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Forward Legal Anonymous Group Pairing-Onion Routing for Mobile Opportunistic networks

IEEE Transactions on Mobile Computing 2025年第7期24卷 6595-6612页

作者： Zhu, Xiuzhen Lin, Limei Huang, Yanze Wang, Xiaoding Hsieh, Sun-Yuan Wu, Jie Fujian Normal University College of Computer and Cyber Security Fujian Provincial Key Laboratory of Network Security and Cryptology Fuzhou350117 China Fujian University of Technology School of Computer Science and Mathematics Fuzhou350118 China National Cheng Kung University Department of Computer Science and Information Engineering Tainan701 Taiwan Temple University Department of Computer and Information Science PhiladelphiaPA19122 United States

Mobile Opportunistic networks (MONs) often experience frequent interruptions in end-to-end connections, which increases the likelihood of message loss during delivery and makes users more susceptible to various cyber attacks. However, most currently proposed anonymous routing protocols are primarily designed for networks with stable connections, making it challenging to protect user identities in MONs. To address these challenges, we propose FLAG-POR (Forward Legal Anonymous Group Pairing-Onion Routing), a novel anonymous routing protocol specifically tailored to enhance message delivery anonymity and security in MONs. Specifically, we abstract the mobile opportunistic network as a contact graph. By introducing the concept of 'groups' into the pairing-onion routing protocol, which encrypts messages and relay nodes layer by layer, we develop a novel group-based pairing-onion routing protocol. This protocol ensures message confidentiality and relay node anonymity, while also improving message forwarding rates, as any node within a group can potentially act as a relay. To ensure message authenticity, we employ the efficient SM2 signing algorithm to generate signatures for the message source. Furthermore, by incorporating parameters such as the public key validity period and master key validity period into the group pairing-onion routing protocol, we achieve forward security in message delivery. We conduct a thorough theoretical analysis of the protocol's security and performance. The experimental results demonstrate that our FLAG-POR protocol outperforms baseline anonymous protocols in terms of delivery success rate, traceability rate, path anonymity, and node anonymity. Additionally, the FLAG-POR scheme effectively resists three potential threats to the routing system: collusion attack threat, node identification threat, and path identification threat, in any situation. © 2025 IEEE.

关键词： Anonymity

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AI-enabled dental caries detection using transfer learning and gradient-based class activation mapping

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Journal of Ambient Intelligence and Humanized Computing 2024年第7期15卷 3009-3033页

作者： Inani, Hardik Mehta, Veerangi Bhavsar, Drashti Gupta, Rajeev Kumar Jain, Arti Akhtar, Zahid Department of Computer Science and Engineering Pandit Deendayal Energy University Gujarat Gandhinagar India Department of Computer Science and Engineering and Information Technology Jaypee Institute of Information Technology Uttar Pradesh Noida India Department of Network and Computer Security State University of New York Polytechnic Institute NY United States

Dental caries detection holds the key to unlocking brighter smiles and healthier lives by identifying one of the most common oral health issues early on. This vital topic sheds light on innovative ways to combat tooth decay, empowering individuals to take control of their oral health and maintain radiant smiles. This research paper delves into the realm of transfer learning techniques, aiming to elevate the precision and efficacy of dental caries diagnosis. Utilizing Keras ImageDataGenerator, a rich and balanced dataset is crafted by augmenting teeth images from the Kaggle teeth dataset. Five cutting-edge pre-trained architectures are harnessed in the transfer learning approach: EfficientNetV2B3, VGG19, InceptionResNetV2, Xception, and ResNet50, with each model, initialized using ImageNet weights and tailored top layers. A comprehensive set of evaluation metrics, encompassing accuracy, precision, recall, F1-score, and false negative rates are employed to gauge the performance of these architectures. The findings unveil the unique advantages and drawbacks of each model, illuminating the path to an optimal choice for dental caries detection using Grad-CAM (Gradient-weighted Class Activation Mapping). The testing accuracies achieved by EfficientNetV2B3, VGG19, InceptionResNetV2, Xception, and ResNet50 models stand at 95.89%, 96.58%, 93.15%, 93.15%, and 94.18%, respectively. The Training accuracies stood at 100%, 99.91%, 100%, 100% and 100%, meanwhile on validation we achieved 97.63%, 96.68%, 98.82%, 96.68%, and 100% accuracies for EfficientNetV2B3, VGG19, InceptionResNetV2, Xception, and ResNet50 models respectively. Capitalizing on transfer learning and juxtaposing diverse pre-trained architectures, this research paper paves the way for substantial advancements in dental diagnostic capabilities, culminating in enhanced patient outcomes and superior oral health. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.

