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An Enhanced Clustering-Based (k, t)-Anonymity Algorithm for Graphs

Chinese Journal of Electronics 2025年第1期34卷 365-372页

作者： Yuanyuan Wang Xing Zhang Zhiguang Chu Wei Shi Xiang Li School of Electronics and Information Engineering Liaoning University of Technology Key Laboratory of Security for Network and Data in Industrial Internet of Liaoning Province Faculty of Information Technology Beijing University of Technology

As people become increasingly reliant on the Internet, securely storing and publishing private data has become an important issue. In real life, the release of graph data can lead to privacy breaches, which is a highly challenging problem. Although current research has addressed the issue of identity disclosure, there are still two challenges: First, the privacy protection for large-scale datasets is not yet comprehensive; Second, it is difficult to simultaneously protect the privacy of nodes, edges, and attributes in social networks. To address these issues, this paper proposes a(k,t)-graph anonymity algorithm based on enhanced clustering. The algorithm uses k-means++ clustering for k-anonymity and t-closeness to improve k-anonymity. We evaluate the privacy and efficiency of this method on two datasets and achieved good results. This research is of great significance for addressing the problem of privacy breaches that may arise from the publication of graph data.

关键词： Data privacy Uncertainty Social networking (online) Publishing Heuristic algorithms Scalability Clustering algorithms Privacy breach Internet Protection

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Constructing the Impossible Differential of Type-II GFN with Boolean Function and Its Application to WARP

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Chinese Journal of Electronics 2024年第1期33卷 80-89页

作者： Jiali SHI Guoqiang LIU Chao LI College of Liberal Arts and Sciences National University of Defense Technology Hunan Engineering Research Center of Commercial Cryptography Theory and Technology Innovation State Key Laboratory of Information Security Institute of Information Engineering

Type-Ⅱ generalized Feist el network（GFN） has attracted a lot of attention for its simplicity and high *** differential attack is one of the powerful cryptanalytic approaches for word-oriented block ciphers such as Feistel-like *** deduce the impossible differential of Type-Ⅱ GFN by analyzing the Boolean function in the middle *** main idea is to investigate the expression with the variable representing the plaintext（ciphertext） difference words for the internal state *** adopting the miss-in-the-middle approach,we can construct the impossible differential of Type-Ⅱ *** an illustration,we apply this approach to WARP,a lightweight 128-bit block cipher with a 128-bit key which was presented by Banik et *** SAC *** structure of WARP is a 32-branch Type-Ⅱ ***,we find two 21-round truncated impossible differentials and implement a 32-round key recovery attack on *** the 32-round key recovery attack on WARP,some observations are used to mount an effective *** the advantage of the early abort technique,the data,time,and memory complexities are 2125.69chosen plaintexts,2126.6832-round encryptions,and 2100-bit,*** the best of our knowledge,this is the best attack on WARP in the single-key scenario.

关键词： WARP Feistel cipher Impossible differential attack

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A verifiable EVM-based cross-language smart contract implementation scheme for matrix calculation

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Digital Communications and Networks 2025年第2期11卷 432-441页

作者： Yunhua He Yigang Yang Chao Wang Anke Xie Li Ma Bin Wu Yongdong Wu Information Science and Technology North China University of Technology Institute of Information Engineering Chinese Academy of Sciences Bei Hang University Yunnan Innovation Institute College of Cyber Security and College of Information Science and Technology Jinan University

The wide application of smart contracts allows industry companies to implement some complex distributed collaborative businesses, which involve the calculation of complex functions, such as matrix operations. However, complex functions such as matrix operations are difficult to implement on Ethereum Virtual Machine(EVM)-based smart contract platforms due to their distributed security environment limitations. Existing off-chain methods often result in a significant reduction in contract execution efficiency, thus a platform software development kit interface implementation method has become a feasible way to reduce overheads, but this method cannot verify operation correctness and may leak sensitive user data. To solve the above problems, we propose a verifiable EVM-based smart contract cross-language implementation scheme for complex operations, especially matrix operations, which can guarantee operation correctness and user privacy while ensuring computational efficiency. In this scheme, a verifiable interaction process is designed to verify the computation process and results, and a matrix blinding technology is introduced to protect sensitive user data in the calculation process. The security analysis and performance tests show that the proposed scheme can satisfy the correctness and privacy of the cross-language implementation of smart contracts at a small additional efficiency cost.

