MWS2023プレミーティング

サイバーセキュリティ研究
トレンド2023（の調査⽅法）
2023年6⽉29⽇
NTT 社会情報研究所
秋⼭満昭

論⽂が多すぎる•

Google Scholar••

arXiv（未査読のプレプリント論⽂）••

vulnerability: 約2,430,000,malware: 約145,000件,

Cryptography and Securityカテゴリ︓約200件/週

難関会議採択論⽂の増加•

USENIX Security採択論⽂︓2013年〜2022年の10年間で5倍に増加

300
200
1000
2012

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2017
採択論文数

2022

1

査読付き論⽂ vs. プレプリント
媒体

品質

速報性

査読付き論文高い（投稿先によって大きく異なるが、査読を経るためある程度の品質は担保されている）

低い（投稿から公開までに数ヶ月〜1年以上かかる）

プレプリント

玉石混交（査読を経ていないので品質は担保されていない）

高い（即座に公開される）

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2いい研究（論⽂）を発⾒するために•査読付き論⽂とプレプリントの特性を理解する

•

品質を重視
•

Top-4（やTier-2）国際会議などの論⽂を中⼼に調査する›

Top-4: IEEE S&P, USENIX Security, ACM CCS, ISOC NDSS›

参考: <https://people.engr.tamu.edu/guofei/sec_conf_stat.htm><http://jianying.space/conference-ranking.html>••

引⽤数の多さ（公開間もない論⽂は引⽤がつきにくいので注意）

速報性を重視•プレプリントを調査する•

品質の⾼い論⽂であるかどうかをある程度⾒極める›

完結した論⽂であるか›

著者グループがその分野で実績があるか›

将来の著名国際会議で採択されているか（著者のウェブサイトで確認できることも）

Copyright 2023 NTT CORPORATION

バランスよく調査す
る（速報性だけを重視して時間を浪費しないように）3トレンド︖• 研究対象が多様化しているので⼀⾔で説明できない•

Top-4国際会議のセッション割や論⽂賞を⾒ればわかるかもしれない

Copyright 2023 NTT CORPORATION

4USENIX Security 2022のセッション⼀覧
Client-Side Security

Information Flow

Network Security III: DDoS

Software Security

Crypto I: Attacking Implementations

Kernel Security

Network Security IV

Software Vulnerabilities

Crypto II: Performance Improvements

Measurement I: Network

OS Security & Formalisms

User Studies I: At-Risk Users

Crypto III: Private Matching & Lookups Measurement II: Auditing & Best
Practices
Crypto IV: Databases & Logging
Measurement III
Crypto V: Provers & ShufflingMeasurement IV
Crypto VI
ML I: Federated Learning
Deanonymization
ML II
Differential Privacy
ML III
Fuzzing I: Networks
ML IV: Attacks
Fuzzing II: Low-Level
ML V: Principles & Best Practices
Fuzzing III
ML VI: Inference
Fuzzing, OS, and Cloud Security
Mobile Security
Hardware Security I: Attacks & Defenses
Network Security I: Scanning &Hardware Security II: Embedded
Censorship

Passwords

User Studies II: Sharing

Privacy, User Behaviors, and Attacks

User Studies III: Privacy

Security Analysis

User Studies IV: Policies & Best
Practices

Hardware Security III

Software Forensics

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Network Security II: Infrastructure

Security Practitioners & Behaviors
SGX I & Side Channels III
SGX II
Side Channels I: Hardware
Side Channels II
Side Channels IV
Smart Homes I
Smart Homes II

Web Security I: Vulnerabilities
Web Security II: Fingerprinting
Web Security III: Bots & Authentication
Web Security IV: Defenses
Web Security V: Tracking
Wireless Security
Zero Knowledge

