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检索条件"任意字段=Proceedings of the 5th ACM Conference on Data and Application Security and Privacy"

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SELMAnalyzer: An APP privacy Leakage Analysis Method Based on Program Execution Logic 5

SELMAnalyzer: An APP Privacy Leakage Analysis Method Based o...

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5th International conference on Advances in Electrical Engineering and Computer applications, AEECA 2024

作者： Li, Jingwei Liu, Tao Zhang, Ruoding Zhang, Yan Song, Xiaoyi Shang, Chong University of Chinese Academy of Sciences Institute of Information Engineering Chinese Academy of Sciences School of Cyberspace Security Beijing China MIIT China Academy of Information and Communications Technology Key Laboratory of Mobile Application Innovation and Governance Technology Beijing China University of Chinese Academy of Sciences China Telecom Co. Ltd. School of Cyberspace Security Beijing China Chinese Academy of Sciences Institute of Information Engineering Beijing China

ISBN: (纸本)9798350355253

Mobile phones have become an indispensable part of people's daily lives, but many mobile applications continue to obtain and use people's private data through malicious behaviors hidden behind normal functions. Existing work provides many methods to detect malicious applications' behaviors. However, the analysis and detection technology for the logic triggering process and implementation methods of potential malicious behaviors still need further improvement. this paper proposes an APP privacy leakage analysis method called SELMAnalyzer. this method builds a software execution logic analysis model SELM(Software Execution Logical Model) based on a graph structure to model the dynamic execution logic and implementation methods of Android applications and mine the privacy leakage problems of applications hidden behind normal UI function interfaces or normal components. At the same time, the method proposed in this paper is verified using a real Android application dataset with an accuracy rate of 89%. Compared with similar methods, it can intuitively display the complete calling process of privacy theft behavior from the UI interface to the underlying functional functions and effectively detect hidden malicious behaviors. © 2024 IEEE.

关键词： Information leakage

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Enhancing Cyber-Physical Systems security: A Review of Deep Learning and Blockchain Integration 5

Enhancing Cyber-Physical Systems Security: A Review of Deep ...

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5th International conference on Image Processing and Capsule Networks, ICIPCN 2024

作者： Selvi, K. Dilip, Golda SRM Institute of Science and Technology Faculty of Engineering and Technology Department of Computer Science and Engineering Vadapalani Campus Chennai India

ISBN: (纸本)9798350367171

Cyber-Physical Systems (CPS) combine physical and computational elements to produce intelligent systems communicating with their surroundings. By integrating digital and physical processes, CPS provides increased functionality in various industries, including industry, transportation, and healthcare. However, there are security, data integrity, and privacy issues brought on by the extensive integration of CPS across several domains. therefore, addressing these issues is significant for an effective and reliable CPS model. this study presents a comprehensive review exploring the synergistic relationship between two cutting-edge technologies, Deep Learning (DL) and Blockchain, deployed to resolve these issues in CPS. this study explores the efficiency of leveraging DL and blockchain to enhance the reliability and effectiveness of the CPS models. Also, this study examines the challenges and limitations faced by those DL and blockchain approaches during their implementation across different CPS domains. this comprehensive review provides promising directions for future research in this dynamic and interdisciplinary field for mitigating the challenges in CPS models. It also aids researchers, practitioners, and policymakers by providing a deeper understanding of the possible effects, difficulties, and opportunities related to utilizing DL and Blockchain technologies to improve the security and functionality of CPS. © 2024 IEEE.

关键词： Blockchain technologies Cyber-Physical Systems Deep Learning Internet of things

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Research and analysis of the security risk management strategy of big data technology in the financial industry 5

Research and analysis of the security risk management strate...