关键词： Smart contract Blockchain Cross-language programming Bilinear pairing Publicly verifiable computation

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FedCLCC:A personalized federated learning algorithm for edge cloud collaboration based on contrastive learning and conditional computing

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Defence technology(防务技术) 2025年第1期43卷 80-93页

作者： Kangning Yin Xinhui Ji Yan Wang Zhiguo Wang School of Information and Software Engineering University of Electronic Science and Technology of ChinaChengdu611731China Institute of Public Security Kash Institute of Electronics and Information IndustryKashi844000China

Federated learning(FL)is a distributed machine learning paradigm for edge cloud *** can facilitate data-driven decision-making in tactical scenarios,effectively addressing both data volume and infrastructure challenges in edge ***,the diversity of clients in edge cloud computing presents significant challenges for *** federated learning(pFL)received considerable attention in recent *** example of pFL involves exploiting the global and local information in the local *** pFL algorithms experience limitations such as slow convergence speed,catastrophic forgetting,and poor performance in complex tasks,which still have significant shortcomings compared to the centralized *** achieve high pFL performance,we propose FedCLCC:Federated Contrastive Learning and Conditional *** core of FedCLCC is the use of contrastive learning and conditional *** learning determines the feature representation similarity to adjust the local *** computing separates the global and local information and feeds it to their corresponding heads for global and local *** comprehensive experiments demonstrate that FedCLCC outperforms other state-of-the-art FL algorithms.

关键词： Federated learning Statistical heterogeneity Personalized model Conditional computing Contrastive learning

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TransTM:A device-free method based on time-streaming multiscale transformer for human activity recognition

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Defence technology（防务技术） 2024年第2期32卷 619-628页

作者： Yi Liu Weiqing Huang Shang Jiang Bobai Zhao Shuai Wang Siye Wang Yanfang Zhang Institute of Information Engineering Chinese Academy of Sciences School of Cyber SecurityUniversity of Chinese Academy of SciencesBeijingChina School of Information Management Beijing Information Science and Technology UniversityBeijingChina

RFID-based human activity recognition(HAR)attracts attention due to its convenience,noninvasiveness,and privacy *** RFID-based HAR methods use modeling,CNN,or LSTM to extract features ***,they have shortcomings:1)requiring complex hand-crafted data cleaning processes and 2)only addressing single-person activity recognition based on specific RF *** solve these problems,this paper proposes a novel device-free method based on Time-streaming Multiscale Transformer called *** model leverages the Transformer's powerful data fitting capabilities to take raw RFID RSSI data as input without ***,we propose a multiscale convolutional hybrid Transformer to capture behavioral features that recognizes singlehuman activities and human-to-human *** with existing CNN-and LSTM-based methods,the Transformer-based method has more data fitting power,generalization,and ***,using RF signals,our method achieves an excellent classification effect on human behaviorbased classification *** results on the actual RFID datasets show that this model achieves a high average recognition accuracy(99.1%).The dataset we collected for detecting RFID-based indoor human activities will be published.

关键词： Human activity recognition RFID Transformer

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A WKB method based on parabolic cylinder function for very-low-frequency sound propagation in deep ocean

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Chinese Physics B 2025年第3期34卷 433-446页

作者： Jian-Kang Zhan Sheng-Chun Piao Li-Jia Gong Yang Dong Yong-Chao Guo Guang-Xue Zheng National Key Laboratory of Underwater Acoustic Technology Harbin Engineering UniversityHarbin 150001China Key Laboratory of Marine Information Acquisition and Security(Harbin Engineering University) Ministry of Industry and Information TechnologyHarbin 150001China College of Underwater Acoustic Engineering Harbin Engineering UniversityHarbin 150001China

