoru Sasaki and Hiroyuki Shinnou, “Fine-tuning for
Named Entity Recognition Using Part-of-Speech Tagging”, PACLIC 2018, Hong Kong, China, 1-3 December,
2018.

9

 国際会議論文：Jing Bai, Hiroyuki Shinnou and Kanako Komiya, “Domain Adaptation for Sentiment Analysis
using Keywords in the Target Domain as the Learning Weight”, PACLIC 2018, Hong Kong, China, 1-3
December, 2018.
 国際会議論文：Aya Tanabe, Kanako Komiya, Masayuki Asahara, Minoru Sasaki and Hiroyuki Shinnou,“Detecting Unknown Word Senses in Contemporary Japanese Dictionary from Corpus of HistoricalJapanese”, JADH 2018, Tokyo, Japan, 9-11 September, 2018.
 国際会議論文：Rui Suzuki, Kanako Komiya, Masayuki Asahara, Minoru Sasaki and Hiroyuki Shinnou, “Allwords Word Sense Disambiguation Using Concept Embeddings”, LREC 2018, no 100, Miyazaki Japan, 9-11
May, 2018.
 国際会議論文：Cheng Shi, Kazuki Yoneyama, "Verification of LINE Encryption Version 1.0 using ProVerif",
International Workshop on Security (IWSEC 2018), LNCS11409, pp.158-173, Sep. 2018.
 国 際 会 議 論 文 ： Shintaro Terada, Kazuki Yoneyama, "Improved Verifiable Delegated Private Set
Intersection", International Symposium on Information Theory and its Applications (ISITA 2018), pp., Oct.
2018.
 国際会議論文：Yuma Kanai, Kazuki Yoneyama, "On Hiding Access Timings in ORAM", International
Symposium on Information Theory and its Applications (ISITA 2018), pp., Oct. 2018.
 国際会議論文：Shotaro Naiki, Masaki Kohana, Shusuke Okamoto and Masaru Kamada: A graphical frontend interface for React.js. In: L. Barolli et al. (eds.), Advances in Network-based Information Systems(Proceedings of the 21st International Conference on Network-based Information Systems, NBiS-2018),
Lecture Notes on Data Engineering and Communications Technologies 22, Springer, pp.887-896, Sep. 2018.
 国際会議論文：Shinya Kinoshita, Michitoshi Niibori and Masaru Kamada: An attendance management
system capable of mapping participants onto the seat map. In: L. Barolli et al. (eds.), Advances in Networkbased Information Systems (Proceedings of the 21st International Conference on Network-based Information
Systems, NBiS-2018), Lecture Notes on Data Engineering and Communications Technologies 22, Springer,
pp.897-902, Sep. 2018.
 国 際 会 議 論 文 ： Tatsuya Ohyanagi, Tomoyuki Ishida, Noriki Uchida, Yoshitaka Shibata, and Hiromasa
Habuchi: "Proposal of a Disaster Support Expert System Using Accumulated Empirical Data", The 12th
International Conference on Innovative Mobile and Internet Services in Ubiquitous Computing (IMIS-2018),
July 2018
 国際会議論文：Yutaka Imaizumi, Hiromasa Habuchi, and Koichiro Hashiura : "Improved Packet Success
Rate on MC-CDMA based On-demand WSN System with MPOMS", IEEE Vehicular Technology Society
Asia Pacific Wireless Communications Symposium (APWCS 2018), Aug. 2018
 国際会議論文：Hikari Iiduka, Hiromasa Habuchi, and Yusuke Kozawa : "Proposal of VN-CSK Systemhaving Positioning Function", IEEE Vehicular Technology Society Asia Pacific Wireless Communications
Symposium (APWCS 2018), Aug. 2018
 国際会議論文：Tomofumi Haruna, Hiromasa Habuchi, and Yusuke Kozawa : "Theoretical Analysis of
Optical-Wireless Code Shift Keying System using Extended Einarsson Code", IEEE Vehicular Technology
Society Asia Pacific Wireless Communications Symposium (APWCS 2018), Aug. 2018
 国際会議論文：Yuto Asano, Hiromasa Habuchi, and Yusuke Kozawa : "Exact Bit Error Rate Analysis for
Optical-Wireless Framed-DOOK System", IEEE 7th Global Conference of Consumer Electronics (GCCE2018), (2018-10-12)
 国際会議論文：Takashi Tokunaga, Hiromasa Habuchi, Yusuke Kozawa, and Ran Sun : "BER Performance
Impaired by Transmission Time Offset Between Users in Optical Wireless CSK/ACDMA System Using
DMPOMs", IEEE 7th Global Conference of Consumer Electronics (GCCE 2018), (2018-10-12)
 国際会議論文：Yutaka Imaizumi, Hiromasa Habuchi, and Yusuke Kozawa : "Enhanced On-demand WSN in
terms of MC-CDMA with MPOMS", IEEE International Symposium on Intelligent Signal Processing andCommunication Systems (ISPACS 2018), pp.102-106, (2018-11-28)
 国際会議論文：Run Sun, Hiromasa Habuchi, and Yusuke Kozawa : "Proposal of Optical Wireless Turbo
Coded System with Hybrid PPM-OOK Signalling", International Conference on Signal Processing andCommunication Systems (ICSPCS 2018), (2018-12-18)

10 国際会議論文：Yuto Asano, Hiromasa Habuchi, and Yusuke Kozawa : "Frame Error Detection Performanceof Optical-Wireless Advanced Framed-DOOK System", International Conference on Signal Processing andCommunication Systems (ICSPCS 2018), (2018-12-19)
 国際会議論文：Lu Yangzhicheng, Tomoyuki Ishida, Hiromasa Habuchi : "Proposal of a Furniture Layout
Simulation System using Mixed Reality Technology", 24th International Symposium on Artificial Life andRobotics pp.808-811, (2019-01-24)
 国際会議論文：Ryo Nakai, Tatsuya Ohyanagi, Tomoyuki Ishida, Hiromasa Habuchi : "Proposal of a Scalable
Interactive Visualization Environment using Large Display in Emergency", 24th International Symposium on
Artificial Life and Robotics pp.812-815, (2019-01-24)
 国 際 会 議 論 文 ： Hikari Iizuka, Ran Sun, Hiromasa Habuchi, and Yusuke Kozawa : "High Accuracy
Positioning System on Indoor Optical Wireless VN-CSK System",RISP International Workshop on Nonlinear
Circuits, Communication and Signal Processing (NCSP'19), (2019-03-05),
 国際会議論文：Yuta Asano, Hiromasa Habuchi, and Yusuke Kozawa : "Effective Frame Error Detecting
Scheme for Optical-Wireless Advanced Framed-DOOK System", RISP International Workshop on Nonlinear
Circuits, Communication and Signal Processing (NCSP'19), (2019-03-05)
 その他（研究会等）：柴田 敏弥, 米山 一樹, "UC 安全動的検索可能暗号の拡張とフォワード安全性について", 暗号と情報セキュリティシンポジウム (SCIS 2019), Jan. 2019.
 その他（研究会等）：金井 佑篤, 米山 一樹, "複数のファイルアクセス可能な ORAM", 暗号と情報セキュリティシンポジウム (SCIS 2019), Jan. 2019.
 その他（研究会等）：寺田 槙太郎, 米山 一樹, "CSIDH に基づくパスワードベース認証鍵交換 ", 暗号と情報セキュリティシンポジウム (SCIS 2019), Jan. 2019.
 その他（研究会等）：野口 凌雅, 花谷 嘉一, 米山 一樹, "ProVerif による HEMS におけるグループ鍵管理の検証", 暗号と情報セキュリティシンポジウム (SCIS 2019), Jan. 2019.
 その他（研究会等）：師 成, 米山 一樹, "ProVerif によるスマートコントラクト決済委託プロトコルの公平性の検証", 暗号と情報セキュリティシンポジウム (SCIS 2019), Jan. 2019.
 その他（研究会等）：勝野 凌介, 米山 一樹, "IC カードとリーダ/ライタ間の認証プロトコルにおける認証
再利用と暗号理論的安全性モデルの関係", 電子情報通信学会情報セキュリティ研究会, Mar. 2019.
 その他（研究会等）：白井 直輝, 米山 一樹, "検証可能委譲秘匿ビット比較演算", 電子情報通信学会情報セキュリティ研究会, Mar. 2019.
 その他（研究会等）：春名智文, 羽渕裕真, 小澤佑介 : "光無線 CSK システムへの拡張 Einarsson 符号の適用性", 電子情報通信学会ワイドバンド研究会 WBS2018-8, pp.17-22, (2018-07-06)
 その他（研究会等）：飯塚暉, 羽渕裕真, 小澤佑介 : "光無線 VN-CSK システムにおける測位性能の検討", 電子情報通信学会ワイドバンド研究会 WBS2018-9, pp.23-27, (2018-07-06)
 その他（研究会等）：今泉豊, 大川智広, 羽渕裕真, 橋浦康一郎 : "変形擬直交 M 系列対を用いるオ
ン デマン ド 型 WSN におけ る パケット成功率向上法", 電子情報通信学会ワイド バン ド 研究会,
WBS2018-11, pp.35-40, (2018-07-06)
 その他（研究会等）：浅野裕太, 羽渕裕真, 小澤佑介 : "光無線フレーム化 DOOK システムにおける同期シンボルによる誤り検出法の検討", 電子情報通信学会ワイドバンド研究会, WBS2018-16, pp.59-63,(2018-07-06)
 その他（研究会等）：徳永岳, 孫冉, 羽渕裕真, 小澤佑介 : "DMPOMs を用いる光無線 CSK システムにおける同期性能を考慮した誤り率性能", 電子情報通信学会ワイドバンド研究会, WBS2018-17,
pp.65-70, (2018-07-06)
 その他（研究会等）：浅野裕太, 羽渕裕真, 小澤佑介 : "誤り検出可能な光無線フレーム化 DOOK シ
ステム", 革新的無線通信技術に関する横断型研究会 MIKA2018, 3-13, (2018-09-27)
 その他（研究会等）：孫冉, 羽渕裕真, 小澤佑介 : "光無線通信におけるハイブリッド PPM-OOK ターボ
符号システム", 革新的無線通信技術に関する横断型研究会 MIKA2018, 3-14, (2018-09-27)
 その他（研究会等）：陳力源, 羽渕裕真: "SIK を用いる多視覚秘密分散法によるマルチルートネットワーク", 革新的無線通信技術に関する横断型研究会 MIKA2018, 4-2, (2018-09-27)
 その他（研究会等）：浅野裕太, 羽渕裕真, 小澤佑介:"拡張フレーム化 DOOK システムのためのフレーム誤り検出法の検討",電子情報通信学会ワイドバンド研究会,WBS2018-30 (ITS2018-13, RCC2018-1161), pp.17-21, (2018-12-06)
 その他（研究会等）：孫冉, 羽渕裕真, 小澤佑介 : "ハイブリッド PPM-OOK 信号形式を用いる光無線
パンクチャードターボ符号システムの検討", 電子情報通信学会ワイドバンド研究会,WBS2018-72(ITS2018-55, RCC2018-103), pp.249-253, (2018-12-07)
 その他（研究会等）：真中佳祐, 陳力源, 羽渕裕真, 小澤佑介 : "VN-CSK 照明可視光通信における等重み(2,2)視覚復号型秘密分散法", 電子情報通信学会東京支部学生会研究発表会, (2019-03-02)
 その他（研究会等）：木口朋洋, 孫冉, 羽渕裕真, 小澤佑介 : "光無線 PPM-OOK システムのためのフレーム同期法 ", 電子情報通信学会東京支部学生会研究発表会, (2019-03-02)
 その他（研究会等）：鈴木暁大, 羽渕裕真 : "フレーム ALOHA を用いる MPSC-PDMA 方式", 電子情報通信学会東京支部学生会研究発表会, (2019-03-02)
 その他（研究会等）：孫冉, 羽渕裕真, 小澤佑介 : "光無線通信ターボ符号システムにおける信号伝送
形式の一検討", 電子情報通信学会 WBS/IT/ISEC 合同研究会, WBS2018- (IT2018- ,ISEC2018- ),(2019-03-07) その他（研究会等）：今泉豊, 羽渕裕真, 橋浦康一郎 : "変形擬直交 M 系列対を用いる ROD-WSN における ノード間干渉の影響", 電子情報通信学会総合大会, (2019-03-19)
 その他（研究会等）：荒井宏，原口春海，“鉄筋製造業における切断作業の効率化に関する研究” ，日本
機械学会生産システム部門研究発表講演会 2019，2019 年 3 月（発表予定）
 その他（研究会等）：黒澤馨、上田明長、松橋駿斗、阪上佑介, "複数の小さな離散対数問題を解くアルゴ
リズム", 暗号と情報セキュリティシンポジウム (SCIS 2019), Jan. 2019.019.
 その他（研究会等）：冨田斗威、尾形わかは、黒澤馨、"標準的な仮定のもとで leakage resilient かつ CCA
安全な ID ベース KEM", 暗号と情報セキュリティシンポジウム (SCIS 2019), Jan. 2019.019.

 計画名：各種講座やセミナー等による地域人材の育成
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 計画名：各種発表会等による技術講演・技術交流
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講演内容
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平成 30 年度茨大シーズ発表会 「IoT 時代の作業者訓練のあり方」
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「高校数学の数式で理解する通信ネットワーク」

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12

2. 研究報告【代表的な論文】

IEICE TRANS. FUNDAMENTALS, VOL.E102–A, NO.1 JANUARY 2019

114

PAPER

Special Section on Cryptography and Information Security

No-Dictionary Searchable Symmetric Encryption∗
Wakaha OGATA†a) , Member and Kaoru KUROSAWA††b) , Fellow

SUMMARY In the model of no-dictionary searchable symmetric encryption (SSE) schemes, the client does not need to keep the list of keywords
W. In this paper, we first show a generic method to transform any passively
secure SSE scheme to a no-dictionary SSE scheme such that the client canverify search results even if w < W. In particular, it takes only O(1) time
for the server to prove that w < W. We next present a no-dictionary SSE
scheme such that the client can hide even the search pattern from the server.
key words: searchable symmetric encryption, dictionary, verifiable, searchpattern

1.