关键词： Chemical activation

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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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Endogenous security of FQn networks: Adaptive System-Level Fault Self-Diagnosis

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IEEE Transactions on Reliability 2024年第3期73卷 1659-1668页

作者： Lin, Yuhang Lin, Limei Huang, Yanze Xu, Li Hsieh, Sun-Yuan Fujian Normal University College of Computer and Cyber Security Fujian Provincial Key Laboratory of Network Security and Cryptology Fuzhou350117 China Fujian University of Technology School of Computer Science and Mathematics Fuzhou350118 China National Cheng Kung University Department of Computer Science and Information Engineering Tainan701 Taiwan

Endogenous security has the ability to discover, eliminate, and solve internal security problems and hidden dangers within the network, and is a superior technology to ensure future network security. The t/k-diagnosis strategy, as a strong and adaptive self-diagnosis strategy, is an important part for ensuring endogenous security. Moreover, the folded hypercube (FQn) as a data transmission network (e.g., optical network) topology offers new potential for the construction of large-scale, high data throughput, and low-latency systems, such as computing network, human-cyber-physical systems, and smart grid. However, there are few studies on endogenous security based on FQn networks. Therefore, this article designs an adaptive system-level fault self-diagnosis strategy, namely Fast t/k-Diagnosis Under Maeng-Malek Model (Ftk-DIAG-MM*) to diagnosis the faulty vertices in FQn network under the Maeng-Malek model (MM∗ mod). Then, we provide a proof of the algorithm correctness theoretically by the fault tolerance of FQn network. It is derived by theoretical derivation that the t/k-diagnosability inherent to the FQn network is (n+1)(k+1)-k(k+3)/2. The simulation experiments demonstrate that the designed Ftk-DIAG-MM∗ strategy can correctly diagnose all vertices within the range allowed by the diagnosability, and still has a great performance when it exceeds the range allowed by the diagnosability. It greatly enhances the fault diagnosis capability of FQn network in the circumstance of misdiagnosing a few vertices, which provides an important theoretical basis for the reliability and endogenous security of FQn networks. © 1963-2012 IEEE.

关键词： Topology

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Enhancing TrUStAPIS Methodology in the Web of Things with LLM-Generated IoT Trust Semantics 26th

Enhancing TrUStAPIS Methodology in the Web of Things with LL...

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26th International Conference on information and Communications security, ICICS 2024

作者： Ferraris, Davide Kotis, Konstantinos Kalloniatis, Christos Network Information and Computer Security Lab University of Malaga Malaga Spain Department of Cultural Technology and Communication University of the Aegean Mytilene Greece

ISBN: (纸本)9789819787975

In the Internet of Things (IoT) there are ecosystems where their physical’smart’ entities virtually interact with each other. Often, this interaction occurs among unknown entities, making trust an essential requirement to overcome uncertainty in several aspects of this interaction. However, trust is a complex concept, and incorporating it in IoT is still a challenging topic. For this reason, it is highly significant to specify and model trust in early stages of the System Development Life Cycle (SDLC) of IoT-integrated systems, thus enhancing the aforementioned task. TrUStAPIS is a requirements engineering methodology recently introduced for incorporating trust requirements during IoT-based system design. The scope of this paper is to provide an extension of TrUStAPIS by introducing IoT trust semantics compatible with the W3C Web of Things (WoT) recommendations generated with the assistance of Large Language Models (LLMs). Taking advantage of LLMs as a tool for integrating and refining existing methodologies, in this paper we present our work towards a revision of the TrUStAPIS methodology. In this work, we contribute a new conceptual model and a refined JSON-LD ontology that takes into account IoT trust semantics, providing eventually a valuable tool for software engineers to design and model IoT-based systems and services. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Requirements engineering