A Wentzel-Kramers-Brillouin(WKB)method is introduced for obtaining a uniform asymptotic solution for underwater sound propagation at very low frequencies in deep *** method utilizes a mode sum and employs the reference functions method to describe the solution to the depth-separated wave equation approximately using parabolic cylinder *** conditions for the validity of this approximation are also ***,a formula that incorporates waveguide effects for the modal group velocity is derived,revealing that boundary effects at very low frequencies can have a significant impact on the propagation characteristics of even low-order normal *** present method not only offers improved accuracy compared to the classical WKB approximation and the uniform asymptotic approximation based on Airy functions,but also provides a wider range of depth ***,this method exhibits strong agreement with numerical methods and offers valuable physical ***,the method is applied to the study of very-low-frequency sound propagation in the South China Sea,leading to sound transmission loss predictions that closely align with experimental observations.

关键词： WKB method normal modes very-low-frequency sound propagation parabolic cylinder function

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Efficient Penetration Testing Path Planning Based on Reinforcement Learning with Episodic Memory

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Computer Modeling in engineering & Sciences 2024年第9期140卷 2613-2634页

作者： Ziqiao Zhou Tianyang Zhou Jinghao Xu Junhu Zhu Henan Key Laboratory of Information Security National Engineering Technology Research Center of the Digital Switching SystemZhengzhou450000China School of Cryptographic Engineering Information Engineering UniversityZhengzhou450000China

Intelligent penetration testing is of great significance for the improvement of the security of information systems,and the critical issue is the planning of penetration test *** view of the difficulty for attackers to obtain complete network information in realistic network scenarios,Reinforcement Learning(RL)is a promising solution to discover the optimal penetration path under incomplete information about the target *** RL-based methods are challenged by the sizeable discrete action space,which leads to difficulties in the ***,most methods still rely on experts’*** address these issues,this paper proposes a penetration path planning method based on reinforcement learning with episodic ***,the penetration testing problem is formally described in terms of reinforcement *** speed up the training process without specific prior knowledge,the proposed algorithm introduces episodic memory to store experienced advantageous strategies for the first ***,the method offers an exploration strategy based on episodic memory to guide the agents in *** design makes full use of historical experience to achieve the purpose of reducing blind exploration and improving planning ***,comparison experiments are carried out with the existing RL-based *** results reveal that the proposed method has better convergence *** running time is reduced by more than 20%.

关键词： Intelligent penetration testing penetration testing path planning reinforcement learning episodic memory exploration strategy

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High-Secured Image LSB Steganography Using AVL-Tree with Random RGB Channel Substitution

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Computers, Materials & Continua 2024年第10期81卷 183-211页

作者： Murad Njoum Rossilawati Sulaiman Zarina Shukur Faizan Qamar Center of Cyber Security Faculty of Information Science and TechnologyUniversiti Kebangsaan MalaysiaBangiSelangor43600Malaysia Computer Science and Cyber Security Faculty of Engineering and Information TechnologyBirZeit UniversityBirZeitRamallahP.O.Box 14Palestine

Random pixel selection is one of the image steganography methods that has achieved significant success in enhancing the robustness of hidden *** property makes it difficult for steganalysts’powerful data extraction tools to detect the hidden data and ensures high-quality stego image ***,using a seed key to generate non-repeated sequential numbers takes a long time because it requires specific mathematical *** addition,these numbers may cluster in certain *** hidden data in these clustered pixels will reduce the image quality,which steganalysis tools can ***,this paper proposes a data structure that safeguards the steganographic model data and maintains the quality of the stego *** paper employs the AdelsonVelsky and Landis(AVL)tree data structure algorithm to implement the randomization pixel selection technique for data *** AVL tree algorithm provides several advantages for image ***,it ensures balanced tree structures,which leads to efficient data retrieval and insertion ***,the self-balancing nature of AVL trees minimizes clustering by maintaining an even distribution of pixels,thereby preserving the stego image *** data structure employs the pixel indicator technique for Red,Green,and Blue(RGB)channel *** green channel serves as the foundation for building a balanced binary ***,the sender identifies the colored cover image and secret *** sender will use the two least significant bits(2-LSB)of RGB channels to conceal the data’s size and associated *** next step is to create a balanced binary tree based on the green *** the channel pixel indicator on the LSB of the green channel,we can conceal bits in the 2-LSB of the red or blue *** first four levels of the data structure tree will mask the data size,while subsequent levels will conceal the remaining digits of secret *** embedding the bits i