Introduction

1.1

Backgroundtable T is defined as T = (ID (w1 ), . . . , ID (wm )), wherewi ∈ W. Let I be an encryption of T . In the store phase,the client sends I and an encryption of D to the server.
We say that an SSE scheme is a no-dictionary SSE
scheme if the client does not need to keep W. In usual SSE
schemes, the client does not need to keep W. However,there are some exceptional cases. In this paper, we study
two cases in which it is non-trivial to design an eﬃcient nodictionary SSE scheme. (The notion of no-dictionary SSE
schemes was first studied by Taketani and Ogata [35] in thesetting of verifiable SSE schemes.)
1.2 No-Dictionary SSE with Search Pattern Hiding

The notion of searchable symmetric encryption (SSE)
schemes was introduced by Song et al. [34]. In the store
phase, a client encrypts a set of files and an index table bya symmetric encryption scheme, and then stores them onan untrusted server. In the search phase, he can eﬃciently
retrieve the matching files for a search keyword w keeping
the keyword and the files secret.
Since then, single keyword search SSE schemes [15],[16], [19], [24], [26], dynamic SSE schemes [13], [21], [22],[25], [27], [30], verifiable SSE schemes [24]–[27], [35], multiple keyword search SSE schemes [1], [7], [12], [20], [23],[36] and more [14] have been studied extensively by many
researchers.
Curtmola, et al. [16], [17] gave a rigorous definition ofprivacy against honest but curious servers. Kurosawa andOhtaki [24], [26] showed a definition of reliability against
malicious servers who may return incorrect search results tothe client, or may delete some encrypted files to save hermemory space. An SSE scheme is called verifiable if itsatisfies both privacy and reliability.
Let D = {D1, . . . , D N } be the set of files and W ={w1, . . . , wm } be the set of keywords, where each keyword w
is contained in some file(s). We call W a dictionary.
Let ID (w) = { j | D j contains w}. Then an index
Manuscript received March 20, 2018.
Manuscript revised June 19, 2018.
† The author is with Tokyo Institute of Technology, Tokyo, 1528552 Japan.
†† The author is with Ibaraki University, Hitachi-shi, 316-8511
Japan.
∗ A part of this paper was published at Financial Cryptography
and Data Security 2017 [31].
a) E-mail: ogata.w.aa@m.titech.ac.jpb) E-mail: kaoru.kurosawa.kk@vc.ibaraki.ac.jp
DOI: 10.1587/transfun.E102.A.114

The search pattern is the information on which past queries
are the same as the current one, where a query is an encryption of a search word w. In usual SSE schemes, the searchpattern is leaked to the server.
If the client keeps a dictionary W, we can construct asearch pattern hiding SSE scheme by using the technique ofprivate information retrieval (PIR) [29], [32]† (The cost for
it is that the communication complexity and the computation
complexity increase.).
In the store phase, the client stores an encrypted index
table I0 = (I0 [1], . . . , I0 [m]) such that I0 [i] is an encryptionof T [i](= ID (wi )), where wi ∈ W for each i. In the searchphase, by using PIR, he obtains I0 [i] from the server without
revealing any information on the search word wi ∈ W. Thismeans that the search pattern is hidden from the server. He
finally retrieves encryptions of all D j such that j ∈ T [i]from the server.
If the client does not want to keep W (i.e. no-dictionary
SSE), there is a simple way to modify the above scheme.
Let b be the bit length of the longest keyword in W,
and let π : {0, 1} ≤b → {0, 1}ℓ be an injection for someℓ. The client constructs an extended index table Te ofsize 2ℓ such that Te [π(w)] = ID (w). Then he stores
Ie = (Ie [1], . . . , Ie [2ℓ ]) such that Ie [i] is an encryption of
Te [i] to the server, and keeps only (b, π). In this way, we canobtain a no-dictionary search-pattern hiding SSE scheme.
However, Ie is much larger than I0 because 2ℓ ≫ |W | ingeneral.

† The connection between SSE and PIR was suggested by Curt-

mola et al. [16], [17].

Copyright © 2019 The Institute of Electronics, Information and Communication Engineers

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1.3

No-Dictionary Verifiable SSE

Consider a verifiable SSE scheme such as follows. The client
stores I1 = ((a1, b1, c1 ), . . . , (am, bm, cm )) to the server suchthat

If we use an oblivious RAM (ORAM) in a dynamic
SSE scheme [18] (in which the client can update files), we
can hide the search pattern and the access pattern. In sucha scheme, however, the client must keep the dictionary (or acorresponding list). The communication cost is also large.
2. Verifiable Searchable Symmetric Encryption(ai, bi, ci ) = (Fk1 (wi ), Fk2 (wi ) + ID (wi ), MAC(ai, bi ))for each wi ∈ W, where F is a pseudorandom function andk1, k2 are keys. To search on w, the client sends(a ′, b′ ) = (Fk1 (w), Fk2 (w))
to the server. The server finds i such that a ′ = ai and returns
the search result with MAC(ai, bi ).
Is it a no-dictionary verifiable SSE scheme? The answer
is no because a malicious server can cheat by saying that a ′ <{a1, . . . , am } (namely w < W) even if a ′ ∈ {a1, . . . , am }.
The client has no way to check this.
We can prevent this cheating by using the extended
index table Te defined in Sect. 1.2. However, the encrypted
Ie gets much larger than I1 (see Sect. 1.2).
For this problem, Taketani and Ogata [35] showed ano-dictionary verifiable SSE scheme such that the encryptedindex table is almost the same size as I1 . In this scheme,
however, the server takes O(N log(N m)) time to prove thatw < W, where N = |D| and m = |W |.
1.4

Our Contribution

In this paper, we first show a generic method to transform any
passively secure SSE scheme to a no-dictionary verifiable
SSE scheme. In the transformed scheme, the encrypted index
table is only a few times larger than that of the underlying
SSE scheme, and the server takes only O(1) time to provethat w < W, which is more eﬃcient than the scheme in[35]. The search time for w ∈ W remains almost the sameas that of the original SSE scheme. We also prove that thetransformed scheme is UC-secure in Appendix similarly to[24], [26].
We next present a no-dictionary search-pattern hiding
SSE scheme such that the encrypted index table is only a few
times larger than I0 (As in the corresponding dictionary SSE
scheme, the cost for it is that the communication complexity
and the computation complexity increase.)† .
We use Cuckoo Hashing [33] in both our results as amain technical tool.
1.5

RemarkIn the verifiable SSE schemes of [24]–[27], the set of keywords is defined as W = {0, 1}ℓ . In reality, however, keywords have various length. Therefore we must use the technique of Sect. 1.2 in practice.
† This part was not written in the conference version [31] of thispaper.

In this section, we define a no-dictionary (verifiable) SSE
scheme and its security. Basically, we follow the notation
used in [12], [24], [26].
• Let D = {D1, . . . , D N } be the set of files.
• Let W be the set of keywords, where each keyword w
is contained in some file(s).
• For w ∈ {0, 1}∗ , define as follows:{{Di | Di contains w} if w ∈ W
D(w) =∅
otherwise• Let C = {C1, . . . , CN }, where Ci is a ciphertext of Di .
• Let
C(w) = {Ci | Ci is a ciphertext of Di ∈ D (w)}.
(1)
Note that C(w) = ∅ if w < W.
If X is a bit string, |X | denotes the bit length of X. If
X is a set, |X | denotes the cardinality of X. “PPT” refers toprobabilistic polynomial time, and “PT” refers to polynomialtime.
2.1 Model
An SSE scheme has two phases, the store phase (which is
executed only once) and the search phase (which is executeda polynomial number of times). In the store phase, the client
encrypts all files in D and stores them on the server. In the
search phase, the client sends a ciphertext of a word w, andthe server returns C(w). If there is a mechanism to verify
the validity of C(w), the scheme is called a verifiable SSE(vSSE).
Formally, a vSSE scheme consists of the following four polynomial-time algorithms vSSE =(Setup, Trpdr, Search, Dec) as follows:• (K, I, C) ← Setup(1λ, D, W, {(w, D (w)) | w ∈W }): a PPT algorithm that generates a key K, an
encrypted index I, and the set of encrypted files
C = {C1, . . . , CN }, where λ is a security parameter.
This algorithm is run by the client in the store phase.
He then stores (I, C) on the server.
• t(w) ← Trpdr(K, w): a PPT algorithm that outputs a
trapdoor t(w) for w ∈ {0, 1}∗ .
This algorithm is run by the client in the search phase.
t(w) is sent to the server.
• (C ∗, Proof) ← Search(I, C, t(w)): a PT algorithm
that outputs the search result C ∗ and Proof for the validity check.

IEICE TRANS. FUNDAMENTALS, VOL.E102–A, NO.1 JANUARY 2019

116

This algorithm is run by the server in the search phase.
She then returns (C ∗, Proof) to the client.
• D ∗ /⊥ ← Dec(K, t(w), C ∗, Proof): a PT algorithm thatdecrypts C ∗ and verifies its validity based on Proof. If
not valid, output is ⊥. This algorithm is run by theclient in the search phase.
We say that a vSSE satisfies correctness if the following
holds for any K, D, W, {(w, D (w)) | w ∈ W } and any wordw ∈ {0, 1}∗ .



1. Adversary A chooses (D, W ) and sends them to challenger
C.
2. C generates (K, I, C) ← Setup(1λ, D, W, {(w, D(w)) |w ∈ W }) and sends (I, C) to A.
3. For i = 1, . . . , q, do:a. A chooses a word wi ∈ {0, 1}∗ and sends it to C.
b. C sends the trapdoor t (wi ) ← Trpdr(K, wi ) back to A.
4. A outputs bit b.

Fig. 1• If(K, I, C) ← Setup(1λ, D, W,{(w, D(w)) | w ∈ W }),t(w) ← Trpdr(K, w),(C ∗, Proof) ← Search(I, C, t(w)),
D ∗ ← Dec(K, t(w), C ∗, Proof),

1. Adversary A chooses (D, W ) and sends them to challenger
C.
2. C sends L1 (D, W ) to simulator S.
3. S computes (I, C) from L1 (D, W ), and sends them to C.
4. C relays (I, C) to A.
5. For i = 1, . . . , q, do:a. A chooses wi ∈ {0, 1}∗ and sends it to C.
b. C sends L2 (D, W, w, wi ) to S, where w =(w1, . . . , wi−1 ).
c. S computes t (wi ) from L2 (D, W, w, wi ) and sends it
to C.
d. C relays t (wi ) to A.

then
D ∗ = D(w).
We assume that C ∗ is equal to C(w)(⊂ C) as in most existing
schemes.
An (not verifiable) SSE scheme is defined by omitting
Proof.

6. A outputs bit b.

Fig. 2

2.2

Real game Gamer e al .

L .
Simulation game Game simSecurity Definition

We next define the security of vSSE schemes. Note that asearch word w does not need to belong to the set W.
Privacy. In a (v)SSE, the server should learn almost
no information on D, W, and the search word w. Let
L 1 (D, W ) denote the information that the server can learn
in the store phase, and let L 2 (D, W, w, w) denote that in
the search phase, where w is the current search word andw = (w1, w2, . . .) is the list of the past search words queriedso far.
In most existing SSE schemes, L 1 (D, W ) =(|D1 |, . . . , |D N |, |W |), and L 2 (D, W, w, w) consists of { j |D j ∈ D (w)} and the search pattern
SPattern((w1, . . . , wq−1 ), w) = (sp1, . . . , spq−1 ),where{
sp j =

10

if w j = w,
if w j , w.

The search pattern reveals which past queries are the sameas w.
Let L = (L 1, L 2 ). The client’s privacy is defined byusing two games: a real game Gamer eal and a simulation
Lgame Gamesim, as shown in Figs. 1 and 2, respectively.
Gamereal is played by a challenger C and an adversary A,
L
and Gamesim
is played by C, A, and a simulator S.
Definition 1 (L-privacy): We say that a vSSE scheme has

L-privacy, if there exists a PPT simulator S such that
| Pr[A outputs b = 1 in Gamer eal ]L− Pr[A outputs b = 1 in Gamesim]|(2)

is negligible for any PPT adversary A.
Reliability. In an SSE scheme, a malicious server might
cheat a client by returning a false result C̃ ∗ (, C(w)) during
the search phase. (Weak) reliability guarantees that the client
can detect such a malicious behavior. Formally, reliability isdefined by game Gamer eli shown in Fig. 3, which is playedby an adversary B = (B1, B2 ) (malicious server) and a challenger C. B1 and B2 are assumed to be able to communicate
freely.
Definition 2 (Reliability): We say that B wins in Gamereli
if B1 receives Di∗ such that D̃i∗ < {D (wi ), ⊥} for some i. We
say that a vSSE scheme satisfies reliability if for any PPTadversary B,
Pr[B wins in Gamer eli ]is negligible.
For SSE schemes in which C ∗ = C(w) is assumed to be
returned as a search result, strong reliability was also definedin [26]. In strong reliability, the server has to answer a wrong
I )(, (C(w), Proof)) that will be accepted in thepair ( C̃ ∗, Proof
search phase to win the game.

OGATA and KUROSAWA: NO-DICTIONARY SEARCHABLE SYMMETRIC ENCRYPTION

117





(Store phase)
1. B1 chooses (D, W ) and sends them to C.
2. C generates (K, I, C) ← Setup(1λ, D, W, {(w, D(w)) |w ∈ W }), and sends (I, C) to B2 .

function if for any PPT distinguisher D,$$

Pr[k ← {0, 1}ℓ : DF (k, ·) = 1] − Pr[ f ← R : D f (·) = 1]
is negligibly small.
It is well known that a pseudo-random function works
as a MAC which is existentially unforgeable against chosenmessage attack.

(Search phase) For i = 1, . . . , q, do
1. B1 chooses wi ∈ {0, 1}∗ and sends it to C.
2. C sends the trapdoor t (wi ) ← Trpdr(K, wi ) to B2 .
Ji ) to C.
3. B2 returns ( C̃i∗, Proof
4. C computes

4. Generic Transformation from SSE to vSSE

Ji )D̃i∗ ← Dec(K, t (wi ), C̃i∗, Proofand returns D̃i∗ to B1 . D̃i∗ can be ⊥.

In this section, we show a generic method to transform any
 SSE which satisfies privacy to a no-dictionary verifiable
Fig. 3 Gamer el i .
SSE. In the transformed scheme, the encrypted index table is only a few times larger than that of the underlying SSE
scheme, and the server takes only O(1) time to prove that
Definition 3 (Strong Reliability): We say that B strongly
w < W. The search time for w ∈ W remains almost thewins in Gamereli if there exists i, such that bothsame
as that of the original SSE scheme. We also prove that
I i ) , ⊥ and ( C̃ ∗, ProofIi) ,Dec(K, t(wi ), C̃i∗, Proofithe transformed scheme is UC-secure in Appendix similarly(C(wi ), Proofi ) hold. We say that a vSSE scheme satisfies
to [24], [26].
strong reliability if for any PPT adversary B,


4.1 Construction

Pr[B strongly wins in Gamereli ]Let SSE0 = (Setup0, Trpdr0, Search0, Dec0 ) be an SSE
scheme. We construct a no-dictionary verifiable SSE
vSSE1 = (Setup1, Trpdr1, Search1, Dec1 ) as follows. Let
F be a pseudo-random function.

is negligible.
3.

Building Blocks

3.1

Cuckoo Hashing• Setup1 (1λ, D, W, {(w, D(w)) | w ∈ W }) : Let W ={w1, w2, . . . , w | W | }.