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5th International conference on Big data Engineering, BDE 2023

作者： Ji, Wenjun Maanshan Vocational and Technical College Anhui province Maanshan243031 China

ISBN: (纸本)9798400708695

With the continuous deepening of financial business informationization, the rapid spread of all kinds of financial data, promoting the financial field to enter the era of big data, and the structural transformation and dynamic development of the financial industry face new *** the context of big data, the study of financial information security prevention and guarantee system will be conducive to guarantee the storage and application of users' *** paper first analyzes the application and characteristics of big data technology in the financial industry, and then deeply analyzes the risks of the application of big data in the financial industry from the three dimensions of technology, management and compliance, and puts forward the corresponding security risk control strategy. © 2023 acm.

关键词： Big data

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privacy-Preserving Human Activity Recognition in Smart Homes using Deep Learning and Edge Computing for Real-Time Processing 5

Privacy-Preserving Human Activity Recognition in Smart Homes...

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5th International conference on Sustainable Communication Networks and application, ICSCNA 2024

作者： Mariappan, K. Gopal, Baskar Parthasarathy, J. Sreekanth, G.R. Nanmaran, R. Jegajothi, B. SRM Institute of Science and Technology Department of Computer Science and Applications Chennai India College of Engineering University of Technology & Applied Science Nizwa Oman Computer Science & Engineering Jayalakshmi Institute Of Technology Dharmapuri India Information Technology Nandha Engineering College Erode52 India Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Department of Electronics and Communication Engineering Chennai India SRS Tech Solutions Chennai India

ISBN: (纸本)9798331530013

the rapid advancement of smart home technologies necessitates efficient human activity recognition (HAR) systems while ensuring user privacy. this research presents a novel architecture that integrates deep learning and edge computing for real-time HAR, emphasizing privacy protection. By employing differential privacy methods and federated learning, the approach minimizes personal data exposure risks. Using the UCI HAR dataset, the model achieves an accuracy of 96.50%, with precision, recall, and Fl-score metrics of 95.75%, 96.20%, and 95.97%, respectively. the results indicate high accuracy and adaptability to varying smart home environments, while edge computing ensures minimal latency. this work highlights the importance of balancing performance and privacy in HAR systems, paving the way for secure smart home applications. Additionally, it points to the potential of deep learning in medical diagnostics, suggesting future research could enhance diagnostic capabilities across various medical imaging modalities, including CT scans and MRIs, to improve healthcare outcomes. © 2024 IEEE.

关键词： Smart homes

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Blockchain Enabled SDN Framework for security Management in 5G applications 23

Blockchain Enabled SDN Framework for Security Management in ...

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24th International conference on Distributed Computing and Networking (ICDCN)

作者： Das, Debashis Banerjee, Sourav Dasgupta, Kousik Chatterjee, Pushpita Ghosh, Uttam Biswas, Utpal Univ Kalyani Comp Sci & Engn Kalyani W Bengal India Kalyani Govt Engn Coll Comp Sci & Engn Kalyani W Bengal India Howard Univ Elect Engn & Comp Sci Washington DC 20059 USA Meharry Med Coll Dept CS & DS Nashville TN 37208 USA

ISBN: (纸本)9781450397964

Fifth-generation (5G) wireless networks are now operational to deploy all over the world. the technology of 5G's objective is to link heterogeneous machines and devices with significant improvements high quality of service (QoS), internet bandwidth, and improved system throughput to enable several upright applications. Despite all these benefits that 5G will provide, still, significant issues need to be resolved, such as decentralization, transparency, and risks associated with data interoperability, network privacy, and security vulnerabilities. Modern networks link an enormous number of devices to the Internet, and in this complicated situation, the use of BC and SDN has been effectively advocated to assure security, privacy, and secrecy. this study offers a blockchain-enabled SDN framework for securing transactions that makes use of Software Defined Network (SDN) and Network Function Virtualization (NFV) to overcome these issues. the proposed framework can address the man-in-the-middle attack between control and data plane in SDN networks. A controller authentication scheme is provided using smart contracts. Smart contracts automatically authenticate the SDN controller to increase the efficiency of controller verification. the communicated data can also be authenticated using smart contracts. the proposed framework can enhance network transparency, data security, and user privacy. Each SDN controller can access verifiable data using the proposed framework.

