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Probabilistic Reliability via Subsystem Structures of Arrangement Graph networks

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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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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Quasi-Linearly Homomorphic Signature for Data Integrity Auditing in Cloud Storage 20th

Quasi-Linearly Homomorphic Signature for Data Integrity Aud...

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20th International Conference on Information security and Cryptology, Inscrypt 2024

作者： Zhang, Futai Huang, Yichi Yang, Wenjie Tian, Jinmei Fujian Provincial Key Laboratory of Network Security and Cryptology College of Computer and Cyber Security Fujian Normal University Fuzhou350117 China

ISBN: (纸本)9789819647330

As the popularity of cloud storage increases, data security issues have attracted significant attention from both academia and business sectors. Among these issues, data integrity auditing is of particular importance. To date, numerous data integrity auditing protocols for cloud storage have been available in the literature. Most of them are based on public key cryptography. In this paper, we examine the key technique involved in public key data integrity auditing in cloud storage. The concept and the security model of quasi-linearly homomorphic signature(QLHS) scheme are introduced. Its relationship with secure public key data integrity auditing in cloud storage is demonstrated. An efficient instantiation of the quasi-linearly homomorphic signature scheme is presented. The performance of a provable data possession(PDP) protocol using our QLHS scheme is analyzed. The comparison demonstrates that our approach is more efficient in terms of computation, communication, and storage space for cloud users. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Public key cryptography

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Malicious Client Detection with Differential Privacy Constraints Based on Model Update Slicing and K-Means Clustering 6

Malicious Client Detection with Differential Privacy Constra...

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6th International Conference on Frontier Technologies of Information and computer, ICFTIC 2024

作者： Qi, Mengshi Wang, Xin He, Yunpeng Yang, Ming Wu, Xiaoming Key Laboratory of Computing Power Network and Information Security Jinan250014 China Shandong Fundamental Research Center for Computer Science Shandong Provincial Key Laboratory of Industrial Network and Information System Security Jinan250014 China

ISBN: (纸本)9798331541750

Federated learning (FL) is a decentralized machine learning technique that protects data privacy by trainng models locally on devices and sharing only model updates instead of raw data. However, FL also faces multiple security challenges. Clientside poisoning attacks can compromise global model training by injecting malicious updates. Additionally, the server may infer private information from client model updates. Most existing studies address these two risks separately, lacking a systematic analysis and response to their combined threats. This paper proposes a method called Sliced-Clustering Guard (SCGuard), which slices gradients and performs clustering analysis on each segment, enabling the server to more accurately detect malicious updates and effectively differentiate malicious client updates with differential privacy (DP) protection. Experimental results demonstrate that SCGuard can mitigate poisoning attacks while effectively safeguarding clients' sensitive information. © 2024 IEEE.

关键词： Federated learning

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The Study of Multi-type Computing Power Trading Mechanism in Computing Power network Based on Blockchain and Combinatorial Double Auction 24

The Study of Multi-type Computing Power Trading Mechanism in...

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4th International Conference on Artificial Intelligence, Big Data and Algorithms, CAIBDA 2024

作者： Zhao, Yue Wang, Jizhi Kong, Lingrui Sui, Tongtong Shandong Computer Science Center National Supercomputer Center in Jinan Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Provincial Key Laboratory of Industrial Network and Information System Security Qilu University of Technology Shandong Academy of Sciences Jinan Shandong China Quancheng Laboratory Jinan Key Laboratory of Digital Security Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center National Supercomputer Center in Jinan Qilu University of Technology Shandong Academy of Sciences Shandong Provincial Key Laboratory of Industrial Network and Information System Security Shandong Fundamental Research Center for Computer Science Jinan Shandong China