Cuckoo Hashing [33] is a hashing algorithm with the advantage that the search time is constant. To store n keys, it
uses two tables T1 and T2 of size m, and two independent
random hash functions h1 and h2 with the range {1, . . . , m}.
Every key x is stored at one of two positions, T1 (h1 (x)) orT2 (h2 (x)). So we need to inspect at most two positions tosearch x.
It can happen that both possible places T1 (h1 (x)) andT2 (h2 (x)) of a given key x are already occupied. This problem is solved by allowing x to throw out the key (say y)occupying the position T1 (h1 (x)). Next, we insert y at its
alternative position T2 (h2 ( y)). If it is already occupied, we
repeat the above steps until we find an empty position. If
we failed after some number of trials, we choose new hashfunctions and rebuild the data structure.
Let n = m(1 − ϵ ) for some ϵ ∈ (0, 1). Then the above
algorithm succeeds with probability 1−c(ϵ )/m+O(1/m2 ) forsome explicit function c(·) [28]. The expected construction
time of (T1, T2 ) is bounded above by [28]2n3.2

1 − eϵ −1.
(1 − eϵ −1 ) + ϵ(3)

Pseudo-Random Function

Let R be a family of all functions f : {0, 1}∗ → {0, 1} n . We
say that F : {0, 1}ℓ × {0, 1}∗ → {0, 1} n is a pseudo-random

1. Run Setup0 (1λ, D, W, {(w, D (w)) | w ∈ W })to obtain (K0, I0, C). Note that Ci ∈ C is a ciphertext of each file Di ∈ D.
2. Randomly choose a key k of F. We write Fk (x)instead of F (k, x).
3. Compute ke y j ← Fk (0∥w j ) for all w j ∈ W.
4. Construct cuckoo hash tables (T1′, T2′ ) of size
|W ||W |+1 which store {ke y j } j=1. Let (h1, h2 ) be thehash functions which are used to construct (T1′, T2′ ).
This means that
T1′ (h1 (ke y j )) = ke y j or T2′ (h2 (ke y j )) = ke y j
for each ke y j . When failing in constructing tables,
go back to step 2.
5. Construct two tables (T1, T2 ) of size |W | + 1 asfollows:
For a = 1, 2 and i = 1, . . . , |W |+1, if Ta′ (i) = ke y j
for some ke y j = Fk (0∥w j ), thenTa (i) ← ⟨ke y j , Fk (a∥i∥ke y j ), Fk (3∥ke y j ∥C(w j )⟩.
Otherwise
Ta (i) ← ⟨null, Fk (a∥i∥null), null⟩.
6. Output (K = (K0, k), I = (I0, T1, T2, h1, h2 ), C).
The client sends (I, C) to the server, and keeps K secret.

IEICE TRANS. FUNDAMENTALS, VOL.E102–A, NO.1 JANUARY 2019118

For each ke y j = Fk (0∥w j ), it holds that

Then T1 and T2 are constructed as shown in Table 2. Notethat the size of each table is 8 = |W | + 1.

T1 (h1 (ke y j ))= ⟨ke y j , Fk (1∥h1 (ke y j )∥ke y j ), Fk (3∥ke y j ∥C(w j ))⟩(Case 1) Suppose that a client searches for a keyword w3 ∈W.

or

1. The client sends trapdoor (ke y3, t 0 (w3 )) to the server.
2. Since h1 (ke y3 ) = 6 and h2 (ke y3 ) = 4, the server
retrieves

T2 (h2 (ke y j ))= ⟨ke y j , Fk (2∥h2 (ke y j )∥ke y j ), Fk (3∥ke y j ∥C(w j ))⟩.

⟨α1, β1, γ1 ⟩ = T1 (6)= ⟨ke y3, Fk (1∥6∥ke y3 ), Fk (3∥ke y3 ∥C1, C4 )⟩,⟨α2, β2, γ2 ⟩ = T2 (4)= ⟨ke y2, Fk (2∥4∥ke y2 ), Fk (3∥ke y2 ∥C2 )⟩• Trpdr1 ((K0, k), w) : Compute ke y ← Fk (0∥w) andt 0 (w) ← Trpdr0 (K0, w). Output t(w) = (ke y, t 0 (w)).
The client sends t(w) to the server, where w is a search word.
• Search1 ((I0, T1, T2, h1, h2 ), C, t(w) = (ke y, token)):Retrievefrom T1 and T2 .
Because α1 = ke y3 , the server obtains the search result⟨α1, β1, γ1 ⟩ ← T1 (h1 (ke y)),⟨α2, β2, γ2 ⟩ ← T2 (h2 (ke y)).
Let
∗

{

C ←

C ∗ = (C1, C4 ) ← Search0 (I0, C, t 0 (w3 )),Proof = γ1 = Fk (3∥ke y3 ∥C1, C4 ),Search0 (I0, C, token)
∅



 γ1
γ2
Proof ←  (α , β , α , β )1 1 2 2and returns (C ∗, Proof) to the client.
3. The client verifies if γ1 = Fk (3∥ke y3 ∥C ∗ ).

if ke y ∈ {α1, α2 }otherwise(Case 2) Suppose that the client searches for w < W.

if ke y = α1
if ke y = α2otherwise

1. The client computes ke y ← Fk (0∥w) and t 0 (w) ←Trpdr0 (K0, w). He sends t(w) = (ke y, t 0 (w)) to theserver.
2. Suppose that h1 (ke y) = 5 and h2 (ke y) = 3. Then theserver retrieves

Output (C ∗, Proof).
The server returns (C ∗, Proof) to the client.
• Dec1 ((K0, k), t(w) = (ke y, token), C ∗, Proof) :(Case 1) Proof = γ.
If γ , Fk (3∥ke y ∥C ∗ ), then output ⊥.
(Case 2) Proof = (α1, β1, α2, β2 ).
If C ∗ , ∅ or ke y ∈ {α1, α2 } or β1 ,Fk (1∥h1 (ke y)∥α1 ) or β2 , Fk (2∥h2 (ke y)∥α2 ), thenoutput ⊥.
Otherwise, compute D ∗ ← Dec0 (K0, token, C ∗ ) andoutput D ∗ .

⟨α1, β1, γ1 ⟩ = T1 (5)= ⟨null, Fk (1∥5), null⟩,⟨α2, β2, γ2 ⟩ = T2 (3)= ⟨ke y4, Fk (2∥3∥ke y4 ), Fk (3∥ke y4 ∥C1, C3, C7 )⟩.
Because ke y < {α1, α2 }, the server returns
C ∗ = ∅ and Proof = (α1, β1, α2, β2 ) =(null, Fk (1∥5), ke y4, Fk (2∥3∥ke y4 )).

The client obtains ⊥ or D ∗ .
4.2

Table 1
keyword w j
w1
w2
w3
w4
w5
w6
w7

ExampleSuppose that there are 7 keywords W = {w1, . . . , w7 } and8 ciphertexts C = {C1, . . . , C8 } such that C(w j ) are given
in Table 1. In the same table, h1 (ke y j ) and h2 (ke y j ) are
the hash values which are used to construct the cuckoo hashtables (T1′, T2′ ) for the set {ke y j = Fk (0∥w j ) | j = 1, . . . , 7}.
Table 2
i
1
2
3
4
5
6
7
8

Example.

C(w j )
C1, C4, C5, C8
C2
C1, C4
C1, C3, C7
C2, C6
C5, C8C1

h1 (key j )
6
2
6
6
7
7
2

h2 (key j )
1
4
4
3
8
6
8

Cuckoo hash tables (T1, T2 ).

T1 (i)⟨ null , Fk (1 ∥1), null⟩⟨ key7 , Fk (1 ∥2 ∥key7 ), Fk (3 ∥key7 ∥C1 )⟩⟨ null , Fk (1 ∥3), null⟩⟨ null , Fk (1 ∥4), null⟩⟨ null , Fk (1 ∥5), null⟩⟨ key3 , Fk (1 ∥6 ∥key3 ), Fk (3 ∥key3 ∥C1, C4 ) ⟩⟨ key6 , Fk (1 ∥7 ∥key6 ), Fk (3 ∥key6 ∥C5, C8 ) ⟩⟨ null , Fk (1 ∥8), null
⟩

i
1
2
3
4
5
6
7
8

T2 (i)⟨ key1 , Fk (2 ∥1 ∥key1 ), Fk (3 ∥key1 ∥C1, C4, C5, C8 ) ⟩⟨ null , Fk (2 ∥2), null⟩⟨ key4 , Fk (2 ∥3 ∥key4 ), Fk (3 ∥key4 ∥C1, C3, C7 )⟩⟨ key2 , Fk (2 ∥4 ∥key2 ), Fk (3 ∥key2 ∥C2 )⟩⟨ null , Fk (2 ∥5), null⟩⟨ null , Fk (2 ∥6), null⟩⟨ null , Fk (2 ∥7), null⟩⟨ key5 , Fk (2 ∥8 ∥key5 ), Fk (3 ∥key5 ∥(C2, C6 ))⟩OGATA and KUROSAWA: NO-DICTIONARY SEARCHABLE SYMMETRIC ENCRYPTION

119

3. The client verifies if ke y < {α1, α2 }, β1 =Fk (1∥h1 (ke y)∥α1 ), and β2 = Fk (2∥h2 (ke y)∥α2 ).
4.3

Eﬃciency

The eﬃciency of our transformed scheme vSSE1 is estimatedas follows:• In the store phase, |W | keys are stored in two tables,
where each table has size m = |W | + 1. Therefore, theclient takes the expected time O(|W |) + time(Setup0 )to run Setup1 from Eq. (3).
• In the search phase, the search time for w ∈ W isalmost the same as that of the original scheme.
• The server takes only O(1) time to prove that w < W
because the search time is constant in cuckoo hashing.
To prove that w < W, in the method of [35], the server
takes O(N log N |W |) time. In the concrete method (Algorithm 1+2) in [6], it takes O(log |W |) + time(Search0 ).
4.4

Security

Theorem 1: If the underlying scheme SSE0 has L =(L 1, L 2 )-privacy and F is a pseudorandom function, thenour scheme vSSE1 has L ′ = (L 1′ , L 2′ )-privacy such that
L 1′ (D, W ) = L 1 (D, W ) ∪ {|W |},L 2′ (D, W, w, wi ) = L 2 (D, W, w, wi )∪ {SPattern(w, wi ), [wi ∈ W]}. (4)In the all existing SSE schemes, |W | ∈ L 1 (D, W ) and{SPattern(w, wi ), [wi ∈ W]} ⊆ L 2 (D, W, w, wi ). (Theremay be some exceptions which use oblivious RAM. But such
SSE schemes are ineﬃcient.) So, the client’s privacy in ourvSSE scheme has the same level as that of the underlying
SSE scheme.
(Proof) Let S0 be a simulator of the underlining SSE scheme
which has (L 1, L 2 )-privacy. We construct a simulator S of
our vSSE scheme which achieves (L 1′ , L 2′ )-privacy as follows.
(Store phase) In Gamesim , S takes L 1′ (D, W ) =L 1 (D, W ) ∪ {|W |} as an input. S runs S0 (L 1 (D, W ))and gets its output (I0, C). Next S constructs T1 and T2 asfollows. Note that the size of each T1, T2 is m = |W | + 1.
′
• Choose ke y1′, . . . , ke y |W
randomly, where ke yi′ is|the simulated value of ke y j = FK (0∥w j ) such that′{ke y1′, . . . , ke y |W
} = {ke y1, . . . , ke y |W | }.
|• Construct the cuckoo hash tables (T1′, T2′ ) which store′ , . . . , ke y ′(ke yπ(1)), where π is a random permuπ( |W |)tation. Let h1, h2 be the two hash functions which areused to construct (T1′, T2′ ).
• For a = 1, 2 and i = 1, . . . , |W | + 1, if Ta′ (i) = ke y j′for some j, then choose two random strings r and r ′,and Ta (i) ← ⟨ke y j′, r, r ′⟩. Otherwise, choose a random
string r and Ta (i) ← ⟨null, r, null⟩.

S sends (I0, T1, T2, h1, h2 ) and C to the challenger. Let
cntr ← 1, where cntr will denote the number of distinct
keywords which the client has queried.
(Search phase) In the ith search phase, S takes
L 2′ (D, W, w, w ∗ ) = L 2 (D, W, w, w ∗ ) ∪ {SPattern(w, w ∗ ),[w ∗ ∈ W]} as an input. S first obtains t 0 (w ∗ ) by running
S0 (L 2 (D, W, w, w ∗ )), and sets′∗
 ke ycntr if sp j = 0 for all j and w ∈ W,∗
ke y jif sp j = 1 for some j,randomotherwise.
{
cntr + 1 if sp j = 0 for all j and w ∗ ∈ W,
cntr ←
cntr
otherwise.


ke yi∗ ← S outputs (ke yi∗, t 0 (w ∗ )) as a simulated trapdoor.
We will prove that there is no adversary A
who can eﬃciently distinguish between Gamer eal
and Gamesim .
We consider a game sequence(Gamer eal, Gamemid, Gamesim ). Gamemid is the same as
Gamereal except that all values of Fk (·) are replaced withrandom strings. For i ∈ {real, mid, sim}, define
Pi = Pr[ A outputs b = 1 in Gamei ].
Then |Preal − Pmid | is negligible because F is a pseudorandom function. We can also see that |Pmid − Psim | isnegligible from the (L 1, L 2 )-privacy of the underlying SSE
scheme. Consequently, |Preal − Psim | is negligible.
2
Theorem 2: Our vSSE scheme vSSE1 satisfies strong reliability if F is a pseudorandom function.
(Proof) We look at the pseudorandom function F as a MAC.
Suppose that there exists an adversary B = (B1, B2 )who can break the strong reliability of our vSSE scheme,
I i ) beand B runs the search phase q times. Let ( C̃i∗, Proof
B2 ’s response to t(wi ) = (ke yi, t 0 (wi )) in the ith searchphase, and let(C(wi ), Proofi ) = Search1 (I, C, t(wi )).
From the definition, B strongly wins if there exists i ∈{1, . . . , q} such that
I i ) , (C(wi ), Proofi ) and( C̃i∗, Proof
I i ) , ⊥.
Dec1 (K, (ke yi, t 0 (wi )), C̃ ∗, Proofi(5)

By using B, we will construct a forger F against the
MAC, where F has oracle access to Fk .
First, F randomly chooses J ∈ {1, . . . , q}. Then, F runs
B by playing the role of the challenger C (see Fig. 3) untilthe (J − 1)th search phase. During this simulation, when C
needs to compute Fk (x) for some x, F queries x to its oracle
Fk .
In the Jth search phase, there are three cases:
I J = γ̃.
(1) Proof
In this case, F outputs m ′ = (3∥ke yJ ∥ C̃J∗ ) and tag ′ = γ̃

IEICE TRANS. FUNDAMENTALS, VOL.E102–A, NO.1 JANUARY 2019120

as a forgery of the MAC F.
I J = ( α̃1, β̃1, α̃2, β̃2 ).
(2) ProofJ = γ and Proof
Since ProofJ = γ, there exists a ∈ {1, 2} such that
Ta (h a (ke yJ )) = ⟨ke yJ , Fk (a∥h a (ke yJ )∥ke yJ ), . . .⟩.
For this a, F outputs m ′ = (a∥h a (ke yJ )∥ α̃ a ) andtag ′ = β̃ a as a forgery.
I J = ( α̃1, β̃1, α̃2, β̃2 ).
(3) ProofJ = (α1, β1, α2, β2 ) and Proof
If there exists a ∈ {1, 2} s.t. (α a, β a ) , ( α̃ a, β̃ a ), then,F outputs m ′ = (a∥h a (ke yJ )∥ α̃ a ) and tag ′ = β̃ a as aforgery. Otherwise F outputs “fail.”
Now F succeeds in forgery if B strongly wins and F
correctly predicts i which satisfies Eq. (5), i.e., Eq. (5) holds
in i = J. Since F predicts J correctly with probability 1/q,
we obtain that
Pr[F succeeds in forgery]≥ Pr[B strongly wins in Gamer eli ] ×

1.
q(GenPIR, QueryPIR, AnsPIR, DecPIR ), where the first two are
PPT algorithms and the last two are PT algorithms.
• (pk, sk) ← GenPIR (1λ ): The receiver runs this algorithm, and sends pk to the sender. He keeps sk secret.
• Qidx ← QueryPIR (sk, idx): The receiver runs this algorithm when he wants to obtain midx , and sends Qidx
to the sender.
• r sp ← AnsPIR (pk, M, Qidx ): The sender runs this algorithm, and sends r sp back to the receiver.
• res ← DecPIR (sk, r sp): The receiver runs this algorithm, and obtains res = midx .
The sender should learn no information on idx from(pk, Qidx ).
More formally, a PIR scheme has to satisfy the following′
property; For any idx and idx ′, (pk, Qidx ) and (pk, Qidx )are computationally indistinguishable.
5.2 No-Dictionary Search-Pattern Hiding2
We prove the UC-security of vSSE1 in Appendix.
5.

