Reviewerly/exHarmony huggingface dataset:
Practical Attacks on Full-round FRIET

FRIET is a duplex-based authenticated encryption scheme proposed at EUROCRYPT 2020. It follows a novel design approach for built-in countermeasures against fault attacks. By a judicious choice of components, the designers propose the permutation FRIET-PC that can be used to build an authenticated encryption cipher denoted as FRIET-AE. And FRIET-AE provides a 128-bit security claim for integrity and confidentiality. In this paper, we research the propagation of pairs of differences and liner masks through the round function of FRIET-PC. For the full-round FRIET-PC, we can construct a differential distinguisher whose probability is 1 and a linear distinguisher whose absolute value of correlation is 1. Moreover, we use the differential distinguisher with probability 1 to construct a set consisting of valid tags and ciphertexts which are not created by legal users. This breaks FRIET-AE’s security claim for integrity and confidentiality. As far as we know, this is the first practical attack that threatens the security of FRIET-AE.
SCB Mode: Semantically Secure Length-Preserving Encryption

To achieve semantic security, symmetric encryption schemes classically require ciphertext expansion. In this paper we provide a means to achieve semantic security while preserving the length of messages at the cost of mildly sacrificing correctness. Concretely, we propose a new scheme that can be interpreted as a secure alternative to (or wrapper around) plain Electronic Codebook (ECB) mode of encryption, and for this reason we name it Secure Codebook (SCB). Our scheme is the first length-preserving encryption scheme to effectively achieve semantic security.
Exploring Integrity of AEADs with Faults: Definitions and Constructions

Implementation-based attacks are major concerns for modern cryptography. For symmetric-key cryptography, a significant amount of exploration has taken place in this regard for primitives such as block ciphers. Concerning symmetric-key operating modes, such as Authenticated Encryption with Associated Data (AEAD), the stateof-the-art mainly addresses the passive Side-Channel Attacks (SCA) in the form of leakage resilient cryptography. So far, only a handful of work address Fault Attacks (FA) in the context of AEADs concerning the fundamental properties – integrity and confidentiality. In this paper, we address this gap by exploring mode-level issues arising due to FAs. We emphasize that FAs can be fatal even in cases where the adversary does not aim to extract the long-term secret, but rather tries to violate the basic security requirements (integrity and confidentiality). Notably, we show novel integrity attack examples on state-of-the-art AEAD constructions and even on a prior fault-resilient AEAD construction called SIV$. On the constructive side, we first present new security notions of fault-resilience, for PRF (frPRF), MAC (frMAC) and AEAD (frAE), the latter can be seen as an improved version of the notion introduced by Fischlin and Gunther at CT-RSA’20. Then, we propose new constructions to turn a frPRF into a fault-resilient MAC frMAC (hash-then-frPRF) and into a fault-resilient AEAD frAE (MAC-then-Encrypt-then-MAC or MEM).
Adoption of a deep learning-based neural network model in the psychological behavior analysis of resident tourism consumption

With the development of society and the continuous progress of science and technology, it has become the mainstream measure to promote the development of the social economy through science and technology. Therefore, to improve the current situation of tourism consumption, improve the consumer sentiment of tourists, and promote the development of the tourism economy, the convolutional neural network (CNN) technology model is used to analyze the tourist's consumer psychology and behavior. Based on this, the user's consumption situation is analyzed, thus providing support for the intelligent improvement of tourism consumption. First, the basic characteristics of tourism consumption mood and behavior are introduced, and the methods to improve the tourism consumption mood and behavior are briefly introduced. Then, the CNN algorithm is employed to identify consumers' travel consumption behaviors and emotions. To improve the recognition effect, the algorithm is combined with skeleton node behavior recognition and video image behavior recognition. Finally, the performance of the designed algorithm is tested. The accuracy of the human behavior recognition (HBR) algorithm is more than 0.88. Compared with the detection effect of the HBR algorithm, the combined algorithm adopted in this work can reduce the image processing time and improve the detection efficiency. The multithread method can effectively reduce the complexity of the model and improve the recognition accuracy. The test results on different data sets show that the proposed algorithm can better adapt to the changes in identification samples and obtain more accurate recognition results compared with similar algorithms. In summary, this study not only provides technical support for the rational analysis of consumer sentiment and consumer behavior but also contributes to the comprehensive development of the tourism market.
Precise Compensation of Estimated Distance by Pose Estimation using Camera-IMU Sensor Fusion