关键词： blockchain distributed SDN 5G network blockchain-enabled SDN wireless communication smart contract

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Achieving efficient and secure keyword attribute community search on cloud servers 5

Achieving efficient and secure keyword attribute community s...

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5th International conference on Computer Communication and Network security, CCNS 2024

作者： Zhong, Ziyang Chang, Pan Cai, Min Software Engineering Institute East China Normal University Shanghai200062 China Shanghai New York University Working Group East China Normal University Shanghai200062 China

ISBN: (纸本)9781510681842

Community search is a technique used to identify and retrieve groups of nodes with specific attributes or associations by analyzing the connections between nodes in a network or graph structure. Existing researches mainly focus on single secure search requirements, making it difficult to support complex graph searches. therefore, this paper proposes a secure search scheme that simultaneously satisfies k-core and keyword attribute similarity requirements. Specifically, to enhance search efficiency, we utilize an improved core decomposition tree to index community graph containing keyword attributes. Additionally, based on the triangle inequality, we design an efficient pruning strategy. To enhance security, Paillier homomorphic encryption and matrix encryption are adopted, presenting a secure and efficient attribute community search scheme that protects the privacy of outsourced data, query requests, and query results. security analysis and performance evaluation demonstrate that our proposed solution is both secure and efficient. © 2024 SPIE.

关键词： Matrices Computer security Clouds data privacy Network security Social networks

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A Review of Cyber security Challenges and Mitigation Strategies in Industry 4.0 Technologies 5

A Review of Cyber Security Challenges and Mitigation Strateg...

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5th IEEE International conference on Advances in Computing, Communication Control and Networking, ICAC3N 2023

作者： Kumar, Mayank Gupta, Himanshu Aiit Amity University Noida India

ISBN: (纸本)9798350330861

the 4th Industrial Revolution, also known as or the Industry 4.0, has been characterized by the emergence of revolutionary technologies like robotics, computer vision, big data the analysis, and the Internet of things, or IoT for short, directly into the operations of industries. As these technologies become increasingly widespread, they also introduce new cybersecurity risks that need to be addressed. this paper provides a comprehensive review of the current literature on cyber security challenges and mitigation strategies in Industry 4.0. the research approach involved a systematic literature review of academic journals, conference proceedings, and relevant reports and studies. the review's findings emphasize the most significant cyber security concerns impacting the Industry 4.0 movement, including data privacy and security, network security, and system integrity. the paper also identifies and evaluates the strategies used to mitigate these challenges, including encryption, access control, and network segmentation. the analysis section interprets the findings, draws meaningful conclusions and offers valuable recommendations for future research and practical applications. the research paper delivers an input to the topic of cyber security within Industry 4.0 by offering an in-depth review regarding the domain's present circumstances and presenting prospective directions for additional research and advancement. © 2023 IEEE.

关键词： Cryptography

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privacy Protection Scheme for Epidemiological Investigation Based on Blockchain Technology 23

Privacy Protection Scheme for Epidemiological Investigation ...

引用

5th Blockchain and Internet of things conference (BIOTC)

作者： Han, Ya Gao, Jianbo Guan, Zhi Chen, Zhong Ren, Lifeng Peking Univ Sch Comp Sci Beijing Peoples R China Peking Univ Chongqing Res Inst Big Data Chongqing Peoples R China Peking Univ Natl Engn Res Ctr Software Engn Beijing Peoples R China