Search-Pattern Hiding

As mentioned before, the existing no-dictionary SSE
schemes leak search pattern. Namely, they have (L 1, L 2 )privacy (Def. 1) such that L 2 includes search pattern.
In this section, we show a no-dictionary search-patternhiding SSE scheme such that the encrypted index table isonly a few times larger than I0 which is defined in Sect. 1.2.
We consider a model such that the search phase consists of two subprotocols. In the first subprotocol, the client
obtains
ID (w) = {i | Di contains w as a keyword}
for the search word w. In the second subprotocol, he obtains
C(w) = {Ci | i ∈ ID (w)}.
We focus on the first subprotocol, in which the searchpattern should be hidden. The definition of privacy is thesame as Def. 1.
If we use PIR in the second subprotocol in addition, we
can hide even the access pattern.
5.1

PIR

PIR is a two party protocol between a sender and a receiver such as follows. The sender has a database M =(m1, . . . , m N ). The receiver wants to obtain midx without
revealing the index idx. A trivial solution is that the sendersends the entire M to the receiver. In PIR, this must be
realized with less amount of communication. There exists a PIR scheme such that the communication overhead isO((log N ) 2 ) [29], [32].
A PIR scheme consists of four algorithms

We show our no-dictionary SSE scheme, SSE2 , which canhide even the search pattern. For each w j ∈ W, let
ID (w j ) = {id 1, . . . , id k j }.
SSE2 = (Setup2, Trpdr2, Search2, Dec2 )• Setup2 :1. Generate two PIR key pairs (sk 1, pk 1 ), (sk 2, pk 2 ).
2. Choose a key K ′ of a symmetric encryption scheme(Enc, Dec) randomly.
3. For each Di ∈ D, compute Ci ← EncK ′ (Di ) and set
C = (C1, . . . , CN ).
4. Compute ID ′ (w j ) ← EncK ′ (id 1 ∥ · · · ∥id k j ∥00 · · · 00)
for all w j ∈ W, where 0s are padded so that|ID ′ (w1 )| = |ID ′ (w2 )| = · · · = |ID ′ (w |W | )|.
5. Choose a key k of pseudo-random function F randomly,
and compute ke y j ← Fk (w j ) for all w j ∈ W.
6. Construct cuckoo hash tables (T1, T2 ) that stores⟨ke y j , ID ′ (w j )⟩. Note that
T1 (h1 (ke y j )) = ⟨ke y j , ID ′ (w j )⟩orT2 (h2 (ke y j )) = ⟨ke y j , ID ′ (w j )⟩holds.
7. Output ((K ′, sk 1, sk 2, k), (T1, T2, pk 1, pk 2 ), C).
The client sends (T1, T2, pk1, pk 2 ) and C to the server, andkeeps (K ′, sk 1, sk 2, k) secret.
• Trpdr2 :1. Compute ke y ← Fk (w).
2. Compute Q b ← QueryPIR (sk b, hb (ke y)) for b = 1, 2.
3. Output t(w) = (Q1, Q2 )The client sends t(w) = (Q1, Q2 ) to the server, where w is asearch word.

OGATA and KUROSAWA: NO-DICTIONARY SEARCHABLE SYMMETRIC ENCRYPTION

121• Search2 :1. Compute r spb ← AnsPIR (pk b, Tb, Q b ) for b = 1, 2.
2. Output (r sp1, r sp2 ).
The server returns (r sp1, r sp2 ) to the client.
• Dec2 :1. Compute res b ← DecPIR (sk b, r spb ) for b = 1, 2.
2. If res1 = ⟨Fk (w), ID 1′ ⟩, then decrypt ID 1′ and obtain
ID (w).
3. If res2 = ⟨Fk (w), ID 2′ ⟩, then decrypt ID 2′ and obtain
ID (w).
4. Otherwise output ID (w) = ∅, which means that “w <W.”
The client obtains ID (w) even if w < W.
If w = w j , the trapdoor t(w) = (Q1, Q2 ) is a pair ofqueries to retrieve T1 (h1 (ke y j )) and T2 (h2 (ke y j )). Therefore, either of res1 and res2 is equal to ⟨ke y j , ID ′ (w j )⟩from the property of cuckoo hashing and PIR.
We can use arbitrary encoding methods to represent
ID (w). For example, ID (w) = {2, 4, 5} can be encrypted
as ID ′ (w) = EncK ′ (010110 · · · ). In this case, padding is
unnecessary because the length of plaintext is constant. This
encoding is more eﬃcient when hit rate is relatively large.
The following theorem shows that vSSE2 does not leakthe search pattern.

as the simulated value of Fk (w j ).
5. Construct cuckoo hash tables (T1′, T2′ ) that stores⟨ke y j′, ID ′′j ⟩.
S2 sends (T1′, T2′, pk1′ , pk2′ ) and C ′ as the simulated values of(T1, T2, pk 1, pk 2 ) and C to the challenger.
(Search phase)S2 outputs t ′ (w) = (Q1′ , Q2′ ), where
Q b′ ← QueryPIR (sk b, 1).
We will prove that there is no adversary
who can eﬃciently distinguish between Gamereal
and Gamesim .
We consider a game sequence(Gamer eal, Game1, Game2, Gamesim ).
Game1 is the same as Gamer eal except that all
queries Q b in search phases are replaced with Q b′ ←QueryPIR (sk b, 1). From the security of PIR, Gamer eal andGame1 are indistinguishable.
Game2 is the same as Game1 except that all valuesof Fk (w j ) are replaced with random strings ke y j′ as inGamesim . From the pseudorandomness of F, Game1 andGame2 are indistinguishable.
The diﬀerence between Game2 and Gamesim is that
• In Game2 , Ci = EncK ′ (Di ) and ID ′ (w j ) =EncK ′ (ID (w j )), where ID (w j ) are padded so that
|ID (w j )| = L max .
• In Gamesim , Ci′ = EncK ′ (0 |Di | ) and ID ′′ (w j ) =EncK ′ (0 Lma x ).

Theorem 3: Define
L 1′′ (D, W ) = (|W |, |D1 |, . . . , |D N |, L max ),L 2′′ (D, W, w, wi ) = (),where
L max = max |ID (wi )|.
wi ∈W

If
• (GenPIR, QueryPIR, AnsPIR, DecPIR ) is a secure PIR
scheme,• F is a pseudorandom function, and• (Enc, Dec) is an IND-CPA secure symmetric encryption scheme,

Therefore, Game1 and Game2 are indistinguishable from
IND-CPA security of (Enc, Dec).
Consequantly, |Preal − Pmid | is negligibly small.
2
The above theorem shows that SSE2 leaks no information in the search phase. However, if a user downloads thehit files Ci ∈ C(w) without using PIR, the server may learnsome information about the search result. In such a case,total leakage becomes L 2′′ (D, W, w, w) = ID (w).
In general, eﬃciency must be sacrificed to obtainsearch-pattern hiding with/without dictionary.
• The search process needs two round-trip communication to complete keyword search process.
• In general, PIR is built by using asymmetric technique.
So, the scheme needs high computation/communication
cost.

then our scheme SSE2 has L = (L 1′′, L 2′′ )-privacy.
(Proof) We construct a simulator S2 which achieves(L 1′′, L 2′′ )-privacy as follows.
(Store phase)
On input L 1′′ (D, W ) = (|W |, |D1 |, . . . , |D N |, L max ),S2 computes (T1′, T2′, pk 1′ , pk 2′ ) and C ′ as follows.
1. As in Setup2 , generate two PIR key pairs(sk 1′ , pk 1′ ), (sk 2′ , pk 2′ ), and choose K ′.
2. For each i ∈ {1, . . . , N }, compute Ci′ ← EncK ′ (0 |Di | )′ ).
and set C ′ = (C1′, . . . , CN′′
3. Compute ID j ← EncK ′ (0 Lma x ) for all j ∈{1, . . . , |W |}.
4. Choose a random string ke y j′ for all j ∈ {1, . . . , |W |}5.3 How to Add Reliability
By using the same idea as in Sect. 4, we can add the reliability
to the above scheme. The client generates cuckoo hash tables(T1, T2 ) such that
T1 (h1 (ke y j ))= ⟨ke y j , ID ′ (w j ), Fk (1∥h1 (ke y j )∥ke y j ∥ID ′ (w j ))⟩or

IEICE TRANS. FUNDAMENTALS, VOL.E102–A, NO.1 JANUARY 2019122

T2 (h2 (ke y j )= ⟨ke y j , ID ′ (w j ), Fk (2∥h2 (ke y j )∥ke y j ∥ID ′ (w j ))⟩holds, where ke y j = Fk (0∥w j ). Then the client checks thevalidity of the answer from the server in the same way as in
Sect. 4.
6.

Conclusion

In this paper, we studied two cases in which constructionof eﬃcient no-dictionary SSE schemes is not trivial, andshowed that the cuckoo hashing technique can be used tosolve the problem in both cases.
First, we proposed a generic transformation from any
passively secure SSE scheme to a no-dictionary verifiable
SSE scheme. The eﬃciency of the transformed scheme isalmost the same as the underlying SSE scheme.
We next presented a no-dictionary search-pattern hiding
SSE scheme that has a compact encrypted index table. In
addition, we showed that our no-dictionary search-patternhiding scheme can be modified to a verifiable scheme withsmall cost.
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Conference on Information and Communication Security (ICICS
2005), pp.414–426, 2005.
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OGATA and KUROSAWA: NO-DICTIONARY SEARCHABLE SYMMETRIC ENCRYPTION

123

UC-security of no-dictionary vSSE scheme is defined
as follows.

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Appendix:

UC-Security for No-Dictionary vSSE

If a protocol is secure in the universally composable (UC)security framework, its security is maintained even if the
protocol is combined with other protocols [9]–[11]. The UC
security is defined based on ideal functionality F . Kurosawa
and Ohtaki introduced an ideal functionality of vSSE [24],[26]. Taketani and Ogata [35] generalized it in order tohandle the general leakage functions L = (L 1, L 2 ) as shownin Fig. A· 1.
In the no-dictionary verifiable SSE setting, the realworld is described as follows. We assume a real adversary, Auc , can control the server arbitrarily, and the client isalways honest. For simplicity, we ignore session id.
In the store phase, an environment, Z, chooses (D, W )and sends them to the client.
The client computes(K, I, C) ← Enc(1λ, K, D, W, {(w, D(w)) | w ∈ W }),and sends (I, C) to the server. The client stores K † andthe server stores (I, C). In the search phase, Z chooses
a word w ∈ {0, 1}∗ and sends it to the client. The clientcomputes t(w) ← Trpdr(K, w) and sends it to the server.
The server, who may be controlled by real adversary Auc ,I ) to the client. The client computes
returns ( C̃ ∗, ProofI ) and sends D̃(w) to Z.
D̃ (w) ← Dec(K, t(w), C̃ ∗, Proof
Note that D̃(w) can be ⊥. After repeating several searches,
Z outputs a bit b.
On the other hand, the ideal world is described as follows: In the store phase, Z sends (D, W ) to the dummyclient. The dummy client sends (store, D, W ) to functionL
ality FvSSE(see Fig. A· 1). In the search phase, Z sends w
to the dummy client. The dummy client sends (search, w)
L
to FvSSE, and receives D(w) or ⊥ (according to ideal adversary Suc ’s decision), which is relayed to Z. At last, Z outputs
a bit bIn both worlds, Z can communicate with Auc (in thereal world) or Suc (in the ideal world) in an arbitrary way.
Store: Upon receiving the input (store, sid, D1, . . . , D N , W )from the dummy client, verify that this is the first input fromthe client with (store, sid).
If it is, then store D = {D1, . . . , D N }, and send L1 ( D, W )to Suc . Otherwise, ignore this input.
Search: Upon receiving (search, sid, w) from the client, send
L2 (D, W, w, w) to Suc . Note that in a no-dictionary vSSE
scheme, the client may send w < W. If Suc returns accept,
then send D(w) to the client. If Suc returns reject, then send
⊥ to the client.

Fig. A· 1

Ideal functionality FvLS S E .

† He may forget D, W, C, I.

Definition 4 (UC-security with leakage L): We say that agiven no-dictionary vSSE scheme has universally composable (UC) security with leakage L against non-adaptive adversaries, if for any PPT real adversary Auc , there exists a
PPT ideal adversary (simulator) Suc , and for any PPT environment Z,| Pr[Z outputs 1 in the real world]− Pr[Z outputs 1 in the ideal world]|
is negligible.
We can show the following theorem.
Theorem 4: If a no-dictionary vSSE scheme satisfies Lprivacy and strong reliability for some L, it has UC security
with leakage L against non-adaptive adversaries.
(Proof) Assume that the scheme satisfies L-privacy andstrong reliability.
We consider four games Game0, . . . , Game3 . Let
pi = Pr[Z outputs 1 in Gamei ]for a fixed Auc . Game0 is equivalent to the real world in thedefinition of UC security. So,
p0 = Pr[Z outputs 1 in the real world].
Game1 is diﬀerent from Game0 in the following points.
• In the store phase, the client records (D, W, I) as wellas the key K.
• In the search phase, if Auc instructs the server to reI ) such that ( C̃ ∗, ProofI ) , (C ∗, Proof) ←turn ( C̃ ∗, Proof
Search(I, C, t(w)), then the server returns reject tothe client. Otherwise the server returns accept.
• If the client receives accept from the server, he sends
D(w) to Z. Otherwise, he sends ⊥ to Z.
Game1 is the same as Game0 until Auc instructs the server
I ) such thatto return ( C̃ ∗, ProofI ) , ⊥ and
Dec(K, t(w), C̃ ∗, Proof∗I ) , (C ∗, Proof).
( C̃ , Proof The above condition is the (strongly) winning condition of
B in Gamereli . So, we can obtain|p0 − p1 | ≤ max Pr[B strongly wins in Gamereli ].
B

From the assumption, |p0 − p1 | is negligibly small.
In Game2 , we split the client into two entities, client1
and client2, as follows: (See Fig. A· 2(a).)
• Both client1 and client2 receive all input from Z.
• In the store phase, only client2 sends (I, C) to theserver.
• In the search phase, only client2 sends t(w) to the server.
Then, only client1 receives accept/reject from theIEICE TRANS. FUNDAMENTALS, VOL.E102–A, NO.1 JANUARY 2019124

- client2
- client1


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-




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server



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Auc

?