关键词： Image steganography pixel random selection(PRS) AVL tree peak signal-to-noise ratio(PSNR) imperceptibility capacity

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Two-Layer Attention Feature Pyramid Network for Small Object Detection

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Computer Modeling in engineering & Sciences 2024年第10期141卷 713-731页

作者： Sheng Xiang Junhao Ma Qunli Shang Xianbao Wang Defu Chen College of Information Engineering Zhejiang University of TechnologyHangzhou310023China Binjiang Cyberspace Security Institute of ZJUT Hangzhou310056China

Effective small object detection is crucial in various applications including urban intelligent transportation and pedestrian ***,small objects are difficult to detect accurately because they contain less *** current methods,particularly those based on Feature Pyramid Network(FPN),address this challenge by leveraging multi-scale feature ***,existing FPN-based methods often suffer from inadequate feature fusion due to varying resolutions across different layers,leading to suboptimal small object *** address this problem,we propose the Two-layerAttention Feature Pyramid Network(TA-FPN),featuring two key modules:the Two-layer Attention Module(TAM)and the Small Object Detail Enhancement Module(SODEM).TAM uses the attention module to make the network more focused on the semantic information of the object and fuse it to the lower layer,so that each layer contains similar semantic information,to alleviate the problem of small object information being submerged due to semantic gaps between different *** the same time,SODEM is introduced to strengthen the local features of the object,suppress background noise,enhance the information details of the small object,and fuse the enhanced features to other feature layers to ensure that each layer is rich in small object information,to improve small object detection *** extensive experiments on challenging datasets such as Microsoft Common Objects inContext(MSCOCO)and Pattern Analysis Statistical Modelling and Computational Learning,Visual Object Classes(PASCAL VOC)demonstrate the validity of the *** results show a significant improvement in small object detection accuracy compared to state-of-theart detectors.

关键词： Small object detection two-layer attention module small object detail enhancement module feature pyramid network

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A Blockchain-Based Efficient Cross-Domain Authentication Scheme for Internet of Vehicles

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Computers, Materials & Continua 2024年第7期80卷 567-585页

作者： Feng Zhao Hongtao Ding Chunhai Li Zhaoyu Su Guoling Liang Changsong Yang Guangxi Engineering Research Center of Industrial Internet Security and Blockchain Guilin University of Electronic TechnologyGuilin541004China School of Information and Communication Guilin University of Electronic TechnologyGuilin541004China School of Computer Science and Information Security Guilin University of Electronic TechnologyGuilin541004China

The Internet of Vehicles(IoV)is extensively deployed in outdoor and open environments to effectively address traffic efficiency and safety issues by connecting vehicles to the ***,due to the open and variable nature of its network topology,vehicles frequently engage in cross-domain *** such processes,directly uploading sensitive information to roadside units for interaction may expose it to malicious tampering or interception by attackers,thus compromising the security of the cross-domain authentication ***,IoV imposes high real-time requirements,and existing cross-domain authentication schemes for IoV often encounter efficiency *** mitigate these challenges,we propose CAIoV,a blockchain-based efficient cross-domain authentication scheme for *** scheme comprehensively integrates technologies such as zero-knowledge proofs,smart contracts,and Merkle hash tree *** divides the cross-domain process into anonymous cross-domain authentication and safe cross-domain authentication phases to ensure efficiency while maintaining a balance between efficiency and ***,we evaluate the performance of *** results demonstrate that our proposed scheme reduces computational overhead by approximately 20%,communication overhead by around 10%,and storage overhead by nearly 30%.

关键词： Blockchain cross-domain authentication internet of vehicle zero-knowledge proof

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