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检索条件"任意字段=International Conference on Information Technology - Coding and Computing"

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A Healthcare Data Sharing Scheme Based on Homomorphic Encryption and Federated Metric Learning 5

A Healthcare Data Sharing Scheme Based on Homomorphic Encryp...

引用

5th international conference on Intelligent computing and Human-Computer Interaction, ICHCI 2024

作者： Zhang, Haoming Liu, Zhentao Wu, Lang Li, Han School of Applied Science Beijing Information Science & Technology University Beijing China

ISBN: (纸本)9798350368284

Medical data is highly sensitive, often leading to 'data silos' in sharing processes. To address this issue, this paper combines blockchain and federated metric learning technologies, and innovatively integrates them with homomorphic encryption technology to propose a privacy protection system suitable for application in medical data sharing scenarios. The system employs federated learning to train a global model across distributed client nodes without sharing raw data. Metric learning classifies clients as benign or malicious based on data similarity, only aggregating models from benign clients to improve efficiency and mitigate data distribution issues. Additionally, differential privacy and homomorphic encryption are used to further protect data privacy by preventing the original data from being reverse deduced and model parameter leakage during aggregation. Experimental results show that the system can achieve a prediction accuracy of 89.102564% under different data distributions, and its performance on medical datasets has been significantly improved compared to traditional federated learning. © 2024 IEEE.

关键词： Federated learning

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Improving Library Document Resource Management and Data Sharing Through Semantic Web technology 3

Improving Library Document Resource Management and Data Shar...

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3rd international conference on Pervasive computing and Social Networking, ICPCSN 2023

作者： Muruganantham, A. Velmurugan, R. Kumar, R. Bengaluru India

ISBN: (纸本)9798350322842

This research focuses on the limitations of the original association rule and presents a method for addressing these limitations by dividing the dataset into event sequences. The original association rule has a limited ability to identify references related to a keyword, only focusing on the closest ones, which can lead to incomplete and inaccurate results. The proposed method overcomes this limitation by categorizing different types of references based on the research subject, which enables the identification of relevant references that are not immediately adjacent. The reliability of different categories is calculated based on the event table, and candidate records undergo procedures such as aggregation and screening to eliminate less reliable records. The feasibility of this method is evaluated by comparing it with numerous association rule processes in the marketplace. The results show that the proposed method has a significant advantage over other algorithms, with a data correlation rate that remains stable at 80%. Moreover, this study emphasizes the importance of Linked Data technology in publishing and sharing data online. Linked Data provides a lightweight and incremental data transfer model, which makes it an ideal way to integrate resources into the information flow continuously. Libraries can use this technology to become part of the internet's information resources, thereby facilitating the addition and interoperability of further web resources. The development of Semantic Web technologies allows for easier communication between humans and computers, sharing information perception specifications that greatly facilitate communication between the two parties. © 2023 IEEE.

关键词： Blockchain

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'BeMyVoice' - A Communicative Platform to Assist Deaf Students 6

'BeMyVoice' - A Communicative Platform to Assist Deaf Studen...

引用

6th international conference on Advancements in computing, ICAC 2024

作者： Kawshalya, Mohottige Imedha Sewwandi Achini, Kiralawella Palliyaguruge Palliyaguru, Umeda Savishka, Gamage Ishini Buddhika, Jayamahamudalige Don Appuhamy, Sadun Chathuranga Suriyaa Kumari, Punam Kristhombuge Swarnakantha, N.H.P Ravi Supunya Sri Laka Institute of Information Technology Faculty of Computing Malabe Sri Lanka

ISBN: (纸本)9798331517878

Globalization and technology have greatly enhanced the quality of life for deaf students by addressing communication barriers, safety concerns, limited accessibility to sign language learning tools, and mobility difficulties. This research proposes a machine-based approach to tackle these challenges through an integrated app that leverages sign language recognition, vibration-based danger detection, interactive educational tools, and indoor navigation assistance. By focusing on the recognition of sign language gestures, detection of potential dangers via vibrations, engagement through gamified learning tools, and navigation within buildings using landmarks, the system aims to improve communication, safety, learning, and mobility for deaf students. The system utilizes advanced deep learning and machine learning models, reaching an accuracy of over $9 0 \%$ in sign language recognition, $9 5 \%$ for danger detection, and high user satisfaction for both educational tools and navigation assistance. Our findings indicate that such integrated technological solutions can significantly enhance the participation and quality of life of deaf students in both educational and social activities. © 2024 IEEE.