This paper presents a novel method to correct with only the camera and IMU sensors an estimated distance error due to a rapid change in a vehicle’s posture while driving, as it is very important to estimate the distance of a front car in autonomous driving. To estimate the change in vehicle’s posture, the proposed method adopts a visual odometry method using the optical flow and the camera-IMU fusion. The error in the estimated distance caused by an instantaneous change in the vehicle
Analysis of the Application of the Accurate Accounting System in the Recording of Financial Statements of PT. The Great Ocean Ocean

The Accurate Accounting System is a software tool used by companies to prepare computerized financial reports. This study takes the title Analysis of the Application of Accurate Accounting Systems in the Recording of Financial Statements of PT. The Great Ocean Ocean. This research uses descriptive qualitative method. This study aims to determine how the application of the Accurate Accounting System. Research conducted by the author is a shipping company. This company already uses an Accurate Accounting System in inputting the company's financial statements. The results of this study are that in implementing the Accurate Accounting System there are no obstacles or problems, so it can still make it easier for employees to input financial reports. In implementing an Accurate Accounting System in this company, there are several advantages that are known by researchers. Therefore researchers conducted research on the application of Accurate Accounting Systems in companies.
Use of GIS to Discover the Existence of Terrorism

Threats to national defense can be military or non-military. The greatest unresolved threat and challenge facing the Indonesian state is terrorism. The Indonesian government has dealt with terrorism, but catching terrorists remains difficult. The purpose of this research is to provide an alternative that uses Geospatial Intelligence (GEOINT) to find out where terrorists are hiding. The limitation of this research is the mountainous region in Central Sulawesi Province. The method used in this study is to use the GEOINT approach which is a combination of remote sensing, geographic information systems (GIS) and cartography, to extract information and analyze the results. The analysis was performed using a weighted linear combination method. The quantification process is carried out on all spatial data used for each parameter related to the presence of terrorists in the mountains. Quantification is done by changing each sub-parameter class to a value between 1-5. Each value is then weighted as a coefficient to arrive at the final score. From the results of the analysis and discussion it can be concluded that the GEOINT analysis can be used as an initial research on terrorist hideouts.
Analysis of Financial Management Information Systems in Improving Performance at the Office of the Sub-District Head of Jagong Jeget (Case study of the Office of the Head of Sub-District of Jagong Jeget)

Abstract A financial information system is an information system designed to provide information about money options for users throughout the company. The financial information system is part of the MIS which is used to solve corporate financial problems. In general, the financial information system has an income system consisting of a data processing subsystem supported by an internal audit subsystem that provides internal data and information. For large companies it usually has staff internal auditors. Like other subsystems, this system is also equipped with the financial intelligence subsystem, which collects information from the environment.
Active Reading Style, Student Vocabulary Learning Strategies and Self-regulated Learning: A Structural Model Equation on Academic Writing Motivation and Self-regulation

Aims: To determine the best fit model for students' academic writing motivation and self-regulation.&#x0D; Study Design: Descriptive-causal design.&#x0D; Place and Duration of Study: The study was conducted among senior high school of Region XIII during 2021-2022.&#x0D; Methodology: The respondents were chosen using stratified random sampling. The data were collected using the online platform.&#x0D; Results: Results showed that the respondents had a high level active reading style; their vocabulary learning strategy was always visible; and their self-regulated learning was high. It also revealed that there was a linked between academic writing motivation and self-regulation. There was a significant relationship between active reading in academic writing motivation and self-regulation; between vocabulary learning strategy, academic writing motivation, and self-regulation; between self-learning, academic motivation and self-regulation. Likewise, there was a significant influence of active learning on academic writing motivation and self-regulation, vocabulary learning strategies and self-learning on academic writing motivation and self-regulation. Finally, model 5 was the most suitable for students’ academic writing motivation and self-regulation.&#x0D; Conclusion: There is a substantial association between students' academic writing motivation and self-regulation and active reading, vocabulary learning strategies, and self-learning. The best model for encouraging and regulating students' academic writing is Model 5. It implies that students needed to have motivated so that they are about to control their learning. This outcome serves as a reminder to teachers that in order for students to develop learning independence and trust, teachers must pique their interest in the lessons or classroom activities.
LNGAT: local neighborhood graph attention network (Erratum)

The <i>Journal of Electronic Imaging</i> (JEI), copublished bimonthly with the Society for Imaging Science and Technology, publishes peer-reviewed papers that cover research and applications in all areas of electronic imaging science and technology.
Determining University Students’ Views on Mobile Technology and Moodle Applications in Personalized Learning