ISBN: (纸本)9798400710247

The advancement of 5G and mobile internet technologies has propelled the development of emerging businesses and applications, demanding higher requirements for network bandwidth and computational resources. To address this challenge, the computing power network (CPN) has emerged. The CPN integrates computing and networking in depth, achieving collaborative allocation of distributed computing resources, enhancing the efficient utilization of computing resources, and improving user experiences in network services. However, in the development of fields such as Extended Reality (XR), Smart Healthcare, Connected Vehicles, and Artificial Intelligence (AI), there is a multidimensional, complex, and rapidly growing demand for computing resources. Therefore, it is crucial to establish a trading mechanism that integrates multiple computing resources in CPN. In this paper, a computing power trading scheme based on blockchain and combinatorial double auction is proposed. Firstly, a computing power trading system based on blockchain was designed, leveraging the decentralized and highly secure characteristics of blockchain technology to enhance the security of computing power transactions. Furthermore, a multi-type computing power trading mechanism (MCPT) based on blockchain and combinatorial double auction was introduced. The use of combinatorial double auctions as an incentive mechanism enables the trading of multiple computing power resources and results in high social welfare. Moreover, a discrete rime optimization algorithm (DRIME) is designed in the proposed mechanism (MCPT) to better solve the computing trading problem. Through simulation experiments, the effectiveness of the approach is validated. © 2024 Copyright held by the owner/author(s).

关键词： Computing power

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Feature Augmented Meta-Learning on Domain Generalization for Evolving Malware Classification 24th

Feature Augmented Meta-Learning on Domain Generalization fo...

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24th International Conference on Algorithms and Architectures for Parallel Processing, ICA3PP 2024

作者： Wang, Fangwei Chen, Yinhe Song, Ruixin Li, Qingru Wang, Changguang Key Laboratory of Network and Information Security of Hebei Province College of Computer and Cyber Security Hebei Normal University Shijiazhuang050024 China College of Computer Science and Technology Guizhou University Guiyang550025 China

ISBN: (纸本)9789819615278

The proliferation of malware has resulted in substantial harm to various sectors and economies. Various deep learning-based malware classification methods have been suggested as a means of mitigating malware threats. These methods typically operate under the assumption of independent and identically distributed training and test data. However, this assumption becomes invalid with the evolving malware family. While domain adaptation models offer a potential solution to this issue, their implementation is hindered by the difficulty of collecting new malware variants. In order to address the previously mentioned problem, we suggest an image-based technique for categorizing malware families utilizing domain generalization. Initially, malware is transformed into gray-scale images that depict byte patterns of the malware. Subsequently, these gray-scale images are fed into a model incorporating convolutional block attention to extract features. Furthermore, data augmentation is implemented at the feature level to broaden the distribution of the source domain and enhance the model’s generalization capabilities. Finally, meta-learning is utilized as a training approach to effectively extract domain-invariant representations. A series of experiments are conducted on the BIG2015 and BenchMFC-G1P1P2. The proposed method demonstrates a higher accuracy rate of 88.66% on the BIG2015 and 80.25% on the BenchMFC-G1P1P2, which is better than the existing methods. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Domain Generalization Domain Shift Feature Argumentation Malware Classification

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Aggregation-based dual heterogeneous task allocation in spatial crowdsourcing

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Frontiers of computer Science 2024年第6期18卷 215-227页

作者： Xiaochuan LIN Kaimin WEI Zhetao LI Jinpeng CHEN Tingrui PEI College of Information Science and Technology&Cyberspace Security Jinan UniversityGuangzhou 510632China National&Local Joint Engineering Research Center of Network Security Detection and Protection Technology Guangzhou 510632China Guangdong Provincial Key Laboratory of Data Security and Privacy Protection Guangzhou 510632China School of Computer Science Beijing University of Posts and TelecommunicationsBeijing 100876China

Spatial crowdsourcing(SC)is a popular data collection paradigm for numerous *** the increment of tasks and workers in SC,heterogeneity becomes an unavoidable difficulty in task *** researches only focus on the single-heterogeneous task ***,a variety of heterogeneous objects coexist in real-world SC *** dramatically expands the space for searching the optimal task allocation solution,affecting the quality and efficiency of data *** this paper,an aggregation-based dual heterogeneous task allocation algorithm is put *** investigates the impact of dual heterogeneous on the task allocation problem and seeks to maximize the quality of task completion and minimize the average travel *** problem is first proved to be ***,a task aggregation method based on locations and requirements is built to reduce task ***,a time-constrained shortest path planning is also developed to shorten the travel distance in a *** that,two evolutionary task allocation schemes are ***,extensive experiments are conducted based on real-world datasets in various *** with baseline algorithms,our proposed schemes enhance the quality of task completion by up to 25% and utilize 34% less average travel distance.

