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Generative Federated Learning with Small and Large Models In Consumer Electronics for Privacy preserving Data Fusion in Healthcare Internet of Things

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IEEE Transactions on Consumer Electronics 2025年

作者： Ghazal, Taher M. Islam, Shayla Hasan, Mohammad Kamrul Abu-Shareha, Ahmad A. Mokhtar, Umi A. Khan, M. Attique Baili, Jamel Saeed, Ali Q. Bhattt, Mohammed Wasim Ahmad, Munir Al-Ahliyya Amman University Center for Cyber Security Faculty of Information Science and Technology Universiti Kebangsaan Malaysia (UKM) Department of Networks and Cybersecurity Hourani Center for Applied Scientific Research Amman Jordan UCSI University Institute of Computer Science and Digital Innovation Kuala Lumpur 56000 Malaysia Universiti Kebangsaan Malaysia (UKM) Center for Cyber Security Faculty of Information Science and Technology Malaysia Al-Ahliyya Amman University Hourani Center for Applied Scientific Research Department of Data Science and Artificial Intelligence Amman Jordan Prince Mohammad bin Fahd University Saudi Arabia King Khalid University College of Computer Science Department of Computer Engineering Abha 61413 Saudi Arabia Northern Technical University Computer Center Ninevah Iraq Korea University College of Informatics Seoul 02841 South Korea

Healthcare Internet of Things (HIoT) requires large-scale privacy features to ensure maximum security in sharing sensitive physiological data in consumer electronics. Recent approaches utilize the fusion concept to provide maximum privacy in health data sharing. Embedded signing data fusion with the health observed data ensures privacy preserved sharing across heterogeneous medical consumer devices for diagnosis. This article proposes a Dependency-correlated Data Fusion Scheme (DcDFS) to maximize the privacy of the health data-sharing process. The proposed scheme prepares separate key signing procedures using triple-DES (data encryption standard) to embed with the accumulated health data. The fusion process is carried out by defining key headers and integrity footers for authentication and verification. Therefore, the fusion generates a combined sequence of linear authentication and validation procedures enclosing the health data. In this scheme, the role of federated learning is to prevent permuted sequences for the same health data. This research integrates Small Language Model (SLM) and Large Language Model (LLM) into the federated learning module to support secure, scalable, and intelligent healthcare data sharing. Their collaboration enhances context-aware training while preserving privacy across decentralized, encrypted environments. A similar sequence mapped between the header and footer is responsible for discarding unauthorized data handling. The learning process verifies the permutation for many-to-one header to footer and vice versa. Therefore, the proposed fusion scheme generates a linear dependency between the actual and security-related data for maximum privacy. The proposed scheme achieves the following: the computation time is confined by 12.424%, the privacy leakage by 12.923%, and the computation efficiency is improved by 11.46%, as observed under the maximum sequences. © 1975-2011 IEEE.

关键词： Data Fusion Federated Learning Healthcare IoT Privacy-Preserving Triple DES

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A Comprehensive Survey on Intelligent Reflecting Surfaces and Unmanned Aerial Vehicles Integration for Enhanced Communication in Massive Networks 11

A Comprehensive Survey on Intelligent Reflecting Surfaces an...

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11th International Conference on Mechatronics and Robotics engineering, ICMRE 2025

作者： Attar, Hani Ababneh, Jafar Hafez, Mohamed Rachini, Ali Solyman, Ahmed Bahy, Ramy M. Zarqa University Faculty of Engineering Zarqa Jordan College of Engineering University of Business and Technology Jeddah21448 Saudi Arabia Zarqa University Faculty of Information Technology Cyber Security Department Zarqa Jordan INTI-IU-University Nilai Faculty of Engineering Feqs Malaysia Department of Computer Science and Information Technology Jounieh Lebanon School of Computing Engineering and Built Environment Glasgow Caledonian University Glasgow United Kingdom Technical Research Center Cairo Egypt

ISBN: (纸本)9798331509293

Intelligent Reflecting Surfaces (IRSs) offer a revolutionary approach to wireless communication by dynamically controlling the properties of electromagnetic waves. By manipulating wavefronts without requiring radio frequency links, IRSs can enhance spectrum and energy efficiency, reduce costs, and improve overall system performance. Unmanned Aerial Vehicles (UAVs) have garnered significant attention due to their mobility and adaptability. However, real-time data transmission between UAVs can be hindered by obstacles and security risks. By combining IRSs and UAVs, we can create unparalleled opportunities in demanding environments. Through coordinated movements and intelligent wave reflection, both systems can optimize wireless signal propagation. This paper provides a comprehensive review of IRS-assisted UAV communications. We explore existing research, introduce novel technologies and applications, and highlight potential research directions for developing low-cost and energy-efficient wireless systems. Additionally, we address current challenges and outline promising areas for future study. © 2025 IEEE.

