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Copyright and License Agreement History Management Framework for Outsourced Software

2023 IEEE International Conference on Metaverse Computing, Networking and Applications, MetaCom 2023

作者： Lee, Taeyang Lee, Jinsue Woo, Seungchan Lee, Jong-Hyouk Sejong University Dept. of Computer and Information Security and Convergence Engineering for Intelligent Drone Seoul Korea Republic of Sejong University Dept. of Computer and Information Security Seoul Korea Republic of

ISBN: (纸本)9798350333336

The practice of transitioning software development tasks to outsourcing has become increasingly prevalent. However, this approach presents challenges in systematically managing the historical records of copyright and license agreements associated with outsourced software. To address potential conflicts between clients and vendors in outsourced software transactions, this paper introduces a framework for effectively managing the history of copyright and license agreements pertaining to outsourced software. © 2023 IEEE.

关键词： Smart contract

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Decentralized Identifier System for Software Copyright Transfer and License Management

Decentralized Identifier System for Software Copyright Trans...

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2023 IEEE International Conference on Metaverse Computing, Networking and Applications, MetaCom 2023

作者： Woo, Seungchan Lee, Taeyang Lee, Jong-Hyouk Sejong University Dept. of Computer and Information Security Seoul Korea Republic of Sejong University Dept. of Computer and Information Security and Convergence Engineering for Intelligent Drone Seoul Korea Republic of

ISBN: (纸本)9798350333336

This paper presents a distributed identifier (DID) system that offers transparent and traceable outsourcing support platform for software development. The proposed system is designed to ensure the privacy of contracting parties during the copyright transfer and license contract process, thereby creating a fair and transparent outsourcing market. By leveraging a DID system, our approach ensures that no single entity controls the information, which increases the overall security and reliability of the system. Also, it reduces corporate losses due to noncompliance with copyright and license contracts. © 2023 IEEE.

关键词： Outsourcing

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Transfer Learning-Based Robust Insider Threat Detection 23

Transfer Learning-Based Robust Insider Threat Detection

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23rd IEEE International Conference on Trust, security and Privacy in Computing and Communications, TrustCom 2024

作者： Kim, Yujun Kim, Deok-Han Kim, Young-Gab Sejong University Dept. of Computer and Information Security Convergence Engineering for Intelligent Drone Seoul South Korea

A malicious insider's threats who has access to the organization's systems and is familiar with security policies are difficult to detect and can cause significant financial damage. A reconstruction-based anomaly detection method leveraging deep learning is one method for detecting insider threats. The method is employed to solve a data imbalance problem caused by the scarcity of abnormal data in real environments. The method trains a deep learning model to reconstruct normal data received from all users. After training, the model reconstructs normal data more accurately than abnormal data, and the reconstruction-based anomaly detection method can detect anomalies based on the reconstruction difference between normal and abnormal data. However, existing reconstruction-based anomaly detection methods train on all users' normal data using the same network parameters. Consequently, if a behavior is normal for one user but abnormal for another, the reconstruction model learns this behavior as normal because the reconstruction model trains only on normal behaviors. Since normal behaviors differ for each user depending on their position, role, and other factors within the organization, it is necessary to develop methods for detecting abnormal behaviors specific to each user. To address this problem, we propose a transfer learning-based insider threat detection method. The proposed method consists of 1) a pre-trained encoder that outputs latent representations of normal data for all users and 2) user-specific decoders assigned to each user, which are trained on the corresponding user's normal data to reconstruct their normal data. We evaluate the proposed method's detection rate (DR) and area under the curve (AUC) on the CERT dataset and compare it with a deep learning model trained on normal data from all users. The experimental results show that the proposed method achieves higher DR and AUC than the deep learning model. These results indicate that the proposed method en

关键词： Anomaly detection Deep Learning Insider threat Transfer Learning

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A Method for Quantitative Object De-Identification Analysis of Anonymized Video 23

A Method for Quantitative Object De-Identification Analysis ...

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23rd IEEE International Conference on Trust, security and Privacy in Computing and Communications, TrustCom 2024

作者： Kim, Deok-Han Kim, Yujun Kim, Young-Gab Sejong University Dept. of Computer and Information Security Convergence Engineering for Intelligent Drone Seoul South Korea

The rise in video content has amplified the risk of information leakage, prompting the development of various anonymization techniques. These techniques include traditional methods such as pixelation, blurring, and masking, as well as more advanced approaches like video encryption, which involves encrypting parameters during video encoding, and techniques that subtly alter facial features to prevent identification. However, assessing the effectiveness of these anonymization techniques remains challenging. Common metrics such as the structural similarity index (SSIM) and peak signal-to-noise ratio (PSNR), often used for object anonymization in videos, primarily assess image quality and lack accuracy for security evaluation. Furthermore, subjective human evaluations fail to provide the consistent, quantitative data necessary for cross-study comparisons. Given that a single identifiable frame in a video can compromise overall security, this study introduces a quantitative method for evaluating the de-identification rate in regions of interest (ROI) within videos. The proposed approach calculates an object de-identification rate (ODR) by combining SSIM and edge detection ratio (EDR) using a harmonic mean and a power mean. Our proposed method enhances the precision and reliability for security of anonymized video. © 2024 IEEE.