Z

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6
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Z

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(b)
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server, and sends D(w)/⊥ to Z.
This change is conceptual only. Therefore p2 = p1 .
Now, we look at (Z, client1, server, Auc ) and client2 as
an adversary A and a challenger C in the real game of privacy, respectively. Then, from the assumption, there exists asimulator S such that Eq. (2) is negligible.
In Game3 , client2 plays the role of the challenger inthe simulation game of privacy; he sends L 1 (D, W ) or
L 2 (D, W, w, w) to the simulator S, and then S sends its outputs (the simulated message) to the server. (See Fig. A· 2(b).)
Again, we look at (Z, client1, server, Auc ) as A. Then Game3is the simulation game and Game2 is the real game. Therefore|p3 − p2 | ≤ | Pr[A outputs 1 in Gamereal ]L]|,− Pr[A outputs 1 in Gamesim
and it is negligible from the assumption.
In Game3 , (client1, client2) behaves exactly the sameL
way as FvSSE
in the ideal world.
So, considering(S, server, Auc ) as a simulator Suc , we obtain
p3 = Pr[Z outputs 1 in the ideal world]
for this simulator.
Consequently, we can say thatfor any Auc there exists Suc such that |p0 − p3 | =| Pr[Z outputs 1 in the real world] − Pr[Z outputs 1 in theideal world]| is negligible.
2
Corollary 1: If SSE0 has L = (L 1, L 2 )-privacy and F is a
pseudorandom function, the vSSE scheme vSSE1 obtained
from SSE0 using the transformation in Sect. 4 is UC-securewith leakage L ′ = (L 1′ , L 2′ ) where L and L ′ are given in
Theorem 1.

Wakaha Ogata
received the B.S., M.E. and
D.E. degrees in electrical and electronic engineering in 1989, 1991 and 1994, respectively,from Tokyo Institute of Technology. From 1995
to 2000, she was an Assistant Professor at HimejiInstitute of Technology. Since 2000 she has beenworking for Tokyo Institute of Technology, andnow she is a Professor from 2013. Her current
interests are cryptography and information security.

Kaoru Kurosawa
received the B.E. and
Dr. Eng. degrees in electrical engineering in
1976 and 1981, respectively, from Tokyo Institute of Technology. From 1997 to 2001, he
was a Professor in Tokyo Institute of Technology. He is currently a Professor in the Department of Computer and Information Sciences at
Ibaraki University. His current research interest is cryptography. He was Program Chair for
Asiacrypt 2007, PKC 2013 and some other conferences. Dr. Kurosawa is a member of IEEE,
ACM, IACR, IEICE. He received the excellent paper award of IEICE in
1981, the young engineer award of IEICE in 1986, Telecom System Scientific Award of Telecommnucations Avdancement Foundation in 2006 andAchievement Award of IEICE in 2007.

JoumalofSignalProcessmg,W1.22,No.4,pp.165-168,July２０１８

SELECTEDPAPERATNCSP'18

ExperimentalEvaluationofHybridPWMDPAMDimmingControlMethod
mrDigitalColorShinKWingUSingRGB-LEDArray

YusukeMatsuda',YusukeKozawa2andYohtaroUmeda3
1,3TbboUmversityofScience

21barakiUmversiW

2641Yamazaki,Noda,qliba278-8510,Japan
E-man:3ytxm̲lkb@rs.noda.ms.acjp+12-1Nakanamsawa,Hitachi,Ibalaki31G8511,Japan
E-mail:kozawa@ieee.org

Abstract

bycombmmgtheoutputsofed,green,andbluemRGBIED(".,mchromaticLED(ILED)).血CSK,Msignal

Inthiswork,wefbcusondigitalcolorshiftkeying(DCSK), pomtsaremappedmsidetheRGBcons鯰uationtriangleon
whichisoneofthemodulationschemesofvisiblenghtcom- theCExychromaticitydiagram[5]andarepresentedby
munication(VLC).DCSKisanexndedversionof正m themtensityratioofred,gⅡ己en,andblue.Whenthem802.15.7colorshiftkeymg(CSK)thattransmitsdtathrouJ] dividualmtensitiesof1℃d,green,andbluemaTIEDarethemrnsitymtiosofr己d,green,andblue.Digitallycon- 恥,&,andPB,respectively,thetotalmfnsityisconstant廿oUedLEDdxiversofDCSKcanalsoreducedlenonlin- (i.e.,Bt+&+PB=o7zst.)fOrnickermitigadon.CSK
earityeHectcausedbytheshiftofthemtensiWampUmde. canalsoudnzetheoriginalheqUencyI℃sponseoftheLED
DCSKsupportsmghtingfUnctionssuchasnickermtigadon, ofMHzorder,whilethehequencyresponseoftheblueLED
targetcolorconbol,anddimmingcontrol.Forthedimmmg withphosphorisumtedtojustMIzorderduetothephosconrolmethodofDCSK,twoschemeshavebeenconsid- phor[6][7].However,CSKsystemssumerhomLEDnonered.Oneispulsewidthmodulation(PWM),whichchanges linearityerectswhenadjustingtothedesiredopticalmtenthedutycycleofopdcalUansmtsignals,andtheotheris sityduetothechangemthecurrentdrivmgwithadigital-todigitalpulseampmmdemodulationの恥M),whichchanges analogconverter(DAC).T1nsanalog-contronedLEDcauses
thenumberofred,green,andblueLEDs(RGB-LEDs)be- nonlinearitiesofthecuncnttovoltage(1-V)characteristics
mgused.hapreviousanalysis,ahybridschemeofPWM andmnsitytocurrent(｡-DcharacteIisticsoftheLED[8].
andDPAMwasproposeddlatcouldaclUevebothawider Moreov"ananalog-conUonedLEDalsocausesanundedimmingmngethanDPAMandahigherspectralefficiency siredcolorshift,wmchisthepeakwavelengthshiftcaused
thanPWM・Unlikemdleoredcalanalysis,withacmallED bychangingthedlivecurrentoftheLED.Asasolutionto
dIivers,thedimminglevel(DL)obtainedbyPWM,DPAM, theseproblems,MonteiroandHrannovicproposedalinear
andhybridPWM/DPAMmaycauseerrorsduetomdividual variablecuITentdlivermcludingpredismrtiontolinearizethe
diHerencesmthedimmingmethodandLEDdrivecuIrent.m LEDoutputmtensity[９１.ThisvariablecuIrentdriverallows
thiswork,weexperimentallyevalua妃山eaccuracyofDLand dnedesiI巳ddrivecuITentItonowntoanLEDmeaIlydue
thesymbolerrorrate(SER)ofDCSKwithPWM,DPAM, totheopencoUectornatureofanOPAMP.HoweveritheseandhybridPWM/DMM.
a1℃hi[cmresmcreasethesystemcomplexityandtheycannot
1．mtrod皿唾i⑪皿

Visiblenghtcommumcation(VLC)isawirelesscommumcationsystemthatprovidesbothcommumcationandnghtmgfUnctions[1][2].Tba"lyVLCtoanmuminationsource,aVLCmodulationmethodmustcongidertheemctsofthe
modulatednJltsignalthathumansperceiveaswenassupportilickermtigation,dimmingconUol,colortempeIamre
control,ahighcolorrenderingmdex(CRI),andsoon.正I遁
802.15TaskGmup7proposedthreeVLCmodulationmethodsfbrnickermtigationanddimmingsupport:on-o鉦睦ymg(OOK),variablepulseposidonmoduladon(VPPM),andcolorshift"ymg(CSK)[3][4].TheCSKsy"misparticularlypromsmgbecauseitcanmcreasethedataspeed

JoumalofSignalProCessing,Wl.22,NO.4,July2018

preventtheproblemofanundesiredcolorshift・DigitalCSK(DCSK)hasalsobeenconsideredasameansofoveI℃onung
thedrawbachofCSK[10]-[12].InDCSK,thedesiredopticalmfnsityisrepresentedbydigitallycontroUedLEDsm
muldpleRGB-LEDs(i.e､,anRGB-LEDanay).Thiscanreducethesystemcomplexityandminimzethee冠睡tofIED
nonlinearity.
Inthiswork,wefbcusonadimmingconrolmethodfOr
DCSKwimRGB-IFDS・Generally,twodimmmgcontrol
schemeshavebeenconsideredfOrCSK[13]:pulsewidthmodulation(PWM)andpulseampmmdemodulation(PAM).
PWMdimsbychangingthedutycycleofopticaltransmt
signals,wmePAMgenerallydmsbyadjustingthedrive
currentoftheLED,whichmcreasesthesys[mcomplexity,

1６５

asmentionedearliemTYlerefOre,fbrDCSK,digitaUycon1ronedPAM(DPAM)ispmposed,whichdmsbychanging
thenumberofRGB-LEDsbemgusedmanRGB-LEDarray.
maprevioussmdy,ahybridschemeofPWMandDPAM
waspmposed[14]thatcouldachievebothawiderdimming
rangethanDPAMandahigherspectraleniciencythanPWM.
Unnkemtheoreticalanalysm,withacmalLEDdrivers,thedimminglevel(DL)obtainedbyPWM,DPAM,andhybrid
PWM/DPAMmaycauseeITorsduetomdividualdiHerences
mthedimmingmethodandLEDdrivecurrem.Inthiswork,
weexperimentanyevaluatetheaccuracyofDLandthesymbolerrorraf(SER)ofDCSKwithPWM,DPAM,andhybrid
PW皿恥Ｍ
2．Sys"mSetup

2.1PWMdimmingcontrolmethod

ofRGB-LEDsmtheRGB-IEDarramyasRGB,thenumber
ofdhnmingstagesofDPAMcanbewrittenas

MTmz=
■■■■■

｜
鶚ｌ

(3)

where[.｣isthenoorhmction.Then,theDPAMDL,gDpAM,
isrepresentedas
E D P A M =

坐旦型4
Ⅳｳ"α諺

,00％（４）(NDPAM=1,2,…,Ⅳ｝"｡")
ThespectraleniciencyofDCSKwithDPAMisthesame
asthatoftheoriginalDCSK.HoweverbthenumberofRGBIEDsmtheRGB-IEDarrayislimiCd,sothenumberof
dimmingstagesofDCSKwithDPAMislessthanthatof
DCSKwithPWM.

PWMisgenerallyusedfbrthedimmmgcontrolmVLC. 2.3HybridPWMPAMdimmiIRgContmlmethOd
TmsmethoddimsthenghtmtensiWmVLCbychanging"rDCSK
thepulsewidth.InaDCSKsysOm,thedutycycleofopAhybridPWM/DPAMsystemwasproposedmaprevious
ticaltransmssionsiglalsisrela[dtothebrighmessofthesmdy[14].TYlissystemcombmesPWMandDPAMtoenable
nghting.WedennednenumberofdimmmgstagesofPWM,
awiderdimmingm皿gethanDPAMandahigherspectralefL
jVMm｡",asficiencythanPWMbyselecmgtheoptimumcombmation.
ThenumberofdimmingstagesofhybridPWM/DPAM,N,(1) canbewrittenas

蝋".=芸

whereZbisthesymboldurationoftheorigmalDCSKand
ZtisthecmpdurationfbrPWMd血nmngcontrol.nlen,the
PWMDL,EpwM,isrepresenedasｇ Ｐ Ｗ Ｍ ＝

幽型型 ,00％Ⅳ淵｡露,(NpWM=1,2,..,jVM@α認）(2)

wheI℃NpwMisthePWMsignalduration.
DCSKwithPWMcanrepresentawiderdimmingrange
bydecreasmgthechipduration,Zt;howeveridlespectralefb
iiciencyofDCSKwithWMislessthanthatofdleoliginal
DCSK
2.2DPAMdhnmingcontrolmethod

Jv=JvM,q麺 Ⅳ耐α錘（５）

Then,theDL,E,isIepIesentedas

JVPwM 驚等 100%(6)E=JvM,"

However,thehybridWM/DPAMsystemcannotacmallyrepresentNDLsbecausedleymcludeovedappedpattems
suchas(EDpAM,EpwM)=(100%,33%)=(33%,100%),
whichtheoreticallyresultme=33%.
Figurelshowsanexampleofthetransmtsignalpatternmodelofa4-aryDCSKwiththehybridPWMの恥MdimmingcontrolmethodusmgnineRGB-LEDs.WhenⅣ；､f”＝3,DPAMcｍ配presentthreedimmingstages.Bycombmng
PWMwiththreedimmmgstages,thehybridPWM/DPAM
canrepresentninedhnmngstagesmcludingovedappedDLs.

nlePAMdimmingcontrolmethodgenerallydimsbyadjustingthe"vecun℃ntofLEDs.However,analogcurrent
controlcausesacolorshiftproblem,andwealsohavetolinealizetheLEDnonnnearityeHects.
Asapossiblesolutiontotheseproblems,DPAMisconsidered[14].DPAMrepresentstheDLsbychangingthenumber
ofacdveRGB-LEDsmtheRGB-LEDarray.nlerefbre,thenumberofdimmingstagesisn皿にdbythenumberofRGBLEDsmtheRGB-LEDarray.Whenwedennethenumberof
RGB-LEDsfbrtheorignalDCSKasNmi"andthenumber

1６６

2.4Experimentalsetup
T11eexperimentalsempofDCSKisshownmiigure２.
Transmssiondataisgenerardnomafield-programmablegateaITay(FPGA:Xilinxvirtex-6).Wepmgmmmedapseudorandombmarysequence(PRBS)generatoLDCSKmodulator,andhybddPWMﾉDPAMdimmmgcontmUermtothe
FPGA.TYlegeneratedDCSKsiglalisappUedtoanLED
driver,andthesignaldataareconverrdmtoanopticalsignal

JoumalofSignaIPI℃cessing,Wl.22,No.4,July2018

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AcknowledgmentS
ThisresearchwassupportedbyJSPSKAKENHIGrants
15K21397andl7K18143.
Remrences[1]YLTanaka､S.HamyamaandM・Nakagawa:Winelcssopticaltmnsmissions
wi山whiにcoIo唾dLEDibrwiIEIesShomelinks・ｏＰｍｃ･正圖ﾖＰＭＲＣ.Ｗ１．２，
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【2I'IIKomineandM.Nakagawa:Fundamenmlanalysisibrvisible-lightcommunicalionsystemusingLEDIighIs,肥EETmnsactionsonConsumerE1ectmnics,
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[4)S.RKljagopal,R.D・RObcI1sandS.-K.Lim:IEEE802.15.7visibleliglllcommunication:ModulationschemesImddimmingsuppo恥正ＥＥａｍ皿ʻ皿皿iʻ̲."Hʻ,皿、MagaZine,W1.500N０･３0pp､72-82,2012,

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Fromtable2,PWMachieveshighDLaccuraciescompaIcd
withthoseofDPAM.Forexample,whenedisabout６７%,
PWMcanachieveareladveerrorof-1.34,w皿ethereladveerrorofDPAMis２.25.Simnarly,whenedisabout
３３%,PWMcanachivearelativeerrorofO.61,whiletherelativeeIrorofDPAMis2.40.ThisisbecausemultipleRGBLEDsinDPAMmcreasetheemctofindividualdimrences
mtheLEDdrivecurrent.Z9110:2011ofJIS(Japanesemdustrialstandards)definesthatthen血mumdiffrencemUluminancewhichcanbeperceivedisabout１.５times[21].
Thepracticaltoleranceoftherelativeerroristherefbreabout
50％・
Figure4showstheSERversusthedistancebetweenthe
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ｐｐ､203<08,2007.
181N.Mumta,YIKozawaandYIUmedil:Digitlllcolorsililikcyingwithmullicolor
LEDaml肌肥EEPhotonicsJoumlll,W1.8,No.４,PP.1-13,2016.
191E.MontcimandS・Hmnilovic:DesignandimplementaUonofcoloIEshiftkcying
fbrvisibleligllt【H0DIoul01IoIi【畔,畝､DoNwlEEE/OSAJoumalofLightwaveTbchnologyi
Ｗ1.32,No.10,pp.2053=2060,2014.
【I０IH.SI1imamoto,YlKozawaandYIUmeda:AnexperimcnlalevaluationonEVM
pcribml叩ceibr4-CSK(colorshinkeying)usingvisibleliglllwithmultiple
filll.colorLEDs,Pmc・IEEERadioandWil℃lcssSymposium(RWS),pp.206208,J”ʼ2015．
【１l]N・Mumla,H・Sllimamolo,YLKozzlwnandYIUmeda:Pcrformnnccevaluation
ofdigitalcolourshiftkeyinglbrvisiblelight.｡………JicuiiUns,Pmc・正EEIntcmadonal"nfeIcnceonCommunicalionWorkshop(ICCW),pp.1374-1379,
Junc2015．
[121M.S・IslimandH.Haas:ModulationTbcllniquesibrLi-Fi,ZTE"mmun.,Ⅶ1.14,No.２･”､29-40,Apm2016.
[13]J.YLSung,C'WChowandC.H.YCh:Dimming-discletc-mulU-ionc(DMT)
fbrsimultanCo"colorconlrolandllighspeedvisiblelightL.皿ｺ舌-両0.1轍耐･]OWOpt.
Exp..Ⅶ1.22,N0.7,ppʼ7538̅7"3,Mar.2014.
114]J・Okumum,Y;Kozawa,YIUmedaandH.Hnbuchi:HybridPWM/DBAMdimmingcontmlibrdigitalcolorshiftkCyingusingRGB.LEDaITayilEEEJoumal
onSelccにdAIEasinCommunications.,W1.36,No.１,pp､45-52,”17．
I1510ptosupplyElcctmnics,May2018.[Onlinel.Availablc:hilp:"www.pcacecom-coiMhtnmnto■

ず■[1qHamamaisuPI1olonicsK.K・@0S6775''May2018.Pnlinel・Aymilab1e：
http:"www.hamamatsu.comjp/en/i)mduct/Ca(cgoIyl310W4001/4１０３ノ
S6775/ni dex・１' ，１[171MidwestOpticalSyslems,Inc.May２０１８.Pnlinel・Ayailable：
http:"midopt.com/nlters/bnndpass/[181A・Bunon,C.AmioLH.L・MinhandZ.Ghassemlooy:Designofanintcgmted
oPUcalIEcciveribrmobnevisiblclightcommunicalionssPGNet,2011.