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Controllable False Data Injection Attack 5th

Controllable False Data Injection Attack

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5th International Conference on Data Science, Machine Learning and Applications, ICDSMLA 2023

作者： Kokkonda, Jayasree Jahnavi, M. Department of Information Technology G. Narayanamma Institute of Technology and Science Hyderabad India Department of Computer Network and Information Security Narayanamma Institute of Technology and Science Hyderabad India

ISBN: (纸本)9789819780426

Yet the Internet of Things continues to grow significantly. A cyber-physical system faces a variety of security challenges due to the network connections made by the various kinds of devices and large systems that make up national infrastructures like a smart grid. Here, For the forward flow and the feedback path of a control system, respectively, we suggest two fake data injection attacks. Both are made using a variable parameter that determines the degree of deterioration. On the forward path, a linear forward assault is created together with the least squares approach. The Kalman filter is constructed on the feedback route. According to the numerical analysis, the suggested assaults govern how much the performance of the control system declines. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Kalman filters

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Probabilistic Reliability via Subsystem Structures of Arrangement Graph networks

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IEEE Transactions on Reliability 2024年第1期73卷 279-289页

作者： Huang, Yanze Lin, Limei Xu, Li Hsieh, Sun-Yuan Fujian University of Technology Fujian Provincial Key Laboratory of Big Data Mining and Applications School of Computer Science and Mathematics Fuzhou350118 China Fujian Normal University College of Computer and Cyber Security Key Laboratory of Network Security and Cryptology Fuzhou350117 China National Cheng Kung University Department of Computer Science and Information Engineering Tainan701 Taiwan

With the rapid growth of the number of processors in a multiprocessor system, faulty processors occur in it with a probability that rises quickly. The probability of a subsystem with an appropriate size being fault-free in a definite time interval is a significant and practical measure of the reliability for a multiprocessor system, which characterizes the functionality of a multiprocessor system well. Motivated by the study of subgraph reliability, as well as the attractive structure and fault tolerance properties of (n, k)-arrangement graph A n, k, we focus on the subgraph reliability for A n, k under the probabilistic fault model in this article. First, we investigate intersections of no more than four subgraphs in A n, k, and classify all the intersecting modes. Second, we focus on the probability P(q, A n, k n-1, k-1) with which at least one (n-1, k-1)-subarrangement graph is fault-free in A n, k, when given a uniform probability q with which a single vertex is fault-free, and we establish the P(q, A n, kn-1, k-1) by adopting the principle of inclusion-exclusion under the probabilistic fault model. Finally, we study the probabilistic fault model involving a nonuniform probability with which a single vertex is fault-free, and we prove that the P(q, A n, kn-1, k-1) under both models is very close to the asymptotic value by both theoretical arguments and experimental results. © 1963-2012 IEEE.

关键词： Fault tolerance

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Integration of MPC into Besu through an extended private transaction model

Integration of MPC into Besu through an extended private tra...

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

作者： Morales, Daniel Agudo, Isaac Lopez, Javier Itis Software Universidad de Málaga Network Information and Computer Security Lab Department of Computer Science Málaga Spain

ISBN: (纸本)9798350333336

In the last few years we have seen many different approaches to incorporate privacy features to blockchains. In the area of cryptocurrencies that would normally mean protecting the identity of the owner of some funds, but there are other applications where privacy is even more important, especially in permissioned blockchains. Permissioned blockchain platforms, such as Hyperledger Besu or Hyperledger Fabric, already include the concept of private transactions, which essentially defines a sub-group of the blockchain where their participants share some private data. We want to go one step ahead and propose an extended model for private transactions where the different participants can have a separated view of the same transaction, allowing the integration of Multi-party Computation protocols in the blockchain. Our work extends Hyperledger Besu's design for private transactions, offering better security properties and a finer grain customization. We cover two specific MPC examples, Private Set Intersection and Byzantine Fault-Tolerant Random Number Generation, and propose a mechanism to run them using smart contract interfaces. © 2023 IEEE.