The aim of this study is to determine the opinions of university students about mobile technology and Moodle applications, considering that university students continue their lessons through the distance education platform throughout the pandemic, mobile technology will turn into an advantage for them. Quantitative research method was used in the study. The research was conducted in the fall semester of 2021-2022. 270 volunteer university students that study in Kazakhstan participated in the research. In the research, 3-week online training was given to university students. In the research, the "Moodle &amp; Mobile Technology" measurement tool developed by the researchers and compiled by experts in the field was used. The measurement tool was delivered and collected by university students via online method. The analysis of the data was made using the SPSS program, frequency analysis, t-test and anova test, and the results were added to the research with tables and comments. According to the results obtained from the research, it has been concluded that university students have a high opinion of mobile technology and module application.
Comparison of Research Trends of Digital Economy Between China and Foreign Countries—Visual Analysis Based on CiteSpace

The purpose was to analyze the evolution path and cutting-edge trend of digital economy research in China and abroad.The research screened the relevant literature from 1990 to 2020, and the data source came from WoS database and CSSCI index database.CiteSpace software was used for quantitative analysis and comparison of keyword sharing, hot word clustering, time zone division of highfrequency words and discrimination of emerging words.It is found that firstly, the research on digital economy in China and abroad was basically the same in terms of stage division, but the time nodes are different.Foreign countries creatively put forward the concept of digital economy in the 1990s, and then entered the fault period from the incubation period to the current rise period.However, domestic digital economy research has been widely studied in the incubation period, then experienced the fault period and recently entered the rise period.Secondly, Chinese and foreign studies have reflected that digital technology innovation is the core, and the deep integration of digital industry, external governance of digital economy, digital path selection mechanism and other issues are the frontier trends of common concern.
Consumer Behavior Prediction Based on Machine Learning Scenarios

Consumer behavior prediction is an important part of the business analysis and strategy development process.With the development of AI technology, machine learning has been also applied to consumer behavior prediction.This paper introduces some common and novel consumer behavior prediction methods, including decision tree algorithm, recurrent neural networks (RNNs) algorithm, and the application of fMRI in machine learning.The advantages and limitations of these methods are clarified by analyzing the practical cases based on these methods.This paper first introduces the background of consumer behavior prediction and review some existing prediction methods.Subsequently an introduction and review of the three selected prediction methods and the cases they participated in are demonstrated accordingly.Afterwards, the advantages of the three methods and the drawbacks of them are evaluated by analyzing the three cases.Then, some measures are proposed to improve the performance of the models to pave the path for future development of consumer behavior prediction in terms of machine learning supports.These analytical results offer guideline for the future development of consumer behavior prediction.
Application of Computer Database Technology in Information Management Use

With the increasing utilization of computers, the system functions of computers are constantly optimized.In information management, the application of computer database technology makes information management more efficient and convenient.Computer database technology mainly includes parallel database, multimedia database, distributed database, active database, objectoriented database, data mining and database, etc.Database technology carries out high-speed data information sharing in information management, establishes a systematic information database system, and greatly improves the security of information management network data.This paper mainly analyzes the problems of computer database technology in information management and provides solutions.
Time Series Predictive Analysis of Bitcoin Price

As a great innovation in virtual currency, bitcoins have the possibility to survive perpetually, although they are like gigantic bubbles.However, no matter whether bitcoins could survive or not, the technology used by bitcoins will exist and develop.There is a great possibility for bitcoins to be served in the intending currency, being issued, supported, and controlled by the government.Consequently, the research for bitcoins is meaningful.To explore the time relationship of bitcoins and give a prediction about the future price based on the given data, ARIMA and GARCH models are used in this paper.Although both of the two models failed to provide the accurate forecasts at the end of this research, they still proved the correlation within time series of bitcoins.
The Research on Innovative Application of Blockchain Technology in Sharing Economy

In the era of information technology, the sharing economy has become the norm, and the generation of artificial intelligence is inseparable from the synthesis of blockchain technology.Correctly understanding and mastering blockchain technology has a strong practical guiding significance for industrial upgrading and transformation.First of all, the paper briefly describes the domestic and foreign development status of the application of blockchain in the financial field, and analyzes the defects faced by the blockchain industry economy.Secondly, the innovative development and application of blockchain technology in the clearing of financial institutions, cross-border payment, capital financing and leasing, asset securitization and asset custody innovation and development application.Then, a blockchain-based securities trading model is proposed, and the advantages of the method are proved through experimental comparative analysis.Finally, the economic development of the blockchain industry is prospected.
A Blockchain Based Security Scheme for Legal Electronic Service