4．Conchnsinns

Weexperimentallyevaluatedthedimmngaccuracyand
SERofDCSKwithhybridPWM/DPAMdinm血gcontrol.
Whentherewereseveralcombmationsrepresentingthesame
DL,thePWMschemehadgreaterdimmingaccuracythanthe

1６８[1９]Kcysigl1t,MSO6104A,May2018．[OnlinCl.Available:
ｌ１ｌtp:"wwwkeysight.com/Wen/pdx-x202252.pn-MSO61"Ahnixed･signaloscilloscope-l-ghzF4-amlogplus-16.digital･Channels?pm=spt&nid=
３西37.115“17＆cc=ＵＳ＆'←eng【201TOPCON"IM-1000;'May2018.pnline]・Available:http:"www.topcontechNo.coj"n/PmduCtSﾉOp-measﾉim-1“０.ｈｍｌ[２1]Gencmlmlesofrccommcndedlighlinglevels,JISZ9110,2011.

JoumalofSignaIProcessing,V01.22,No.４,July２０１８、

Journal of Robotics, Networking and Artificial Life, Vol. 5, No. 2 (September 2018) 135-138___________________________________________________________________________________________________________A Training Method for the Speech Controlled Environmental Control System
Based on Candidate Word Discriminations
Taro Shibanoki*, Masaki Watanabe*, Go Nakamura†, Takaaki Chin†, Toshio Tsuji‡*

Ibaraki University, 4-12-1, Nakanarusawacho, Hitachi, 316-8511, Japan
Hyogo Rehabilitation Center, 1070 Akebonocho, Nishi-Ku, Kobe,651-2181, Japan‡
Hiroshima University, 1-4-1, Kagamiyama, Higashi-Hiroshima,739-8527, Japane-mail: taro.shibanoki.ts@vc.ibaraki.ac.jp, 14t4070a@vc.ibaraki.ac.jp, g_nakamura@assistech.hwc.or.jp,
chin@assistech.hwc.or.jp, tsuji@bsys.hiroshima-u.ac.jp
http://bs.cis.ibaraki.ac.jp†

Abstract
This paper proposes a concept of a training system for the speech controlled environmental control system: BioRemote based on candidate word discriminations. The proposed system can provide three-types of voice signal
training: (1) volume, (2) tempo/timing and (3) candidate word which are important for accurate speech recognition
based on false recognition results. During the training, such three kinds of features are extracted from measured voice
signals and visually and auditory fed back to the user in real time. This allows the user to train speech abilities evenif false recognition results are extracted because of slurred speech. The efficacy of the proposed system wasdemonstrated through training experiments for slurred speech conducted with healthy participants. The results
showed that the proposed system was capable for the training of speech abilities.
Keywords: speech training, environment control system (ECS), speech recognition, candidate word, learning-type
look-up table.

to fully recover verbal functioning because of individual
differences and degrees of disability.
This paper proposed a training system for a speechcontrolled environmental control system based on
candidate word discrimination that can acquire the skillof fixed speech. After the training, the user’s intention
can be accurately discriminated, even if the user cannot
fully recover his/her verbal functioning.

1. Introduction
The number of disabled people in Japan continues toincrease annually and stands at 1.76 million. The
population of severely disabled people in particular wasaround 760,000, and such patients associated with aspeech disability reached 81,000 [1].
Against such a background, many speech-controlledenvironmental control systems (ECSs) have beendeveloped [2], [3]. However, it is difficult for patientswith dysarthria to use such systems, since the models
used in these systems considers standard adults’ speech.
Although some studies have investigated the use of
speaker-dependent models to support the learning ofindividual users’ voices [4], and the authors’ researchgroup also proposed the voice signal-based manipulation
method for ECS based on candidate word discrimination[5], fluctuating speech makes discrimination difficult.
The speech training system can support the recovery ofas much of a user’s speech as possible, and it has been
widely discussed as motivation and long-term
experiences for users [6], [7]. However, it can be difficult

2. Speech Training System Based on Candidate
Word Discrimination
Figure 1 shows the structure of the proposed speechtraining system based on candidate word discrimination.
The proposed system provides training for patients withdysarthria to speak the same way every time, even withslurred speech. This training can be applied to control thetraining of a voice-controlled environmental control
system [5] with slurred speech.
The proposed speech training system consists of a PC
with a feedback display, audio processor, andmicrophone. During the speech training, the display

Copyright © 2018, the Authors. Published by Atlantis Press.
This is an open access article under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
135

Journal of Robotics, Networking and Artificial Life, Vol. 5, No. 2 (September 2018) 135-138___________________________________________________________________________________________________________

Commandgeneration…

Featureextraction

2.1. Voice signal processing

Intention
estimation

Voice SpeechControl
Infraredsignal recognition command signals
results

provides the extracted features of voice signals andcurrent status of the users’ abilities to improve theirspeech skills. The details of the system are described in
the following subsections.

Domestic
appliances

Operator

The structure of the voice signal processing is shown in
Fig. 1. First, the amplitude and timing information ofvoice signals are extracted, and discrimination results arethen obtained using the candidate words/phenomes
Wh/Mh and the log-likelihoods T (Wh) with the candidate
word discrimination method [5].

VolumeTimingCandidate word

(L)
(L)

Microphone

Fig. 1. Structure of the proposed training system

2.1.1. Extraction of voice signal features

M11
M21

PC

Voice signals are recorded using a microphone andsampled at 16 [kHz]. The amplitude information v(t) of
the measured voice signals with full-wave rectificationand low-pass filtering (cut-off frequency: 1 [Hz]) is
obtained based on the gains of the amplifier andmicrophone input levels.
Feature vector X used for speech recognition is thendefined as the low-frequency components of Melfrequency cepstrum coefficients (MFCCs) for each frame,
and the output probabilities P(X|W) of a feature vector X
from word W = {w1, w2, …, wK} (wk: word, K: number ofwords) are calculated using an N-gram model andphoneme-hidden Markov model (phoneme HMM)
dividing the words W into phonemes m = {m1, m2, …,
mJ} (mj: phoneme, J: number of phonemes) and matchingphoneme HMM to X. Subsequently, the top H words Wh(h = 1, 2, …, H) with the maximum log-likelihood, theirphonemes Mh, and log-likelihoods T(Wh) are extractedusing Julius [8].

Microphone(a) Volume training(b) Tempo/timing
training(c) Candidate word
speech training

Fig. 2. Scenes from the training

to phoneme (L)Mci (i = 1, 2, …, Ic; Ic: number of learning
data for class c) of each discrimination class memorized
in the learning-type LUT. The coincidence 𝑠 , between(D)
Mu and (L)Mci is then calculated, and a class with amaximum value of 𝑟 representing the average of all𝑠 , values (the number of coincident phonemes) is thentaken as the discrimination result. To disambiguate
discrimination, the difference between log-likelihoods
T((D)Wu) and T((L)Wci) is used to determine the result when
the same values for some classes are obtained.
2.2. Speech training for candidate word
discrimination method
For speech therapy, the treatment of articulation,
prosody and pitch range, speech rate, vocal volume, or
resonance is important [6]. The proposed speech trainingis therefore composed of three stages (see Fig. 2), as
explained in the following subsections.
Before the training, to make the learning data sets usedin each training, the trainee is instructed to utter C words
T times, and the maximum/minimum and averagevolumes of each word are determined. The durations of
C× T words [startDct, endDct] used in the timing/tempo
control training are also determined using Julius [8].

2.1.2. Intention estimation using candidate word
discrimination
The user’s intention is discriminated using the learningtype look-up table (LUT) [5]. The user is instructed toutter C words (corresponding to the control commands ofdomestic appliances) multiple times, and top V words Wcv
with their maximum log-likelihood and their phonemes
Mcv and log-likelihood T(Wcv) in H extracted words arecorresponded to each discrimination class (c = 1, 2, …,
C; v = 1, 2, …, V; V < H) in the learning stage. In thediscrimination stage, a new set of H words are extracted,
and the phenomes (D)Mu (u = 1, 2, …, U; U < H) of top U
words with their maximum log-likelihood are compared136

Journal of Robotics, Networking and Artificial Life, Vol. 5, No. 2 (September 2018) 135-138___________________________________________________________________________________________________________

2.2.1. Volume control training

3.

In this training, the trainee practices adjusting the vocal
volume level. During the training, the amplitude
information extracted from a measured voice signal ispresented on the display with the desired values(predetermined maximum/minimum and average). The
trainee controls his/her voice signal so the extracted
amplitude information follows the average value andfalls within the min./max. range. The training result isevaluated using the following equation.
𝑆

100

𝑉
0

𝑣 t

𝑣 t
𝑉
𝑣 t ,𝑣 t

𝑉𝑉

3.1. Method
To verify the efficacy of the proposed training system,
training experiments were performed with three healthy
males (subjects A–C, 22.3
1.15 [year]). In theexperiments, participants were instructed to speak with
their tongue touching the maxillary central to simulateslurred speech. The parameters used in the experiments
were set as C = 7, T = 10, H = 10, V = 10, U = 5, D = 10,
𝐿1, 𝐷= 10, 𝐷
= 500, and 𝑆 =50. The otherparameters, K, J, and Ic, were adjusted based on the input
voice signal durations and learning procedure results.
Ten sessions of each training stage were performed in the
training experiments, and discrimination experiments
were also performed before and after training to verify
the effectiveness of the proposed training method. In thediscrimination experiments, participants were asked toutter each word three times without feedback.

. 1

𝑉

The closer the amplitude information is to the average,
the higher the score, and if it exceeds the min./max.
values, the score becomes zero. The average of the 𝑆
value of speech duration is output at the end of each trial.
2.2.2. Tempo/timing control training
For accurate discrimination using the candidate word
discrimination method, it is also important to control thetiming and time from the start to the end of speech. In thistraining, the trainee controls the tempo/timing of his/herspeech. During the training, the stored voice signals ofeach word are randomly shown in the display. The trainee
is instructed to regulate his/her speech duration andtiming according to the pre-specified timing shown in
waveforms. The system evaluates the ratio of extracted
speech duration to pre-specified duration in this training.

3.2. Results and discussion
Figure 3 shows examples of experimental results. From
this figure, the training scores are stable as the number ofsessions increased, and the average discrimination rates
before and after training have relatively high accuracy.
Although participants simulated slurred speech, they
could utter each word the same way from the beginningof the training.
Therefore, other training experiments were performed so
the participants could mimic other participants’ speech.
In the experiments performed, Sub. A trained using Subs.
B and C’s learning data sets. These experimental results
are shown in Fig. 4, and it is confirmed that Sub. A cannot
follow other participants’ speech during 10 training
sessions. An additional 10 training sessions were
therefore performed with words, the score of which was
below 40. In the latter 10 sessions, each score was
gradually increased as the number of training sessions
increased. The average discrimination rates before andafter 20 training sessions were 61.90 48.56 [%] and
80.95
39.27 [%], respectively, and the significant
difference before and after training was confirmed at alevel of 1 [%]. These outcomes indicated that the
proposed training system was capable of speech training.

2.2.3. Candidate word speech training
Candidate word speech training is conducted so thetrainee speaks approximately the same way every time.
The candidate phonemes for each discrimination word
and extracted trainee’s phonemes are shown in thedisplay during this training. The trainee practices tocontrol his/her speech so similar candidate phonemes are
extracted. The score of this training is defined as a ratioof the number of complete/ambiguous coincidence incandidate and extracted phonemes:
𝑆

⎧ 100
100
⎨
⎩

𝑆

/𝐷

𝐿

𝑀 ,𝑀

𝑆

/𝐷

0

𝐿

0

𝐿

0

𝑀 ,𝑀
𝐿

𝐿

Training Experiments

, (2)

𝑀 ,𝑀

where 𝐿 ∙ represents Levenshtein distance.

137

Journal of Robotics, Networking and Artificial Life, Vol. 5, No. 2 (September 2018) 135-138___________________________________________________________________________________________________________

4. Conclusion(a) Volume training(b) Tempo/Timing training(c) Candidate word speechtraining
Fig. 3. Experimental results(d) Discrimination rates

This paper proposes a speech training system for thevoice signal controlled ECS based on candidate word
discriminations. The proposed training system provides
three types of speech training that are important to speakin the same way every time. In the training experiments,
it could be confirmed that the trainees’ speech skills were
gradually improved through training using the proposedsystem.
In future work, the authors plan to perform training
experiments for patients with dysarthria and establish an
online tuning method of training levels for each stage.
Acknowledgements
This work was partially supported by JSPS/MEXT
KAKENHI Grant Numbers 17K12723 and 26330226.
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December 2017).

(a) Volume training(b) Tempo/Timing training(c) Candidate word speech training(d) Discrimination rates
Fig. 4. Experimental results using the other subjects’learning data sets (Sub. A).

138

3. プロジェクト業績

【特許】
1)

2)
3)
4)
5)

米山一樹, 吉田麗生, 小林鉄太郎, 川原祐人, 冨士仁, "鍵配送システム及び方法、鍵生成装置、代表ユーザ端末、サーバ装置、ユーザ端末並びにプロ グラム", 国際出願,
PCT/JP2018/17124
外岡秀行，室伏拓実，須佐綾太，伊藤達男，"路面状態検知装置", 国内出願, 2018158827
藤芳明生，“検索システム、検索方法、及び検索プログラム”，国内出願，2018-159778
米山一樹, 岡野裕樹、吉田麗生, 小林鉄太郎, "通信システム、サーバ装置、通信端末、
通信方法、及びプログラム", 国内出願, 2018/179336
羽渕裕真，金森勝美，イット ワンシット，”無線制御装置、無線通信装置および無線通信システム”,国内出願, 2018-093910【学術誌論文】
1)

Taro Shibanoki, Masaki Watanabe, Go Nakamura, Takaaki Chin and Toshio Tsuji, “A Training
Method for the Speech Controlled Environmental Control System Based on Candidate Word
Discriminations”, Journal of Robotics, Networking and Artificial Life, Vol. 5, No. 2(September 2018), pp. 135-138, 2018.