关键词： Drones

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Towards Faster Fully Homomorphic Encryption Implementation with Integer and Floating-point Computing Power of GPUs

Towards Faster Fully Homomorphic Encryption Implementation w...

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International Symposium on Parallel and Distributed Processing (IPDPS)

作者： Guang Fan Fangyu Zheng Lipeng Wan Lili Gao Yuan Zhao Jiankuo Dong Yixuan Song Yuewu Wang Jingqiang Lin State Key Laboratory of Information Security Institute of Information Engineering Chinese Academy of Sciences Beijing China School of Cyber Security University of Chinese Academy of Sciences Beijing China Data Assurance and Communication Security Research Center Chinese Academy of Sciences Beijing China School of Cryptography University of Chinese Academy of Sciences Beijing China Department of Computer and Software Nanjing University of Information Science and Technology Nanjing China Ant Group Hangzhou China School of Computer Science Nanjing University of Posts and Telecommunications Nanjing China School of Cyber Security University of Science and Technology of China Hefei China

Fully Homomorphic Encryption (FHE) allows computations on encrypted data without knowledge of the plaintext message and currently has been the focus of both academia and industry. However, the performance issue hinders its large-scale application, highlighting the urgent requirements of high-performance FHE *** noticing the tremendous potential of GPUs in the field of cryptographic acceleration, this paper comprehensively investigates how to convert the available computing resources residing in GPUs into FHE workhorses, and implement a full set of low-level and middle-level FHE primitives based on two arithmetic units (i.e., INT32 and FP64 units) with three types of data precision (i.e., INT32, INT64 and FP64). This paper gives a comprehensive evaluation and comparison based on each road-map. Our implementations of fundamental functions outperform the implementations on the same platform by 1.7× to 16.7×. Taking CKKS FHE schemes as a case study, our implementation of homomorphic multiplication achieves 3.2× speedup over the state-of-the-art GPU-based implementation, even considering the difference of platforms. The detailed evaluation and comparison of this paper would offer a vital reference for the follow-up work to choose appropriate underlying arithmetic units and important primitive optimizations in GPU-based FHE implementations.

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Zero-pole cancellation for identity-based aggregators:a constant-size designated verifier-set signature

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Frontiers of computer science 2020年第4期14卷 197-210页

作者： E CHEN Yan ZHU Changlu LIN Kewei LV School of Computer and Communication Engineering University of Science and Technology BeijingBeijing100083China College of Mathematics and Informatics Fujian Normal UniversityFuzhou350117China Fujian Provincial Key Lab of Network Security&Cryptology Fujian Normal UniversityFuzhou350007China Institute of Information Engineering DCS Research CenterChinese Academy of SciencesBeijing100093China

In this paper we present a designated verifier-set signature(DVSS),in which the signer allows to designate many verifiers rather than one verifier,and each designated verifier can verify the validity of signature by *** research starts from identity-based aggregator(IBA)that compresses a designated set of verifier’s identities to a constant-size random string in cryptographic *** IBA is constructed by mapping the hash of verifier’s identity into zero or pole of a target curve,and extracting one curve’s point as the result of aggregation according to a specific *** the different types of target curves,these two IBAs are called as zeros-based aggregator and poles-based aggregator,*** on them,we propose a practical DVSS scheme constructed from the zero-pole cancellation method which can eliminate the same elements between zeros-based aggregator and poles-based *** to this design,our DVSS scheme has some distinct advantages:(1)the signature supporting arbitrary dynamic verifiers extracted from a large number of users;and(2)the signature with short and constant *** rigorously prove that our DVSS scheme satisfies the security properties:correctness,consistency,unforgeability and *** is a preview of subscription content,log in to check access.