关键词： Students

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Joint Signature Authentication Scheme Based on Blockchain technology

Joint Signature Authentication Scheme Based on Blockchain Te...

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2024 international conference on Optical Communication and Optoelectronic technology, OCOT 2024

作者： Han, Chao Gao, Song Liu, Tingjian Xu, Jianchao Wen, Tao Shandong Sansec Information Technology Co. Ltd. Jinan250101 China Sansec Technology Co. Ltd. Beijing100102 China Inspur Software Co. Ltd. Jinan250101 China

ISBN: (纸本)9781510683266

Accompanied by the development of big data and cloud computing and other technologies, the traditional centralized authentication technology faces increasing security risks due to the existence of its trusted center. In order to solve the problems, blockchain technology enters the scope of research scholars. In this paper, we focus on the authentication and secure data transmission scheme of data sender to receiver via some other node in the absence of trusted center under the situation of three-party participation in the field of identity authentication. In this paper, we introduce the identity-based cryptosystem and design a three-party joint signature and authentication scheme based on the SM9 identification algorithm, combined with the decentralized, tamper-proof, publicly verifiable and other characteristics of blockchain technology. The scheme realizes the identity authentication and message integrity verification. The analysis shows that the scheme has security attributes such as decentralization and privacy protection, at the same time, we also demonstrate that the proposed scheme has the property of mitigating common network attacks. © 2024 SPIE.

关键词： Blockchain Receivers information security Network security Cryptography Design Data processing Computer security Data transmission Telecommunications

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Accurate Hardware Trojan Detection technology Based on Node Concealment Features 8

Accurate Hardware Trojan Detection Technology Based on Node ...

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8th IEEE international Test conference in Asia (ITC-Asia)

作者： Wang, Zhen Jiang, Dan Li, Jingru Zheng, Shuhang Shanghai Univ Elect Power Coll Comp Sci & Technol Shanghai 201306 Peoples R China

ISBN: (纸本)9798331540340;9798331540333

The globalization of the IC supply chain has increased the possibility for adversaries to insert hardware Trojans (HTs), which are always inserted into nodes with high concealment. Although several methods have been introduced to detect HTs, they do not specifically focus on node concealment and are not accurate enough. In this paper, 11 new features are proposed reflecting the node concealment, i.e, the controllable difficulty and observable difficulty of nodes, for machine-learning-based HT detection. The proposed features comprehensively consider the circuit structure information and signal propagation characteristics, and quantify the possibility of attacks. After combining the proposed features with existing ones for classification, the true positive rate (TPR) is 35 points higher than that without using the proposed features. Compared with the state-of-the-art works, our TPR and true negative rate (TNR) have increased by 15.6% and 2.1%, respectively, especially in large-scale circuits. It shows that our method has a great advantage in detection accuracy.

关键词： Hardware Trojan gate-level netlist HT concealment node rarity sample balance

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Interactive Simulation Tool for Spatiotemporal Data of Climate-related Fires over Borneo 11

Interactive Simulation Tool for Spatiotemporal Data of Clima...

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11th international conference on information and Communication technology, ICoICT 2023

作者： Muttaqien, Furqon H. Wirahman, Taufiq Shabrina, Ayu Latifah, Arnida L. Research and Innovation Agency Research Center for Computing National Bogor Indonesia School of Computing Telkom University Bandung Indonesia

ISBN: (纸本)9798350321982

Hazardous forest fires over Borneo in 2019 should be a concern that natural climate-related disasters have been increasing;they can be more frequent and extreme. Research about forest fire prediction and its impact has been abundant. However, there still needs to be more people's awareness of the hazard and risks. This study introduces an interactive simulation tool to help society and scientists from other fields understand better the risk of climate-related fire in Borneo. The interactive simulator of forest fire prediction is created as a web-based application using the Flask framework and Bokeh library in Python. As the first development, it visualizes the historical spatial and temporal forest and land fire data over Borneo, computed by machine learning methods, namely Random Forest, Decision Trees, and Support Vector Machine. The prediction results show that the three models similarly predict burned areas. Meanwhile, Random Forest predicts the carbon emission slightly better than other models, with 4.751 and 0.008 for MAE and NRMSE, respectively. It also gives interactive features that the user can play to estimate the fires, given climate and environmental conditions. © 2023 IEEE.