2)

Kanako Komiya, Minoru Sasaki, Hiroyuki Shinnou, Manabu Okumura, “Domain Adaptation
using Word Embeddings for Word Sense Disambiguation”, 自然言語処理, Vol.25, No.4
(September 2018), pp.463-480.

3)

Kanako Komiya, Masaya Suzuki, Tomoya Iwakura, Minoru Sasaki, Hiroyuki Shinnou,“Comparison of Methods to Annotate Named Entity Corpora”, ACM Transactions on Asianand Low-Resource Language Information Processing (TALLIP), Volume 17 Issue 4, (August2018) Article No. 34．

4)

Kazuki Yoneyama, Reo Yoshida, Yuto Kawahara, Tetsutaro Kobayashi, Hitoshi Fuji, Tomohide
Yamamoto, "Exposure-Resilient Identity-Based Dynamic Multi-Cast Key Distribution", IEICE
Trans. on Fundamentals, vol.E101.A, No.6, pp.929-944, Jun. 2018.

5)

Shota Suto, Toshiya Watanabe, Susumu Shibusawa and Masaru Kamada: Multi-touch tabletop
system using infrared image recognition for user position identification, Sensors, Special issue- Advances in Infrared Imaging: Sensing, Exploitation and Applications, Vol. 18, No.5, 1559
(18 pages) , May 2018.

6)

Daiki Ito, Michitoshi Niibori and Masaru Kamada: Real-time web-cast system by multihop
WebRTC communications, International Journal of Grid and Utility Computing, Vol.9, No.4,
pp.345-356, Sep. 2018.

7)

Keisuke Osawa, Hiromasa Habuchi, and Yusuke Kozawa : "Theoretical Analysis on Bit Error
Rate of Visible-Light Variable N-parallel Code-Shift-Keying", IEICE Transaction on
Fundamentals, Vol.E101-A, No.12, pp.2352-2358, (2018-12)

8)Yusuke Matsuda, Yusuke Kozawa and Yohtaro Umeda: "Experimental Evaluation of Hybrid

1

PWM/DPAM Dimming Control Method for Digital Color Shift Keying Using RGB-LED
Array", Journal of Signal Processing, Vol. 22, No. 4, pp. 165-168, July 2018.
9)

榑林雄飛, 外岡秀行: "衛星画像の影解析及び反復的 3D モデリングによる建物の高さ推定", 日本リモートセンシング学会誌, Vol. 38, No. 2, pp. 137-148, April 2018.

10) Wakaha Ogata, Kaoru Kurosawa: No-Dictionary Searchable Symmetric Encryption. IEICE
Transactions 102-A(1): 114-124 (2019)【国際会議論文】
1) Akinaga Ueda, Hayato Tada, Kaoru Kurosawa: (Short Paper) How to Solve DLOG Problem with
Auxiliary Input. IWSEC 2018: 104-113
2) Hayato Tada, Akinaga Ueda, Kaoru Kurosawa: How to Prove KDM Security of BHHO. IWSEC
2018: 281-296
3) Taro Shibanoki, Yuki Koizumi, Bi Adriel Jr. Yozan and Toshio Tsuji, “Selection of Motor
Imagries for Brain–Computer Interfaces Based on Partial Kullback–Leibler Information
Measure”, The Second Annual IEEE Life Sciences Conference (LSC), Montreal, Canada, 28-30
October, 2018 (accepted).
4) Kazuya Hashimoto, Taro Shibanoki, Go Nakamura, Takaaki Chin and Toshio Tsuji, “A Dualarm Cooperation Training System for Myoelectric Prosthetic Hand Control”, The Second AnnualIEEE Life Sciences Conference (LSC), Montreal, Canada, 28-30 October, 2018 (accepted).
5) Hiroyuki Shinnou, Xinyu Zhao and Kanako Komiya, “Domain Adaptation Using a Combinationof Multiple Embeddings”, PACLIC 2018, Hong Kong, China, 1-3 December, 2018.
6) Masaya Suzuki, Kanako Komiya, Minoru Sasaki and Hiroyuki Shinnou, “Fine-tuning for Named
Entity Recognition Using Part-of-Speech Tagging”, PACLIC 2018, Hong Kong, China, 1-3
December, 2018.
7) Jing Bai, Hiroyuki Shinnou and Kanako Komiya, “Domain Adaptation for Sentiment Analysis
using Keywords in the Target Domain as the Learning Weight”, PACLIC 2018, Hong Kong,
China, 1-3 December, 2018.
8) Aya Tanabe, Kanako Komiya, Masayuki Asahara, Minoru Sasaki and Hiroyuki Shinnou,“Detecting Unknown Word Senses in Contemporary Japanese Dictionary from Corpus ofHistorical Japanese”, JADH 2018, Tokyo, Japan, 9-11 September, 2018.
9) Kanako Komiya, Hiroyuki Shinnou, “Investigating Effective Parameters for Fine-tuning of Word
Embeddings Using Only a Small Corpus”, DeepLo 2018, Workshop of ACL 2018, pp. 60-67,
Melbourne Australia, 19 July, 2018.
10) Rui Suzuki, Kanako Komiya, Masayuki Asahara, Minoru Sasaki and Hiroyuki Shinnou, “Allwords Word Sense Disambiguation Using Concept Embeddings”, LREC 2018, pp.1006-1011,
Miyazaki Japan, 9-11 May, 2018.
11) Cheng Shi, Kazuki Yoneyama, "Verification of LINE Encryption Version 1.0 using ProVerif",
International Workshop on Security (IWSEC 2018), LNCS11409, pp.158-173, Sep. 2018.
12) Atsushi Fujioka, Kazuki Yoneyama , "Single Private-Key Generator Security Implies Multiple
Private-Key Generators Security", International Conference on Provable Security (ProvSec
2018), LNCS11192, pp.56-74, Oct. 2018.
13) Shintaro Terada, Kazuki Yoneyama, "Improved Verifiable Delegated Private Set Intersection",International Symposium on Information Theory and its Applications (ISITA 2018), pp.552-556,
Oct. 2018.
14) Yuma Kanai, Kazuki Yoneyama, "On Hiding Access Timings in ORAM", International

2Symposium on Information Theory and its Applications (ISITA 2018), pp.548-551, Oct. 2018.
15) Atsushi Fujioka, Katsuyuki Takashima, Shintaro Terada, Kazuki Yoneyama, "Supersingular
Isogeny Diffie-Hellman Authenticated Key Exchange", International Conference on Information
Security and Cryptology (ICISC 2018), LNCS11396, pp.177-195, Nov. 2018.
16) Shotaro Naiki, Masaki Kohana, Shusuke Okamoto and Masaru Kamada: A graphical front-end
interface for React.js. In: L. Barolli et al. (eds.), Advances in Network-based Information
Systems (Proceedings of the 21st International Conference on Network-based Information
Systems, NBiS-2018), Lecture Notes on Data Engineering and Communications Technologies
22, Springer, pp.887-896, Sep. 2018.
17) Shinya Kinoshita, Michitoshi Niibori and Masaru Kamada: An attendance management systemcapable of mapping participants onto the seat map. In: L. Barolli et al. (eds.), Advances in
Network-based Information Systems (Proceedings of the 21st International Conference on
Network-based Information Systems, NBiS-2018), Lecture Notes on Data Engineering andCommunications Technologies 22, Springer, pp.897-902, Sep. 2018.
18) Yasuhiro Ohtaki: An image source checker for educational presentation materials In: L. Barolli
et al. (eds.), Advances in Network-based Information Systems (Proceedings of the 21stInternational Conference on Network-based Information Systems, NBiS-2018), Lecture Notes
on Data Engineering and Communications Technologies 22, Springer, pp.903-912, Sep. 2018.
19) Minoru Sasaki: Multi-Domain Word Embeddings for Semantic Relation Analysis among
Domains. Fourth Asia Pacific Corpus Linguistics Conference (APCLC2018), Sep. 2018
(Accepted).
20) Minoru Sasaki: Word Embeddings of Monosemous Words in Dictionary for Word Sense
Disambiguation. The Twelfth International Conference on Advances in Semantic Processing(SEMAPRO2018), Nov. 2018 (Accepted).
21) Yasutomo Kimura, Minoru Sasaki: Stance Classification Using Political Parties in Tokyo
Metropolitan Assembly Minutes. The Seventh International Conference on Data Analytics(DATA ANALYTICS 2018), Nov. 2018 (Accepted).
22) Mamoru Fujiyoshi, Akio Fujiyoshi, Hiroshi Tanaka and Toru Ishida, Universal Design Tactile
Graphics Production System BPLOT4 for Blind Teachers and Blind Staffs to Produce Tactile
Graphics and Ink Print Graphics of High Quality, 16th International Conference on Computers
Helping People with Special Needs (ICCHP 2018), LNCS 10897, pp.167-176, July 201823) Masaki Kohana, Hiroki Sakaji, Akio Kobayashi, A Parallel Calculation Method on Web Browser
for Contents Categorization, The 32th International Conference on Advanced Information
Networking and Applications Workshop (WAINA-2018), pp. 40-44, May 201824) Masaki Kohana, Shusuke Okamoto, A Location-Based Web Browser Network for Virtual Worlds,
In: L. Barolli et al. (eds.), Advances in Network-based Information Systems (Proceedings of the
21st International Conference on Network-based Information Systems, NBiS-2018), Lecture
Notes on Data Engineering and Communications Technologies 22, Springer, pp. 929-936, Sep
201825) atsuya Ohyanagi, Tomoyuki Ishida, Noriki Uchida, Yoshitaka Shibata, and Hiromasa Habuchi:"Proposal of a Disaster Support Expert System Using Accumulated Empirical Data", The 12th
International Conference on Innovative Mobile and Internet Services in Ubiquitous Computing(IMIS-2018), July 201826) Yutaka Imaizumi, Hiromasa Habuchi, and Koichiro Hashiura : "Improved Packet Success Rateon MC-CDMA based On-demand WSN System with MPOMS", IEEE Vehicular Technology
Society Asia Pacific Wireless Communications Symposium (APWCS 2018), Aug. 2018327) Hikari Iiduka, Hiromasa Habuchi, and Yusuke Kozawa : "Proposal of VN-CSK System having
Positioning Function", IEEE Vehicular Technology Society Asia Pacific WirelessCommunications Symposium (APWCS 2018), Aug. 201828) Tomofumi Haruna, Hiromasa Habuchi, and Yusuke Kozawa : "Theoretical Analysis of OpticalWireless Code Shift Keying System using Extended Einarsson Code", IEEE VehicularTechnology Society Asia Pacific Wireless Communications Symposium (APWCS 2018), Aug.
201829) Yuto Asano, Hiromasa Habuchi, and Yusuke Kozawa : "Exact Bit Error Rate Analysis for
Optical-Wireless Framed-DOOK System", IEEE 7th Global Conference of Consumer
Electronics (GCCE 2018), Oct. 201830) Takashi Tokunaga, Hiromasa Habuchi, Yusuke Kozawa, and Ran Sun: "BER Performance
Impaired by Transmission Time Offset Between Users in Optical Wireless CSK/ACDMA
System Using DMPOMs", IEEE 7th Global Conference of Consumer Electronics (GCCE2018), Oct. 201831) Yutaka Imaizumi, Hiromasa Habuchi, and Yusuke Kozawa : "Enhanced On-demand WSN in
terms of MC-CDMA with MPOMS", IEEE International Symposium on Intelligent Signal
Processing and Communication Systems (ISPACS 2018), Ishigaki, pp.102-106, (2018-11-28)
32) Run Sun, Hiromasa Habuchi, and Yusuke Kozawa : "Proposal of Optical Wireless Turbo Coded
System with Hybrid PPM-OOK Signalling", International Conference on Signal Processing andCommunication Systems (ICSPCS 2018), Cairns, Australia, (2018-12-18)
33) Yuto Asano, Hiromasa Habuchi, and Yusuke Kozawa : "Frame Error Detection Performance of
Optical-Wireless Advanced Framed-DOOK System", International Conference on Signal
Processing and Communication Systems (ICSPCS 2018), Cairns, Australia, (2018-12-19)34) Lu Yangzhicheng, Tomoyuki Ishida, Hiromasa Habuchi : "Proposal of a Furniture Layout
Simulation System using Mixed Reality Technology", The 24th International Symposium on
Artificial Life and Robotics pp.808-811, (2019-01-24)
35) Ryo Nakai, Tatsuya Ohyanagi, Tomoyuki Ishida, Hiromasa Habuchi : "Proposal of a Scalable
Interactive Visualization Environment using Large Display in Emergency", The 24th
International Symposium on Artificial Life and Robotics pp.812-815, (2019-01-24)
36) Hikari Iizuka, Ran Sun, Hiromasa Habuchi, and Yusuke Kozawa : "High Accuracy Positioning
System on Indoor Optical Wireless VN-CSK System",RISP International Workshop on
Nonlinear Circuits, Communication and Signal Processing (NCSP'19), (2019-03-05)
37) Yuta Asano, Hiromasa Habuchi, and Yusuke Kozawa : "Effective Frame Error Detecting Scheme
for Optical-Wireless Advanced Framed-DOOK System",RISP International Workshop on
Nonlinear Circuits, Communication and Signal Processing (NCSP'19), (2019-03-05)
38) Ryuichi Takahashi, Kazuma Nishida, Yoshiaki Fukazawa: "Recommendation of Web Service
Selection Algorithm Based on Web Application Review", IEEE TENCON2018, Oct. 2018.
39) Ryuichi Takahashi, Kazuma Nishida, Yoshiaki Fukazawa:" Recommendation Method forService Selection Algorithm Based on User Preference", CSAE2018, Oct. 2018.
40) Hideyuki Tonooka, Yudai Mizoguchi: "Release of the Satellite-based Lake and Reservoir
Temperature Database in Japan (SatLARTD-J) Version 3", 17th World Lake Conference, Oct.
2018.
41) Yuki Watanabe, Masanao Kobayashi, Noboru Nakamichi, Rieko Inaba,Shinya Watanabe,
Takashi Hasuike, Takeo Tatsumi, Tomoharu Ugawa, Yasuhiro Ohtaki, Yoshifumi Yamamoto, Kei
Onishi, Toshio Matsuura, Hiroshi Ishikawa: “Transition of Information Studies on Japanese
Secondary Education - Meta Text Analysis of the Government Course Guidelines”, 17th Hawaii