关键词： task allocation aggregation shortest path dual heterogeneous spatial crowdsourcing

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Cross-chain Transaction Tracking Protocol based on Multi-dimensional Digital Watermarking Fingerprints 6

Cross-chain Transaction Tracking Protocol based on Multi-dim...

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6th International Conference on Frontier Technologies of Information and computer, ICFTIC 2024

作者： Li, Duanzhen Xu, Shujiang He, Haochen Xue, Hongrui Key Laboratory of Computing Power Network and Information Security Ministry of Education Jinan250014 China Shandong Fundamental Research Center for Computer Science Shandong Provincial Key Laboratory of Industrial Network and Information System Security Jinan250014 China

ISBN: (纸本)9798331541750

Cross-chain technology plays a critical role in the process of interconnecting blockchains. However, all attention has been focused on how to achieve efficient cross-chain interoperability protocols, thus neglecting the most important security issues in cross-chain data interaction. Frequent network attacks and data privacy leaks have sounded the alarm for the safety of cross-chain data transactions. How to solve the problem of data ownership tracking in cross-chain transactions has become the top priority. This paper designs a cross-chain transaction tracking protocol based on multi-dimensional digital watermark fingerprints, using robust watermark, fragile watermark, and user identity key to achieve multi-dimensional tracking and supervision of cross-chain data transactions. Finally, this paper analyzes the feasibility and efficiency of the proposed protocol through experiments. © 2024 IEEE.

关键词： Blockchain

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A Novel Construction of Updatable Identity-Based Hash Proof System and Its Applications

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Chinese Journal of Electronics 2023年第3期32卷 564-576页

作者： QIAO Zirui ZHOU Yanwei YANG Bo ZHANG Wenzheng ZHANG Mingwu School of Computer Science Shaanxi Normal University State Key Laboratory of Cryptology Science and Technology on Communication Security Laboratory Henan Key Laboratory of Network Cryptography Technology School of Computere Hubei University of Technology

In the previous works, to further provide the continuous leakage resilience for the identity-based encryption scheme, a new cryptography primitive, called updatable identity-based hash proof system(U-IB-HPS),was proposed. However, most of the existing constructions have some deficiencies, they either do not have perfect key update function or the corresponding security with tight reduction relies on a non-static complexity assumption. To address the above problems, a new construction of U-IB-HPS is created, and the corresponding security of our system is proved based on the static complexity assumption. Also, the corresponding comparisons and analysis of performances show that our proposal not only achieves the perfect key update function and the anonymity, but also has the tight security reduction. In additional, our proposal achieves the same computational efficiency as other previous systems. To further illustrate the practical function of U-IB-HPS, a generic method of non-interactive data authorization protocol with continuous leakage resilience is designed by employing U-IB-HPS as an underlying tool, which can provide continuous leakage-resilient data authorization function for the cloud computing. Hence, the application field of U-IB-HPS is further extended through our study.

关键词： Authorization Cloud computing Protocols Identity-based encryption Complexity theory Computational efficiency Proposals

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The dummy-based trajectory privacy protection method to resist correlation attacks in Internet of Vehicles

The dummy-based trajectory privacy protection method to resi...

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作者： Chen, Qiuling Ye, Ayong Zhao, Ziwen Xiong, Jinbo Fujian Provincial Key Laboratory of Network Security and Cryptology College of Computer and Cyber Security Fujian Normal University Fuzhou China

Existing dummy-based trajectory privacy protection schemes do not take into account the correlation of multiple locations and whether the generated trajectory based on dummies matches the user's movement mode, which enables the adversary to identify some dummies. Aiming at this problem, to ensure that the generated trajectories match the movement modes of users, historical query trajectories of users are selected. In this way, the generated dummies on the selected historical query trajectories are based on the location relationship of adjacent time and the background information constraint of the dummy, namely, they should meet the time reachability, the similarity of historical query probability and the maximum in-degree. security analysis shows that the proposed scheme effectively perturbs the spatiotemporal correlation between the real location and dummies. Furthermore, the proposed scheme is compared with the existing schemes in terms of single-point location exposure risk and trajectory exposure risk, and the experimental results indicate that the proposal has significant improvement in location privacy protection of the user. © 2022 John Wiley & Sons, Ltd.

关键词： Location

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