关键词： Forecasting

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Democratizing GDPR Compliance: AI-Driven Privacy Policy Interpretation 2024

Democratizing GDPR Compliance: AI-Driven Privacy Policy Inte...

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16th international conference on Contemporary computing, IC3 2024

作者： Mittal, Sangeeta Gupta, Saksham Bansal, Kritarth Aggarwal, Geetali Jaypee Institute of Information Technology India

ISBN: (纸本)9798400709722

With long privacy policies, users face the challenge of understanding them easily in order to ensure that their privacy rights are upheld. This paper presents an approach for democratizing GDPR compliance through AI-driven privacy policy interpretation. The methodology leverages advanced artificial intelligence techniques of Large Language Models (LLMs) for implementing effective comprehension of privacy policies. By extracting key information related to personally identifiable information (PII), the proposed solution empowers users to make informed decisions about their data privacy. The effectiveness of AI-driven privacy policy interpretation has been shown via various examples of automated summarization of lengthy and complex privacy policies as compliant/non-compliant to GDPR. Overall, it makes privacy policies more accessible, relevant, and actionable for users. © 2024 Copyright held by the owner/author(s).

关键词： Differential privacy

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Implementation of an Enhanced Data Integrity Verification Model in Cloud computing 4

Implementation of an Enhanced Data Integrity Verification Mo...

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4th IEEE international conference on Electrical, Computer, and Energy Technologies, ICECET 2024

作者： Khumalo, Nomsa L. Mathonsi, Topside E. Ojo, Sunday O. Tshwane University of Technology Department of Information Technology Pretoria South Africa Durban University of Technology Department of Information Technology Durban South Africa

ISBN: (纸本)9798350395914

Cloud computing has revolutionized access to computing resources by offering internet-based utility services, eliminating the need for significant upfront investments in hardware and software infrastructure. However, ensuring data integrity (DI) within this paradigm presents multifaceted challenges. These challenges encompass issues of complexity, security, privacy, control limitations, human error, and financial constraints. Existing DI solutions often fall short of effectively verifying data, mitigating replay attacks, and managing computational overhead. This deficiency leads to an increasing need for third-party verifiers with access to cloud infrastructure, raising concerns about data security and privacy. This paper proposes the Cryptographic Accumulator Provable Data Possession with Merkle Hash Tree (CAPDP-MHT) scheme as a robust solution to address the limitations of current DI approaches. Through extensive simulations and rigorous evaluations utilizing MATLAB, CAPDP-MHT demonstrates significantly enhanced performance compared to both Provable Data Possession (PDP) and Rivest-Shamir-Adleman (RSA) algorithms across various scenarios. Specifically, CAPDP-MHT achieves an average data verification success rate of 25%, a substantial improvement over PDP and RSA's rates of 10% and 5%, respectively. Additionally, it outperforms existing algorithms in detecting replay attacks, accomplishing this within 30 seconds compared to PDP's 45 seconds and RSA's 70 seconds. Furthermore, CAPDP-MHT demonstrates superior computational efficiency, incurring an overhead of approximately 27 seconds, significantly lower than PDP's 45 seconds and RSA's 60 seconds. These results establish CAPDP-MHT as a highly reliable and efficient solution for data integrity verification in cloud environments. It surpasses traditional PDP and RSA-based schemes in both reliability and computational efficiency, offering a promising avenue for addressing the challenges of data integrity in the cloud com

关键词： Cloud computing Cryptographic Accumulator Provable Data Possession-Merkle Hash Tree algorithm Data Integrity Data Verification

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Multiresource allocation in dynamic MEC systems: a continual learning-based approach 3

Multiresource allocation in dynamic MEC systems: a continual...