4International Conference on Education 2019 (HICE2019), Jan. 2019.
42) Ryota Kimoto, Yusuke Kozawa, Yohtaro Umeda, Hiromasa Habuchi: “Underwater Visible Light
Simultaneous Wireless Information and Power Transfer using Inverse Pulse Position Modulation
Scheme”, RISP International Workshop on Nonlinear Circuits, Communications and Signal
Processing 2019 (NCSP 2019), March 2019.
43) Kazuya Hashimoto, Taro Shibanoki, Go Nakamura, Takaaki Chin and Toshio Tsuji, “A Dualarm Cooperation Training System for Myoelectric Prosthetic Hand Control”, The Second AnnualIEEE Life Sciences Conference (LSC), 2pages, Montreal, Canada, 28-30 October, 2018.
44) Taro Shibanoki, Yuki Koizumi, Bi Adriel Jr. Yozan and Toshio Tsuji, “Selection of Motor
Imagries for Brain–Computer Interfaces Based on Partial Kullback–Leibler Information
Measure”, The Second Annual IEEE Life Sciences Conference (LSC), pp. 243-246, Montreal,
Canada, 28-30 October, 2018.
45) Kazuma Nishida, Ryuichi Takahashi and Yoshiaki Fukazawa, “ Fault-tolerant Topology
Determination for IoT Network”, The 13th International Conference on Ubiquitous Information
Management and Communication, Phuket, Thailand, 4-6 January, 2019.
46) Mitsumasa Ota, Ryuichi Takahashi and Yoshiaki Fukazawa, “ FAULT-TOLERANTTOPOLOGY CONTROL FOR IOT NETWORKS USING VARIABLE KCONNECTIVITY” , 9th International Conference on Internet Technologies & Society 2019,
Hong Kong, China, 8-10 February, 2019.
47) Ryu Sakamoto, Ryuichi Takahashi and Yoshiaki Fukazawa, “ STABILITY-BASED LIVEMIGRATION USING DYNAMIC MARGIN ” , 9th International Conference on Internet
Technologies & Society 2019, Hong Kong, China, 8-10 February, 2019.
48) Hiroki Sakaji, Akio Kobayashi, Masaki Kohana, Yasunao Takano, Kiyoshi Izumi, “Estimationof Tags using Various Data for Online Videos,” The 33rd International Conference on Advanced
Information Networking and Applications, Matsue, Japan, 27-29 March, 201949) Yasunao Takano, Yusuke Iijima, Kou Kobayashi, Hiroki Sakaji, Masaki Kohana, Akio
Kobayashi, “Improving Document Similarity Calculation using Cosine-Similarity Graphs,” The
33rd International Conference on Advanced Information Networking and Applications, Matsue,
Japan, 27-29 March, 201950) Hideyuki Tonooka, Yudai Mizoguchi, Release of the Satellite-based Lake and Reservoir
Temperature Database in Japan (SatLARTD-J) Version 3, Proc. of 17th World Lake Conference,
pp. 1254-1256, October, 2018.
【招待講演】
1) 黒澤馨、「辞書無し検索可能暗号について」、情報理論とその応用シンポジウム、特別セッション（情報セキュリティ）、2018.12.21.
2) 黒澤馨、「検索可能暗号について」、総務省委託研究ＳＣＯＰＥプロジェクト（中央大学）主催シンポジウム、2019.2.23【研究会等】
1) 佐々木 稔, 古宮 嘉那子, 新納 浩幸，単語の分散表現を用いた領域における出現単語の特徴分析，言語資源活用ワークショップ 2018， pp. 552-559, (2018,09,05).
2) 新納浩幸，鈴木類，古宮嘉那子, 双方向 LSTM による分類語彙表番号を語義とした allwords WSD，言語資源活用ワークショップ 2018， pp. 192-202, (2018,09,04).
3) 田邊絢，古宮嘉那子，浅原正幸，佐々木稔，新納浩幸, 日本語歴史コーパスの現代語辞書における未知語義判定システム，言語資源活用ワークショップ 2018，pp. 112-117,

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9)

10)
11)
12)
13)

14)

15)

16)
17)
18)
19)
20)

21)
22)

(2018,09,04).
柳沼 大輝, 古宮 嘉那子, 新納 浩幸, 分散表現のファインチューニングによる語義曖昧性解消の 領域適 応, 情報 処理学会 研究 報告 自然 言語処理（ NLP ） ，2018-NL-236,(2018,07,09).
佐々木 稔，短文に対する補助文脈を考慮した語義曖昧性解消，電子情報通信学会 言
語理解とコミュニケーション研究会テキストアナリティクス・シンポジウム，NLC2018-18,(2018,09,06).
佐々木 稔，木村 泰知，Gaussian LDA を用いた地方議会会議録のトピック分析，言語処
理学会第 25 回年次大会, (2019,03,14)
木村 泰知，佐々木 稔，東京都議会の会派を用いた Stance classification の試み，言語処
理学会第 25 回年次大会, (2019,03,15)
久野和敏，小飼敬，上田賀一：グラフデータベースを用いたモデル検査手法の提案，情報処理学会研究報告，ソフトウェア工学(SE)，2018-SE-198(9) (2018,03,02)
堀田大貴，平山秀昭，早瀬健夫，田原康之，大須賀昭彦：プロセスマイニングにおけるビ
ジネスプロセスモデルの自動修正に対応したゴールモデルの修正手法，信学技報, vol.
118, no. 116, AI2018-1, pp. 1-6, (2018,07,02)．
羽渕裕真, 金森勝美, イット ワンシット : "スパースな疑似雑音符号を用いる DS/CDMA",
電子情報通信学会ワイドバンド研究会, WBS2018-1, pp.1-5, (2018-05-17)
春名智文, 羽渕裕真, 小澤佑介 : "光無線 CSK システムへの拡張 Einarsson 符号の適用
性", 電子情報通信学会ワイドバンド研究会 WBS2018-8, pp.17-22, (2018-07-06)
飯塚暉, 羽渕裕真, 小澤佑介 : "光無線 VN-CSK システムにおける測位性能の検討", 電子情報通信学会ワイドバンド研究会 WBS2018-9, pp.23-27, (2018-07-06)
今泉豊, 大川智広, 羽渕裕真, 橋浦康一郎 : "変形擬直交 M 系列対を用いるオンデマン
ド型 WSN におけるパケット成功率向上法", 電子情報通信学会ワイドバンド研究会,
WBS2018-11, pp.35-40, (2018-07-06)
浅野裕太, 羽渕裕真, 小澤佑介 : "光無線フレーム化 DOOK システムにおける同期シンボルによる誤り検出法の検討", 電子情報通信学会ワイドバンド研究会, WBS2018-16,
pp.59-63, (2018-07-06)
徳永岳, 孫冉, 羽渕裕真, 小澤佑介 : "DMPOMs を用いる光無線 CSK システムにおける同期性能を考慮した誤り率性能", 電子情報通信学会ワイドバンド研究会, WBS2018-17,
pp.65-70, (2018-07-06)
羽渕裕真, 金森勝美, イット ワンシット : "拡張 Einarsson 符号に変形擬直交 M 系列を融合する CSK", 電子情報通信学会ソサイエティ大会, A-9-6, (2018-09-11)
イット ワンシット, 金森勝美, 羽渕裕真 : "UWB インパルス無線における符号分割多元接続方式の検討", 電子情報通信学会ソサイエティ大会, A-9-7, (2018-09-11)
浅野裕太, 羽渕裕真, 小澤佑介 : "誤り検出可能な光無線フレーム化 DOOK システム",
革新的無線通信技術に関する横断型研究会 MIKA2018, 3-13, (2018-09-27)
孫冉, 羽渕裕真, 小澤佑介 : "光無線通信におけるハイブリッド PPM-OOK ターボ符号システム", 革新的無線通信技術に関する横断型研究会 MIKA2018, 3-14, (2018-09-27)
木元亮太, 小澤佑介, 楳田洋太郎, 羽渕裕真 : "光強度変復調法を用いた水中可視光ワ
イヤレス給電通信システムに関する基礎検討", 革新的無線通信技術に関する横断型研究会 MIKA2018, 3-17, (2018-09-27)
陳力源, 羽渕裕真: "SIK を用いる多視覚秘密分散法によるマルチルートネットワーク", 革
新的無線通信技術に関する横断型研究会 MIKA2018, 4-2, (2018-09-27)
浅野裕太, 羽渕裕真, 小澤佑介:"拡張フレーム化 DOOK システムのためのフレーム誤り
検 出 法 の 検 討 ", 電 子 情 報 通 信 学 会 ワ イ ド バ ン ド 研 究 会 ,WBS2018-30(ITS2018-

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24)

25)

26)
27)
28)

29)
30)
31)
32)

33)
34)
35)

36)

37)
38)
39)

40)

13,RCC2018-61),pp.17-21, (2018-12-06)
木元亮太, 小澤佑介, 楳田洋太郎, 羽渕裕真 : "反転パルス位置変調方式を用いた水中
可視光ワイヤレス給電通信システムに関する基礎検討", 電子情報通信学会ワイドバンド
研究会, WBS2018-32 (ITS2018-15, RCC2018-63), pp.29-34, (2018-12-06)
孫冉, 羽渕裕真, 小澤佑介 : "ハイブリッド PPM-OOK 信号形式を用いる光無線パンクチャードターボ符号システムの検討", 電子情報通信学会ワイドバンド研究会,WBS2018-72(ITS2018-55, RCC2018-103), pp.249-253, (2018-12-07)
真中佳祐, 陳力源, 羽渕裕真, 小澤佑介 : "VN-CSK 照明可視光通信における等重み(2,2)視覚復号型秘密分散法", 電子情報通信学会東京支部学生会研究発表会, (2019-0302), 発表予定
木口朋洋, 孫冉, 羽渕裕真, 小澤佑介 : "光無線 PPM-OOK システムのためのフレーム
同期法 ", 電子情報通信学会東京支部学生会研究発表会, (2019-03-02), 発表予定
鈴木暁大, 羽渕裕真 : "フレーム ALOHA を用いる MPSC-PDMA 方式", 電子情報通信学会東京支部学生会研究発表会, (2019-03-02), 発表予定
孫冉, 羽渕裕真, 小澤佑介 : "光無線通信ターボ符号システムにおける信号伝送形式の一検討", 電子情報通信学会 WBS/IT/ISEC 合同研究会, WBS2018- (IT2018- ,ISEC2018- ),(2019-03-07), 発表予定
今泉豊, 羽渕裕真, 橋浦康一郎 : "変形擬直交 M 系列対を用いる ROD-WSN におけるノード間干渉の影響", 電子情報通信学会総合大会, (2019-03-19), 発表予定
小栗勇太, 外岡秀行, 鹿島臨海工業地帯周辺における ASTER/FRP 画像の解析, 日本リモートセンシング学会第 65 回学術講演会論文集, (2018.11.28).
劉 明智, 外岡秀行, MODIS 画像を用いた中国の中小都市におけるヒートアイランドの時系列解析, 日本リモートセンシング学会第 65 回学術講演会論文集, (2018.11.28).
溝口裕大, 外岡秀行, 衛星湖沼水温データベース日本編（SatLARTD-J）を用いた水温－
気温差の季節変動に基づく湖沼分類, 日本リモートセンシング学会第 65 回学術講演会論
文集, (2018.11.28).
外岡秀行, 酒井理人, 粂田綾香, 中右浩二, ALOS-2/CIRC 及び CALET/CIRC のラジオメ
トリック校正の状況, 日本リモートセンシング学会第 65 回学術講演会論文集, (2018.11.27).
小池優希, 外岡秀行, サロマ湖における MODIS 画像の熱力学解析による氷厚推定と現地検証（２）, 日本リモートセンシング学会第 65 回学術講演会論文集, (2018.11.27).
平井暁裕, 外岡秀行, 李 雲慶, 周辺のハイパースペクトル画像を利用したマルチスペク
トル鉱物分類における WorldView-3/SWIR の有効性, 日本リモートセンシング学会第 65回学術講演会論文集, (2018.11.27).
佐久間史洋, 菊池雅邦, 朝木萌奈, 外岡秀行, 加藤創史, 神山徹 : "ASTER TIR の深宇
宙・月校正", 日本リモートセンシング学会第 64 回学術講演会論文集, pp. 185-186,(2018.5.18)
溝口裕大, 外岡秀行 : "衛星湖沼水温データベース日本編 (SatLARTD-J) の準リアルタ
イム更新", 日本リモートセンシング学会第 64 回学術講演会論文集, pp. 45-46, (2018.5.18)
小池優希, 外岡秀行 : "サロマ湖における MODIS 画像の熱力学解析による氷厚推定と現地検証", 日本リモートセンシング学会第 64 回学術講演会論文集, pp. 159-160, (2018.5.17)
小栗勇太, 外岡秀行 : "ASTER 画像を利用した MODIS 熱異常アルゴリズム（MOD14）の性能解析", 日本リモ ートセン シ ン グ学会第 64 回 学術講演会論 文集, pp. 157-158,(2018.5.17)
平井暁裕, 外岡秀行 : "マルチスペクトル画像と周辺のハイパースペクトル画像の組み合わせによる鉱物同定 (2)", 日本リモートセンシング学会第 64 回学術講演会論文集, pp.
127-128, (2018.5.17)

741) 柴田 敏弥, 米山 一樹, "UC 安全動的検索可能暗号の拡張とフォワード安全性について",暗号と情報セキュリティシンポジウム (SCIS 2019), Jan. 2019.
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43) 松井 政裕, 岡野 裕樹, 村上 啓造, 小林 鉄太郎, 米山 一樹, "グループ鍵交換プロトコ
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44) 藤岡 淳, 高島 克幸, 米山 一樹, "同種写像を用いた 1 ラウンド認証グループ鍵共有", 暗号と情報セキュリティシンポジウム (SCIS 2019), Jan. 2019.
45) 寺田 槙太郎, 米山 一樹, "CSIDH に基づくパスワードベース認証鍵交換 ", 暗号と情報
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46) 野口 凌雅, 花谷 嘉一, 米山 一樹, "ProVerif による HEMS におけるグループ鍵管理の検証", 暗号と情報セキュリティシンポジウム (SCIS 2019), Jan. 2019.
47) 師 成, 米山 一樹, "ProVerif によるスマートコントラクト決済委託プロトコルの公平性の検証", 暗号と情報セキュリティシンポジウム (SCIS 2019), Jan. 2019.
48) 勝野 凌介, 米山 一樹, "IC カードとリーダ/ライタ間の認証プロトコルにおける認証再利用と暗号理論的安全性モデルの関係", 電子情報通信学会情報セキュリティ研究会, Mar.
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49) 白井 直輝, 米山 一樹, "検証可能委譲秘匿ビット比較演算", 電子情報通信学会情報セキュリティ研究会, Mar. 2019.
50) 日置千仁, 岡田信一郎, “効果的な反復学習を促す得点計算法の学習失敗への対策とその検証”, 情報処理学会 コンピュータと教育研究会 146 回研究発表会，2018 年 10 月．
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52) 太田光雅, 高橋竜一, 深澤良彰, “IoT ネットワークにおける障害耐性の高いトポロジー生成”, 電子情報通信学会 知能ソフトウェア工学研究会 (SIG-KBSE), 2018 年 7 月．
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8茨城大学重点研究「地域に密着した世界的 ICT イノベーションの創出」
茨城大学工学部附属 ICT グローカル教育研究センター
２０１８年度報告書
発行日

平成 31 年 3 月

発行者

茨城大学 工学部 情報工学科
教授 黒澤 馨〒316-8511 日立市中成沢町 4-12-1
Tel: 0294-38-5135 Fax: 0294-38-5282※禁無断転載茨城大学重点研究
http://www.ibaraki.ac.jp/generalinfo/activity/researching/juuten/

茨城大学工学部附属教育研究センター
http://www.eng.ibaraki.ac.jp/research/centers/index.html

ICT グローカル教育研究センター
http://www.eng.ibaraki.ac.jp/research/centers/ict/index.html