关键词： Object de-identification rate assessment Video de-identification quality assessment Video encryption Video surveillance

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A Privacy-Aware Provably Secure Smart Card Authentication Protocol Based on Physically Unclonable Functions

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IEEE Transactions on Dependable and Secure Computing 2024年第4期21卷 2766-2778页

作者： Fan, Chun-I Karati, Arijit Wu, Shou-Li National Sun Yat-sen University Department of Computer Science and Engineering Information Security Research Center The Intelligent Electronic Commerce Research Center Kaohsiung804 Taiwan National Sun Yat-sen University Department of Computer Science and Engineering Kaohsiung804 Taiwan

For many industrial applications, the smart card is a necessary safety component in user authentication. Smart cards provided to the users are used in open and public places, making them susceptible to physical and cloning attacks. Thus, the opponent can break the authentication process without the smart card if the information is exposed. In addition, many existing authentication systems employ challenge-response pairs (CRPs) to identify users by creating large numbers of data on the server and spending much time looking for and comparing responses. To address these concerns, we propose a lightweight privacy-preserving authentication protocol in which the physically unclonable function is considered a necessary tool. The suggested technique avoids creating a significant number of CRPs on the server to identify users uniquely. Under formal security models, the proposed protocol is resistant to user impersonation attacks and session key disclosure attacks and achieves robust mutual authentication. Nonetheless, it is immune to other essential security vulnerabilities. Empirical performance analysis demonstrates its viability in comparison to prior works. © 2023 IEEE.

关键词： Authentication

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Provably Secure Efficient Key-Exchange Protocol for intelligent Supply Line Surveillance in Smart Grids

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IEEE Internet of Things Journal 2025年第12期12卷 21784-21792页

作者： Ayub, Muhammad Faizan Li, Xiong Mahmood, Khalid Alenazi, Mohammed J. F. Das, Ashok Kumar Wang, Guijuan University of Electronic Science and Technology of China School of Computer Science and Engineering Chengdu611731 China National Yunlin University of Science and Technology Graduate School of Intelligent Data Science Douliu64002 Taiwan King Saud University College of Computer and Information Sciences Department of Computer Engineering Riyadh12311 Saudi Arabia International Institute of Information Technology Hyderabad Center for Security Theory and Algorithmic Research Hyderabad500032 India Korea University College of Informatics Department of Computer Science and Engineering Seoul02841 Korea Republic of Key Laboratory of Computing Power Network and Information Security Shandong Provincial Key Laboratory of Industrial Network and Information System Security Shandong Fundamental Research Center for Computer Science Ministry of Education Shandong Computer Science Center Jinan250353 China

intelligent supply line surveillance is critical for modern smart grids (SGs). Smart sensors and gateway nodes are strategically deployed along supply lines to achieve intelligent surveillance. They collect data continuously and transmit it to the control centre in real-time. It enables real-time monitoring, fault detection, and efficient energy management across distribution networks. This advanced surveillance system ensures continuous monitoring of supply lines, detecting anomalies, and optimizing operations to maintain the stability and reliability of the SG. However, the reliance of all participating nodes on public communication channels to transmit supply line surveillance data exposes these systems to critical cyber attacks. These cyber attacks include impersonation, physical tampering, ephemeral secret leakage (ESL), and desynchronization attacks. To address these issues, existing key-exchange protocols often fail to ensure robust security while imposing high computation and communication overheads, limiting their practicality for resource-constrained environments. Therefore, we propose a secure and efficient key exchange and tamper-resistant authentication protocol using elliptic curve cryptography (ECC) and physical unclonable functions (PUFs). The PUF mechanism provides robust resistance against physical tampering and cloning attacks, ensuring enhanced physical security for supply line devices. We validate the security robustness of the devised protocol using the random or real (ROR) model. Furthermore, informal security analysis demonstrates the protocol’s robustness in rigorously resisting various attacks, including physical tampering, impersonation, ESL and desynchronization. Moreover, we determine the performance evaluation that reveals the protocol’s superior efficiency compared to competing protocols, achieving significant reductions of 28.64% in computation overhead and 9.96% in communication overhead. © 2014 IEEE.

关键词： Authentication Protocol

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Decentralized identifier based illegal digital content distribution tracking system using the format-preserving encryption algorithm

Decentralized identifier based illegal digital content distr...