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3rd international conference on Electronic information Engineering, Big Data, and Computer technology, EIBDCT 2024

作者： Zhan, Shutao Mao, Jin Chu, Zhipeng Xiong, Ke Fan, Pingyi Letaief, Khaled B. Eng. Res. Center of Network Management Technology for High Speed Railway of Ministry of Education School of Computer and Information Technology Beijing Jiaotong University Beijing100044 China National Engineering Research Center of Advanced Network Technologies Beijing Jiaotong University Beijing100044 China Collaborative Innovation Center of Railway Traffic Safety Beijing Jiaotong University Beijing100044 China Department of Electronic Engineering Tsinghua University Beijing100084 China Department of Electrical and Computer Engineering Hong Kong University of Science and Technology Hong Kong Hong Kong

ISBN: (纸本)9781510680449

Recently, mobile edge computing (MEC) has been considered as a promising solution to address the challenges arising from the growing computationally intensive applications and limited computation capability of mobile devices. Thus, the resource allocation is crucial for ensuring the system performance of MEC. Recent deep learning-based resource allocation (DLRA) methods achieve preferable performance in real-time. However, in practical scenarios, the number of users often changes, which leads to a decrease in the performance of DLRA methods. Thus, once the number of users changes, the traditional DLRA methods need to retrain their neural networks, which consumes a lot of computing resources. To address this issue, this paper proposes a continual learning-based resource allocation (CLRA) method to jointly optimize multiple resource including offloading decision, power control, time slot assignment and computation resource distribution in MEC system. Our CLRA method is able to avoid forgetting previous knowledge when the number of users in the MEC system changes by selecting a small number of the most representative samples from the past and relearning. Experimental results show that, our proposed CLRA method achieves a better performance than the traditional DLRA method in terms of the higher quality of service's (QoS's) satisfaction rate and the less energy consumption. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Resource allocation

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Cooperative Completing Tasks of Charging WRSNs with Multiple MUVs and Laser-charged UAVs 21

Cooperative Completing Tasks of Charging WRSNs with Multiple...

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21st IEEE international Symposium on Parallel and Distributed Processing with Applications, 13th IEEE international conference on Big Data and Cloud computing, 16th IEEE international conference on Social computing and Networking and 13th international conference on Sustainable computing and Communications, ISPA/BDCloud/SocialCom/SustainCom 2023

作者： Luo, Chuanwen Liu, Ning Chen, Ting Cao, Jia Hong, Yi Chen, Zhibo Li, Deying Beijing Forestry University Information Science and Technology Beijing China University of Electronic Science and Technology of China Chengdu China Renmin University of China School of Information Beijing China

ISBN: (纸本)9798350329223

With the rapid development of unmanned aerial vehicles (UAVs), they can not only carry communication equipment for intercepting and interfering with signals to protect communication security, but also carry energy transmission devices to transfer energy to wireless sensor networks and enhance network lifespan. This paper investigates the network framework of multiple UAVs-based wireless rechargeable sensor network (WRSN) assisted by multiple mobile unmanned vehicles (MUVs). On the basis of this network, we cooperatively investigate the trajectory optimization of multi-UAVs and multi-MUVs for charging WRSN (TOUM) problem, whose goal aims at designing the optimal travel plan of UAVs and MUVs cooperatively to charge WRSN such that the remaining energy of each sensor in WRSN is greater than or equal to the threshold and the maximum time consumption of UAVs is minimized. The TOUM problem is proved NP-hard. To solve the TOUM problem, we first investigate the MUTSP problem to balance the charging tasks assigned to each UAV. Then, according to the MUTSP problem, we propose the TOUM algorithm(TOUMA) to design the detailed travel plan of UAVs and MUVs. We have validated the effectiveness of our algorithm through extensive simulation experiments. The experimental results demonstrate that the TOUMA algorithm outperforms both the solar charging method and the base station charging method in terms of time efficiency. Furthermore, under various parameter settings, the ratio of the TOUMA algorithm consistently remains below 1.56. © 2023 IEEE.

关键词： Wireless sensor networks

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