关键词： designated verifier-set signature aggregator unforgeability exclusivity

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Leveraging Intel SGX to enable trusted and privacy preserving membership service in distributed ledgers

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International Journal of information and computer security 2021年第1-2期16卷 63-83页

作者： Liang, Xueping Shetty, Sachin Tosh, Deepak K. Foytik, Peter Zhang, Lingchen Institute of Information Engineering Chinese Academy of Sciences Beijing China School of Cyber Security University of Chinese Academy of Sciences Beijing China Virginia Modeling Analysis and Simulation Center Old Dominion University NorfolkVA United States Department of Computer Science University of Texas at EL Paso El PasoTX United States

Distributed ledger technology (DLT) provides decentralised services by removing the need of trust among distributed nodes in the distributed system. Transactions across the network are visible to all participants. However, some transactions may contain sensitive information such as business contracts or even personal health records. To protect user privacy, the architecture of distributed multi-channel ledger with membership service as a critical component can be adopted. The proposed multi-channel membership service architecture combines two promising technologies, distributed ledger and Intel Software Guard Extensions (SGX). With SGX remote attestation and isolated execution, each node is enrolled as a trusted entity to the channels, which separate different applications and provide better flexibility. We propose security properties for membership service in distributed ledger and illustrate how SGX help to achieve these properties in each phase. security analysis and evaluation show that the proposed architecture could enhance the privacy preservation and capabilities against attacks. Copyright © 2021 Inderscience Enterprises Ltd.

关键词： Blockchain

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Authentic Learning on DevOps security with Labware: Git Hooks To Facilitate Automated security Static Analysis

Authentic Learning on DevOps Security with Labware: Git Hook...

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IEEE Annual International computer Software and Applications Conference (COMPSAC)

作者： Md Mostafizur Rahman MD Abdul Barek Mst Shapna Akter Abm Kamrul Islam Riad Md Abdur Rahman Hossain Shahriar Akond Rahman Fan Wu Department of Information Technology University of West Florida Florida USA Department of Intelligent Systems and Robotics University of West Florida Florida USA Center for Cyber Security University of West Florida Florida USA Dept. of Computer Science and Software Engineering Auburn University USA Tuskegee University Alabama USA

ISBN: (数字)9798350376968

ISBN: (纸本)9798350376975

This paper presents an innovative approach to DevOps security education, addressing the dynamic landscape of cybersecurity threats. We propose a student-centered learning methodology by developing comprehensive hands-on learning modules. Specifically, we introduce labware modules designed to automate static security analysis, empowering learners to identify known vulnerabilities efficiently. These modules offer a structured learning experience with pre-lab, hands-on, and post-lab sections, guiding students through DevOps concepts and security challenges. In this paper, we introduce hands-on learning modules that familiarize students with recognizing known security flaws through the application of Git Hooks. Through prac-tical exercises with real-world code examples containing security flaws, students gain proficiency in detecting vulnerabilities using relevant tools. Initial evaluations conducted across educational institutions indicate that these hands-on modules foster student interest in software security and cybersecurity and equip them with practical skills to address DevOps security vulnerabilities.

关键词： Learning systems DevOps Codes Education Static analysis Dynamic scheduling Software

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Intersection-policy private mutual authentication from authorized private set intersection

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science China(information sciences) 2020年第2期63卷 116-130页

作者： Yamin WEN Fangguo ZHANG Huaxiong WANG Yinbin MIAO Zheng GONG School of Statistics and Mathematics Guangdong University of Finance and Economics State Key Laboratory of Cryptology School of Data and Computer Science Sun Yat-sen University Guangdong Key Laboratory of Information Security Sun Yat-sen University School of Physical and Mathematical Sciences Nanyang Technological University Department of Cyber Engineering Xidian University School of Computer South China Normal University

Private mutual authentication(PMA) enables two-way anonymous authentication between two users certified by the same trusted group authority. Most existing PMA schemes focus on acquiring a relatively onefold authentication policy that ensures affiliation-hiding or designated single-attribute ***, in practice, users are typically provided with multiple attributes. In addition to the affiliation-hiding requirement, how to effectively achieve a more flexible authentication policy for multi-attribute applications remains a challenging issue. The intersection policy for authentication is also required when the attribute intersection is not an empty set or its cardinality is no less than a threshold value. To solve the above problems, we first propose an optimal authorized private set intersection protocol with forward security based on identity-based encryption and then design a new PMA protocol with intersection-policy called IP-PMA, which provides a simple solution for secret handshakes between two members(holding multiple attributes) from the same organization. Formal security analyses proved that our two proposed protocols are secure in the random oracle model. Empirical tests demonstrated that the IP-PMA protocol is optimized with linear complexity and may be more suitable for resource-constrained applications.