Electronic service has long been regarded as a significant legal service method for the optimal distribution of limited judicial resources.However, information security remains the major concerns within academia and judicial authorities during the actual application.Within current legal framework, digitization of the whole process was studied systematically and a practical technical scheme was proposed to enhance the security of electronic service system.Based on the research, the information security relies on three aspects, namely the ability for litigants to judge the authenticity of legal documents, identification, encryption and management of crucial data, reliable non-repudiation of key behaviors.To assure the system security, anti-counterfeiting and fidelity techniques were applied to realize the generation and processing of electronic judicial documents; Identification encryption and key partitioning techniques were used to get the document exposed for data safety in transmission; Key behavioral data of the whole process were fixed and stored on alliance chain with network slicing technique to balance the strength and efficiency.Besides, neutrality, confidentiality and convenience of service system were also considered in the architecture.Finally, the innovated scheme was developed and all results were displayed in the paper.
Smart Contract in Blockchain

Smart contract is presented as a new infrastructure for programming, deployment and execution with the rapid pace of blockchain technology in recent years.The development of blockchain technology provides a good operational basis for smart contracts, which can play an important role on the blockchain.With the rapid development of blockchain platforms such as bitcoin, smart contracts have a good opportunity for development.However, smart contract applications are still at an early stage of development, with relatively little relevant research, and the applicable scenarios of smart contracts in practical applications are not rich enough.In the paper, we study and discuss several aspects, by changing decentralization to weak-centralization, retaining appropriate supervision, and providing necessary right remedy for users of non-performance clause, can make smart contracts safe to use by compromising part of transaction efficiency.
A New Time-Effective Weighted Interpolation Method for Color Filter Array Demosaicking

To reduce the cost of storage and size, most digital cameras capture images through a chip whose surface is covered with a color filter array (CFA) where each sensor only samples one of three original color values.To reconstruct a full image, an interpolation process, often called CFA demosaicking, is required to estimate the missing color values.In this paper, a new time-effective weighted interpolation method for CFA demosaicking is proposed.The new algorithm contains three consecutive steps: First, during the interpolation of green plane, the image is divided into three different regions where each of these is handled with different strategies.Second, four-directional weighted interpolation with gradient inverse weighted filtering (GIWF) refinement is utilized in filling the missing red and blue components.Finally, a postprocessing step with 2-dimensional finite impulse response (FIR) filter is used for further enhancement.An analysis of experimental results shows that the proposed algorithm inherits the good traits of edge preservation under lower time cost.
Stacking Model for Financial Fraud Detection with Synthetic Data

With the fast pace development of the Internet nowadays, financial frauds have also emerged continuously, which has seriously affected the development of the financial sector.Due to the lack of data in the financial field and the loose structure of transaction information, financial fraud detection remains a significant challenge.Based on the traditional machine learning model, this paper combines the three basic logistic regression models, support vector machine and random forest, and designs a two-layer stacking prediction model to detect financial transaction fraud.For unbalanced samples, this article uses up-sampling, under-sampling, and fusion methods to test and help search for optimal parameters through GridSearchcv.The final experiment shows that the Stacking model has a 97% recall rate and 87% accuracy for fraud samples on synthetic financial datasets.It can quickly detect most fraud samples while keeping false positives within a reasonable range.The model designed in this paper enriches the research of model fusion in financial fraud detection.
Exploring the Application of Blockchain Technology in the Field of Electricity Marketing

In order to fully implement the strategic deployment of the State Grid Corporation of China to build a world-class energy Internet enterprise, it is imperative to accelerate the digital transformation of marketing services.Based on the ideas of optimizing the existing business process, protecting user data privacy and promoting data sharing, we designed the idea of data uplinking based on the scenarios of signing electronic contracts, collecting electricity bills from customers and tracing equipment quality in the power marketing scenario to effectively improve the security and sharing ability of the platform and promote the construction of the power marketing system with the characteristics of business integration and data sharing.Through the construction of the existing system, the data in the existing power marketing related business system can be collected, solidified and shared, and the automatic calculation of these large data flows can be realized through the construction of blockchain-based smart contracts, so as to support the company to respond to the decision.The data collection and processing system based on block chain can also optimize the existing storage resources of the business system and improve system performance.