Smart Vehicles

5

CCS 2022のセッション⼀覧
Applied Crypto: Advanced Public-Key
Encryption Schemes

Applied Crypto: Cryptographic Protocols

FM & PL: Security Protocols

Network Security: Internet Security

Based Security

HW & CPS: Aspects of Masking

Network Security: Network Vulnerabilities

Software Security: Fuzzing

HW & CPS: Attacks and Defense

Network Security: Network Vulnerabilities

Software Security: Hardware-Assisted Defense

Applied Crypto: Digital Currencies &Blockchains

HW & CPS: CPS and IoTPriv & Anon: Ads and Location Privacy

Software Security: Hardware-Assisted Defense

Applied Crypto: Digital Signatures

HW & CPS: Side Channels

Priv & Anon: Ads and Location Privacy

Applied Crypto: Key-Exchange

HW & CPS: Side Channels

Priv & Anon: Differential Privacy

Software Security: Information Leakage andAccess Control

Applied Crypto: Secure MultipartyComputation

HW & CPS: Side Channels: Defences

Priv & Anon: Differential Privacy

HW & CPS: Side Channels: Hardware andMicroarchitecture

Priv & Anon: Federated Analytics and Learning

Applied Crypto: Secure Multiparty
Computation & Private- Set Intersection

ML: Adversarial Examples in ML

Applied Crypto: Symmetric-Key Encryption
and Attacks

ML: Adversarial Examples in ML

Applied Crypto: Zero-Knowledge 1

ML: Attacks to ML

Applied Crypto: Zero-Knowledge 2

ML: Federated Learning Security

Blockchain and Distributed Systems

ML: Inference Attacks to ML

Blockchain and Distributed Systems
Blockchain and distributed systems
Blockchain and distributed systems
FM & PL: Hardware Security
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ML: Inference Attacks to ML
ML: ML for Network Security
ML: Poisoning and Backdooring ML
Network Security: Cloud and IoT Security
Network Security: Cloud and IoT Security

Priv & Anon: Online, Mobile and Multimedia
Privacy
Priv & Anon: Online, Mobile and Multimedia
Privacy

Software Security: Vulnerability Detection
Software Security: Vulnerability Detection
Usability & Measurement: Attacks
Usability & Measurement: Attacks
Usability & Measurement: Finding Violations

Priv & Anon: Privacy Attacks in ML

Usability & Measurement: Security and Privacy
Practices

Priv & Anon: Privacy Attacks in ML

Web Security: Client Side Security

Priv & Anon: Privacy in Graphs

Web Security: Server-Side Security

Priv & Anon: Privacy Preserving ML

Web Security: The C in Web Stands for Crypto

Priv & Anon: Secure Query Answering

Web Security: The C in Web Stands for Crypto

Software Security: Analysis

Web Security: Users Under Attack

Software Security: Defenses and Virtualization-6

S&P 2023のセッション⼀覧
Applied cryptography

Infrastructure security

Privacy and covert channels

Authentication

IoT security

Rowhammer and spectre

Biometric securityLow-level software security

Side-channel attacks

Blockchain 1

Machine learning assurance

SMC

Blockchain 2

Machine learning backdoors

Software isolation

Bug finding

Machine learning privacy

Software security

Cryptographic attacks

Malware and malicious sites

Software supply chains

Cryptographic proof techniques

ML attacks

Trust and safety

Cryptographic protocols

ML Security and Privacy

Web security

Election and device recycling

Model-based software security

Web security

Fuzzing

Network security

Human factors

Physical channel attacks

Human factors 2

Physical channels 2

Copyright 2023 NTT CORPORATION7NDSS 2023のセッション⼀覧Blockchains IFuzzing

Software Security I

Blockchains II

Keys and Certification

Software Security II

Cloud and Edge Computing

ML and AI I

Trustworthy Computing

Cyber Attacks

ML and AI II

Usable Security and Privacy

Cyber-Crime and Forensics

ML and AI III

Web Security I

Cyber-Physical Systems
Security I

Mobile Security and Privacy

Web Security II

Network Protocols

Web Security III

Cyber-Physical Systems
Security II

Copyright 2023 NTT CORPORATION

Privacy and Anonymity I
Privacy and Anonymity II8

論⽂賞（distinguished paper awards）•

Variable Names and Types

USENIX Security 2022
•OpenVPN is Open to VPN Fingerprinting•The Antrim County 2020 Election Incident: An
Independent Forensic Investigation•An Audit of Facebook's Political Ad Policy
Enforcement•

Online Website Fingerprinting: Evaluating
Website Fingerprinting Attacks on Tor in theReal World•

Attacks on Deidentification's Defenses•

Identity Confusion in WebView-based Mobile
App-in-app Ecosystems•

Provably-Safe Multilingual Software
Sandboxing using WebAssembly•

Faster Yet Safer: Logging System Via FixedKey Blockcipher•

Private Signaling•FIXREVERTER: A Realistic Bug Injection
Methodology for Benchmarking Fuzz Testing•Dos and Don'ts of Machine Learning in
Computer Security• Augmenting Decompiler Output with Learned
Copyright 2023 NTT CORPORATION••Four Modern CMOS Technology Generations

CCS 2023•

It's (DOM) Clobbering Time: Attack
Techniques, Prevalence, and Defenses•The Leaky Web: Automated Discovery ofCross-Site Information Leaks in Browsers andthe Web•

Victory by KO: Attacking OpenPGP Using Key
Overwriting•

Proving UNSAT in Zero Knowledge•Automatic Detection of Speculative Execution
Combinations•WaVe: a verifiably secure WebAssembly
sandboxing runtime•

Zapper: Smart Contracts with Data andIdentity Privacy•Characterizing Everyday Misuse of SmartHome Devices•