关键词： Blockchain

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Federated Transfer Learning for On-Device LLMs Efficient Fine Tuning Optimization

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Big Data Mining and Analytics 2025年第2期8卷 430-446页

作者： Chuantao Li Bruce Gu Zhigang Zhao Youyang Qu Guomao Xin Jidong Huo Longxiang Gao Key Laboratory of Computing Power Network and Information Security Shandong Computer Science Center(National Supercomputer Center in Jinan)Qilu University of Technology(Shandong Academy of Sciences)Jinan 250000Chinaand also with Shandong Provincial Key Laboratory of Computer NetworksJinan 250000China Key Laboratory of Computing Power Network and Information Security Shandong Computer Science Center(National Supercomputer Center in Jinan)Qilu University of Technology(Shandong Academy of Sciences)Jinan 250000Chinaand also with Department of Computer ScienceFudan UniversityShanghai 200000China TelChina Group Co.Ltd. Jinan 250000China Key Laboratory of Computing Power Network and Information Security Shandong Computer Science Center(National Supercomputer Center in Jinan)Qilu University of Technology(Shandong Academy of Sciences)Jinan 250000Chinaand also with College Oceanography and Space InformaticsChina University of Petroleum(East China)Qingdao 266000China

The proliferation of Large Language Models(LLMs)has catalyzed the growth of various *** is therefore imperative to ensure the controlled and beneficial application of LLMs across specific domains for downstream tasks through transfer learning,while preserving their general *** propose a novel and on-device efficient fine-tuning optimization algorithm for LLMs,utilizing federated transfer ***,we introduce the Fusion of low Rank Adaptation(FoRA)optimization algorithm from a micro perspective,which enhances multi-dimensional feature aggregation through the addition of efficient *** a meso perspective,we extend the application of the FoRA algorithm across all linear layers within the Transformer architecture to facilitate downstream task ***,from a macro perspective and with a focus on the medical domain,we incorporate quantization techniques into the federated learning framework to achieve on-device efficient fine-tuning optimization,thereby offering dual protection for data and model *** results indicate that,compared to existing state-of-the-art methods,our algorithm significantly improves LLM performance while ensuring dual privacy protection of both data and models.

关键词： Federated learning fine-tuning deep learning Large Language Models(LLMs)

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Continuous and Transparent E-Invigilation of E-Assessments

International Journal of Emerging Technologies in Learning

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International Journal of Emerging Technologies in Learning 2023年第14期18卷 78-104页

作者： Ketab, Salam S. Al Abdulwahid, Abdulwahid Centre for Security Communications and Network Research at Plymouth University Plymouth United Kingdom Computer and Information Technology Department Jubail Industrial College Royal Commission for Jubail and Yanbu Jubail Saudi Arabia

A massive number of users are currently utilizing e-learning. Despite the flexibility provided, the traditional methods of course delivery are still used, including e-examinations. There is significant concern about the potential for cheating. The current solutions in this respect fundamentally fail to offer the required level of security. This paper seeks to develop an e-invigilator that will provide continuous and transparent invigilation of examinees. The study involves a detailed presentation of the proposed architecture and a complete design to be the core of the system, which captures, processes, and monitors students in a controlled and convenient fashion. The proposed framework prototype was developed, presented, and utilized, involving 51 participants to conduct an experiment to explore the viability of the proposed framework. For all 51 participants in this experiment, the false rejection rate was 0 in 2D facial recognition mode, while in 3D facial recognition mode it was 0.04827. Moreover, in order to evaluate the robustness of the approach against targeted misuse, three participants were tasked with a series of nine threat scenarios. The false acceptance rate was 0.038 in the 2D mode and 0 in the 3D mode. © 2023 by the authors of this article. Published under CC-BY.

关键词： Face recognition

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