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作者： Kwon, Soonhong Park, Jaehyoung Lee, Taeyang Oh, SungHeun Lee, Jong-Hyouk Department of Computer and Information Security & Convergence Engineering for Intelligent Drone Sejong University Seoul Korea Republic of Protocol Engineering Lab. Sejong University Seoul Korea Republic of Technical Research Center DigiCAP Seoul Korea Republic of

The coronavirus pandemic, which first began in December 2019, has completely changed our daily lives. In particular, daily online digital content consumption over the world has soared since the start of the coronavirus pandemic. For preventing illegal digital content distribution, various technologies have been applied, but current copyright protection technologies are still lacking to provide secure digital content distribution while preserving privacy. In this article, we introduce a new digital content distribution system, which utilizes blockchain-based decentralized identifier and format-preserving encryption to enable user privacy preserved digital content tracking. We present the system architecture with detailed message flows of the proposal and provide its analysis result in terms of security and overhead. © 2022 John Wiley & Sons Ltd.

关键词： Coronavirus

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Trusted and Privacy-Preserving Billing System for Smart Grids

Trusted and Privacy-Preserving Billing System for Smart Grid...

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International Conference on Big Data and Smart Computing (BIGCOMP)

作者： Kayumov Abduaziz Shincheol Lee Ji Sun Shin Department of Computer and Information Security and Convergence Engineering for Intelligent Drone Sejong University Seoul South Korea Department of Computer and Information Security Sejong University Seoul South Korea

ISBN: (数字)9798331529024

ISBN: (纸本)9798331529031

With the advent of smart meters in recent years, privacy has become one of the biggest concerns in smart grids. While privacy is achieved by designing smart grid services while maintaining the anonymous participation of consumers, several technical issues must be solved by electricity companies, such as confirmation of payments or assurance of consumption data integrity and quality. In this paper, we propose a new system model for data aggregation in smart grid environments that balances the needs of consumers and electricity companies. To decentralize and achieve transparent data processing, we apply a permissioned blockchain network and smart contracts. To support consumer privacy, we propose a privacy-preserving smart contract that runs on a trusted execution environment. Payments are processed and confirmed at the end of a billing period by the smart contract to enforce data consistency and integrity. We implement our smart contract design for Hyperledger Fabric, a permissioned blockchain network, and analyze its privacy, data, and blockchain benefits.

关键词： Privacy Data privacy Electricity Data integrity Smart contracts Companies Smart meters Smart grids Blockchains Reliability

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Research on Metaverse security and Forensics

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computers, Materials & Continua 2023年第10期77卷 799-825页

作者： Guangjun Liang Jianfang Xin Qun Wang Xueli Ni Xiangmin Guo Pu Chen Department of Computer Information and Cyber Security Jiangsu Police InstituteNanjingChina Engineering Research Center of Electronic Data Forensics Analysis NanjingChina Key Laboratory of Digital Forensics Department of Public Security of Jiangsu ProvinceNanjingChina School of Intelligent Engineering Nanjing Institute of Railway TechnologyNanjingChina

As a subversive concept,the metaverse has recently attracted widespread attention around the world and has set off a wave of enthusiasm in academic,industrial,and investment ***,while the metaverse brings unprecedented opportunities for transformation to human society,it also contains related *** is a digital living space with information infrastructure,interoperability system,content production system,and value settlement system as the underlying structure in which the inner core is to connect real residents through applications and *** social incentives and governance rules,the metaverse reflects the digital migration of human *** article will conduct an in-depth analysis of the metaverse from the perspective of electronic data ***,from the perspective of Internet development,the background and development process of the metaverse is *** systematically elaborating on the concept and connotation of the metaverse,this paper summarizes the different views of current practitioners,experts,and scholars on the ***,from the perspective of metaverse security,the social risk and crime risks of the metaverse are *** the importance of metaverse forensics is ***,from the perspective of blockchain,smart wearable devices,and virtual reality devices,the objects and characteristics of metaverse forensics have been studied in *** smart wearable devices as an example,this paper gives the relevant experimental process of smart bracelet ***,many challenges faced by metaverse forensics are summarized by us which provide readers with some exploratory guidance.

关键词： Metaverse forensics blockchain smart wear virtual reality

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Holographic Multi-Channel QR Code based Copyright Distribution Management System

Holographic Multi-Channel QR Code based Copyright Distributi...

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2023 IEEE International Conference on Metaverse Computing, Networking and Applications, MetaCom 2023

作者： Kwon, Soonhong Son, Wooyoung Lee, Jong-Hyouk Sejong University Dept. of Computer and Information Security and Convergence Engineering for Intelligent Drone Seoul Korea Republic of Sejong University Protocol Engineering Lab. Seoul Korea Republic of

ISBN: (纸本)9798350333336

In this paper, we address the growing challenges arising from the rapid expansion of the global digital content market, fueled by COVID-19-induced digital transformation and increased reliance on online streaming services. While this trend has many positive implications, it has also led to persistent concerns surrounding copyright infringement and unfair distribution of copyright fees, negatively impacting copyright holders. To tackle these issues, we propose a new copyright distribution management system utilizing holographic multi-channel QR codes, which aims to safeguard the rights of copyright holders and ensure a fair distribution of royalties. © 2023 IEEE.

关键词： Copyrights

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