STAR: Secret Sharing for Private Threshold
Aggregation Reporting•

Not Yet Another Digital ID: Privacy-preserving
Humanitarian Aid Distribution•“In Eighty Percent of the Cases, I Select thePassword for Them”: Security and Privacy
Challenges, Advice, and Opportunities atCybercafes in Kenya•

Space Odyssey: An Experimental Software
Security Analysis of Satellites

S&P 2023•

MEGA: Malleable Encryption Goes Awry•

Practically-exploitable Cryptographic
Vulnerabilities in Matrix•

Weak Fiat-Shamir Attacks on Modern ProofSystems•

Typing High-Speed Cryptography against
Spectre v1•

Red Team vs. Blue Team: A Real-World
Hardware Trojan Detection Case Study Across•NDSS 2023•

Your Router is My Prober: Measuring IPv6
Networks via ICMP Rate Limiting SideChannels

9論⽂賞（distinguished paper awards）
CSS（コンピュータセキュリティシンポジウム）で考えるとどのトラックぽい︖
暗号ぽい• Faster Yet Safer: Logging System Via FixedKey Blockcipher• Victory by KO: Attacking OpenPGP Using KeyOverwriting• Proving UNSAT in Zero Knowledge• MEGA: Malleable Encryption Goes Awry
• Practically-exploitable Cryptographic
Vulnerabilities in Matrix• Weak Fiat-Shamir Attacks on Modern ProofSystems• Typing High-Speed Cryptography against
Spectre v1

UWSぽい• Characterizing Everyday Misuse of SmartHome Devices• “In Eighty Percent of the Cases, I Select thePassword for Them”: Security and Privacy
Challenges, Advice, and Opportunities atCybercafes in Kenya

•
••

•
MWSぽい
• Red Team vs. Blue Team: A Real-World•
Hardware Trojan Detection Case Study Across
Four Modern CMOS Technology Generations •• Augmenting Decompiler Output with Learned
Variable Names and Types•
システムorMWSぽい• FIXREVERTER: A Realistic Bug Injection•Methodology for Benchmarking Fuzz Testing

PWSぽい• Attacks on Deidentification's Defenses• Private Signaling• STAR: Secret Sharing for Private Threshold
Aggregation Reporting• Not Yet Another Digital ID: Privacy-preserving システムぽい•
Humanitarian Aid Distribution• OpenVPN is Open to VPN Fingerprinting• The Antrim County 2020 Election Incident: AnBWSぽい
Independent Forensic Investigation• Zapper: Smart Contracts with Data and• An Audit of Facebook's Political Ad Policy
Identity Privacy
Enforcement• Online Website Fingerprinting: Evaluating
Website Fingerprinting Attacks on Tor in theCopyright 2023 NTT CORPORATIONReal WorldIdentity Confusion in WebView-based Mobile
App-in-app Ecosystems
Provably-Safe Multilingual Software
Sandboxing using WebAssembly
Dos and Don'ts of Machine Learning in
Computer Security
Automatic Detection of Speculative Execution
Combinations
It's (DOM) Clobbering Time: Attack
Techniques, Prevalence, and Defenses
The Leaky Web: Automated Discovery ofCross-Site Information Leaks in Browsers andthe Web
WaVe: a verifiably secure WebAssembly
sandboxing runtime
Your Router is My Prober: Measuring IPv6
Networks via ICMP Rate Limiting SideChannels
Space Odyssey: An Experimental Software
Security Analysis of Satellites

10「現場の奥地」からの報告（1）•The Antrim County 2020 Election Incident: An Independent Forensic Investigation (USENIXSecurity 2022)•Investigating State-of-the-Art Practices for Fostering Subjective Trust in Online Voting throughInterviews (USENIX Security 2022)•

Helping hands: Measuring the impact of a large threat intelligence sharing community (USENIXSecurity 2022)•

Why Users (Don't) Use Password Managers at a Large Educational Institution (USENIX Security2022)•RE-Mind: a First Look Inside the Mind of a Reverse Engineer (USENIX Security 2022)•Characterizing the Security of Github CI Workflows (USENIX Security 2022)•

99% False Positives: A Qualitative Study of SOC Analysts' Perspectives on Security Alarms(USENIX Security 2022)

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11

「現場の奥地」からの報告（2）•Understanding the How and the Why: Exploring Secure Development Practices through aCourse Competition (CCS 2022)•SoK: Taxonomy of Attacks on Open-Source Software Supply Chains (S&P 2023)•No One Drinks From the Firehose: How Organizations Filter and Prioritize Vulnerability
Information (S&P 2023)•Vulnerability Discovery for All: Experiences of Marginalization in Vulnerability Discovery (S&P2023)•Everybodyʼs Got ML, Tell Me What Else You Have: Practitioners' Perception of ML-Based
Security Tools and Explanations (S&P 2023)

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12