关键词： private mutual authentication secret handshake intersection policy authorized private set intersection multi-attribute matching

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Design of blockchain-enabled secure smart health monitoring system and its testbed implementation

Cyber Security and Applications

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Cyber security and Applications 2023年 1卷

作者： Thapliyal, Siddhant Singh, Shubham Wazid, Mohammad Singh, D.P. Das, Ashok Kumar Department of Computer Science and Engineering Graphic Era Deemed to be University Dehradun 248 002 India Center for Security Theory and Algorithmic Research International Institute of Information Technology Hyderabad 500 032 India

Smart healthcare technology is transforming from the traditional healthcare system in every manner conceivably. Smart healthcare provides several advantages over the existing approaches. However, it suffers from healthcare data security and privacy issues. As the Internet attackers may get access to sensitive healthcare data through the use of various types of cyber attacks. In this paper, an architecture of a blockchain-enabled secure smart health monitoring system has been presented (in short, it is called as BSSHM). BSSHM consists of various health data monitoring sensors, i.e., temperature, heartbeat, etc., which monitor the real time health data of the different patients. The healthcare data of the patients can be transmitted to the connected health servers in a secure way, where this data can be stored securely for its various uses. The formal security verification of the proposed BSSHM is also done through the widely-accepted Scyther tool. It has been proved that BSSHM is able to defend various potential attacks. © 2023

关键词： Authentication Blockchain Cyber security Healthcare Internet of Medical Things (IoMT)

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Implementing OIML R46 Communication Unit for DLMS/COSEM security Suite 1 and Passing CTT V3.1 Test

Implementing OIML R46 Communication Unit for DLMS/COSEM Secu...

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IEEE International Conference on Networking, Sensing and Control

作者： Chun-Tsai Chien Chien-Lung Wang I-En Liao Sying-Jyan Wang Taiwan Information Security Center National Chung Hsing University Taichung City Taiwan R.O.C. Department of Computer Science and Engineering National Chung Hsing University Taichung City Taiwan R.O.C.

With the growing deployment of smart metering systems, ensuring secure and reliable communication between smart meters and utility providers is crucial. The DLMS/COSEM security Suite 1 offers a standardized framework for secure data exchange and authentication in smart metering applications. This paper focuses on the implementation of an PSA-based OIML R46 communication unit, following the principles of the Platform security Architecture framework, to achieve compliance with DLMS/COSEM security Suite 1 specifications. The proposed communication unit integrates cryptographic algorithms, secure storage mechanisms, and key management protocols to guarantee the confidentiality, integrity, and authenticity of the transmitted data. Furthermore, the unit undergoes rigorous testing using the DLMS Conformance Test Tool V3.1 to validate its compliance and interoperability. The results demonstrate the successful implementation of a secure OIML R46 communication unit that meets DLMS/COSEM security Suite 1 requirements and has undergone thorough CTT V3.1 testing.

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Deep Learning and CNN-Based Approach for Efficient Detection of Potato Leaf Diseases

Deep Learning and CNN-Based Approach for Efficient Detection...

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IEEE Asia-Pacific Conference on Geoscience, Electronics and Remote Sensing Technology (AGERS)

作者： Taher M. Ghazal Jamshaid Iqbal Janjua Walid Abushiba Muhammad Salah-ud-Din Iqbal Waqas Iqbal Munir Ahmad Muhammad Saleem Faculty of Information Science and Technology College of Arts & Science Applied Science University Manama Bahrain & Center for Cyber Security Universiti Kebangsaan Malaysia Selangor Malaysia Al-Khawarizimi Institute of Computer Science (KICS) University of Engineering & Technology (UET) Lahore Pakistan College of Engineering Applied Science University Bahrain School of Computer Science Minhaj University Lahore Pakistan Department of forestry and Range Management University of Agriculture Faisalabad Pakistan College of Informatics Korea University Seoul Republic of Korea

ISBN: (数字)9798331543105

ISBN: (纸本)9798331543112

Potato is a maj or food crop worldwide, providing essential nutrients to millions. However, various diseases can severely affect potato crops, leading to reduced yield and quality. Early disease detection is crucial for effective disease management and control. This study presents a deep learning-based approach using CNN to autonomously diagnose potato leaf diseases. The model leverages the Plant Village dataset, which contains images of potato leaves in both healthy and diseased states. The proposed method demonstrates high accuracy in identifying multiple potato leaf diseases, offering promising results for application in precision agriculture. By utilizing CNN s, the model effectively detects and classifies disease symptoms, providing a reliable tool for early intervention in agricultural practices. The approach's potential impact on improving crop yield and minimizing losses due to diseases is highlighted, making it a significant contribution to smart farming techniques. The study underscores the importance of deep learning in modern agricultural practices and its role in enhancing disease management strategies.

关键词： Deep learning Precision agriculture Smart agriculture Plants (biology) Geoscience Nutrients Reliability Remote sensing Diseases Testing

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