ISBN: (纸本)9798400708213

Since Bitcoin was invented in 2008, the blockchain technology has been growing rapidly. A blockchain is a growing public ledger called blocks which are interconnected with a chain by utilizing cryptography. Utilizing blockchain, we can share information over the system safely, where everyone can see but can't do any alteration. Because of this feature of blockchain system, everyone can fetch or reason out the peer nodes' data or even private data. To protect the privacy and data security of the blockchain system, a common practice is to use privacy computing technology to guarantee the privacy protection required. At present, the global pandemic of the COVID-19 is still going on, and it will coexist with humanity for a long time. How to screen the flow regulation quickly and make it traceable is an important research topic. this paper proposed one epidemiological data privacy protection scheme based on blockchain platform combined with secure multi-party computation based on protocols and federated learning based on modern cryptography. In this paper, we use federated learning technology to realize the construction of a federated learning model involving multiple institutions and departments in the process of epidemiological investigation to avoid the risk of user privacy leakage during epidemiological investigation. the blockchain technology is used to realize the multi-institution federated learning model On-chain operation, with the introducing of the global model competition mechanism, to realize the optimal federated learning model On-chain, and ensure the optimization of learning goals. Meanwhile, the secret sharing technology is used to realize the sharing of the validation dataset, which avoids the optimization problem of federated learning model caused by the institution knowing the global validation dataset.

关键词： Blockchain Epidemiological investigation Federated learning Secret sharing

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Proposition Development Study- Intervention of AI in the Education Sector of UAE 5

Proposition Development Study- Intervention of AI in the Edu...

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5th International conference on Information Management and Machine Intelligence, ICIMMI 2023

作者： Ramakrishnan, Swamynathan Bishnoi, Malini Mittal Harish, V. Jijitha, S. Amity Business School Amity University Dubai United Arab Emirates PSGIM PSG College of Technology TN Coimbatore India Department of Computer Applications Bharathiar University Coimbatore India

ISBN: (纸本)9798400709418

Artificial intelligence (AI) has been revolutionizing various fields, including education sector, therefore it is essential to learn about the potentials and challenges of the AI impact on learning and education process. As the UAE's commitment to become a leader in innovation and education, it is vital to study about the factors that impact the successful implementation of AI in education sector in the UAE. the study acknowledges the transformative potential of AI in education sector including personalized learning experiences, streamlined administrative tasks, and enhanced assessment processes. the paper examines the main elements that influence the application of AI in the UAE's education sector, drawing on previously published research. It investigates the technological foundation necessary to allow AI interventions, the accessibility and availability of data, the significance of data privacy and security, and the moral issues raised by the application of AI algorithms. the study analyses the existing literature on the intervention of AI in education sector in UAE and based on it the propositions are developed. the propositions developed in this study can serve as a foundation for further research, discussions, and decision-making related to the intervention of AI in the UAE's education sector. © 2023 acm.

关键词： data privacy

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Blockchain Technology in HR: Enhancing Transparency and security in Employee data Management 5

Blockchain Technology in HR: Enhancing Transparency and Secu...

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5th International conference on Sustainable Communication Networks and application, ICSCNA 2024

作者： Paranthaman, Prabakaran Kumaran, V. Senthil Vijayalakshmi, V. Rimo, Shibe St. Joseph's Institute of Technology Department of Management Studies Tamil Nadu Chennai India Saveetha College of Liberal Arts and Sciences Saveetha Institute of Technical and Medical Sciences Department of Business Administration Tamil Nadu Chennai India

ISBN: (纸本)9798331530013

Traditional Human Resources (HR) systems, which are dependent on centralized databases, have problems with data manipulation, illegal access, and inefficiencies resulting from numerous middlemen and manual processes. these systems are susceptible to data breaches because these frequently experience single points of failure. the research proposes a blockchain-based HR system that uses smart contracts and an immutable, decentralized ledger to manage HR processes like performance reviews and payroll. the system aims to address these issues. the comparative analysis's results demonstrate that the proposed system lowers data breaches to two incidents from 15 and 8 in the existing systems, shortens payroll processing time from 24 to 8 hours, and saves administrative costs to 4,000 from 10,000 and 6,000 in the existing systems. if, the proposed approach performs slightly lower than the best-performing existing systems in terms of GDPR compliance and transparency, but it still delivers a lot of security, efficiency, and cost-effectiveness gains. © 2024 IEEE.

关键词： Efficiency

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