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21st International Computer Conference on Wavelet Active Media Technology and Information Processing, ICCWAMTIP 2024

作者： Zhou, Zeyu Huang, Yuanyuan Wang, Yongli Li, Siyu Lu, Jiazhong He, Peilin Chengdu University of Information Technology Advanced Cryptography and System Security Key Laboratory of Sichuan Province Chengdu610225 China Dazhou Key Laboratory Government Data Security Dazhou635000 China University of Pittsburgh Department of Informatics and Networked Systems Pittsburgh15260 United States

ISBN: (纸本)9798331519254

Graph Neural Networks (GNNs) have emerged as powerful tools across diverse applications, including social networks, bioinformatics, and recommendation systems. However, their susceptibility to adversarial attacks, particularly targeted attacks, poses a significant challenge. Targeted attacks exploit the message-passing mechanism of GNNs to induce severe performance degradation, even with minimal perturbations. Inspired by the self-repair and adaptive behaviors of spider webs, this paper introduces SpiderWeb Protector, a biomimetic defense strategy designed to enhance GNN robustness. The proposed method integrates three core components: Community-Centric Graph Update, which selectively reinforces key graph structures;Topology Feature Merging, which improves feature representation by incorporating structural insights;and Edge Pruning, which dynamically removes adversarial connections. Comprehensive experiments on three datasets (Cora, Citeseer and Cora_ml) and two GNN models (GCN and GIN) demonstrate the superior performance of SpiderWeb Protector against both direct and influence-targeted attacks, achieving state-of-the-art results. © 2024 IEEE.

关键词： Graph neural networks

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VFLF: A verifiable federated learning framework against malicious aggregators in Industrial Internet of Things

VFLF: A verifiable federated learning framework against mali...

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作者： Zhou, Zhou Tian, Youliang Peng, Changgen Yang, Nan Long, Shigong State Key Laboratory of Public Big Data College of Computer Science and Technology Guizhou University Guizhou Guiyang China Institute of Cryptography and Data Security Guizhou University Guizhou Guiyang China

As an important approach to overcome data silos and privacy concerns in deep learning, federated learning, which can jointly train the global model and keep data local, has shown remarkable performance in a range of industrial applications. However, federated learning still suffers from the problem that shared gradients may be subject to tampering, inference functions, and falsification. To address this issue, we propose a verifiable federated learning framework to deal with malicious aggregators. Initially, we propose a reputation calculation mechanism to solve the problem of selecting a reliable aggregator based on a multiweight subjective logic model. Furthermore, we design a verifiable federated learning scheme to ensure data confidentiality, integrity, and verifiability, as well as support the client's dynamic withdrawal. security analyses indicate that our framework is secure against malicious adversaries. Furthermore, experimental results on real datasets show that our verifiable federated learning has high accuracy and feasible efficiency. © 2022 John Wiley & Sons, Ltd.

关键词： Internet of things

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Sharing of Encrypted Lock Keys in the Blockchain-Based Renting House System from Time- and Identity-Based Proxy Reencryption

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China Communications 2022年第5期19卷 164-177页

作者： Zhiwei Wang Liping Qian Danwei Chen Guozi sun School of Computer Nanjing University of Posts and TelecommunicationsNanjing 210023China Jiangsu Key Laboratory of Big Data Security and Intelligent Processing Nanjing 210023China Guangxi Key Laboratory of Cryptography and Information Security Department of Computer SciencesGuilin University of Electronic TechnologyGuilin 541004China

To design an efficient protocol for sharing the encrypted lock keys in the renting house system,we introduce a new notion called time-and identitybased proxy reencryption(TIPRE)and the blockchain *** CPA secure TIPRE scheme is constructed from Green et al.’s identity-based proxy reencryption scheme by adding the time *** every time period,a time stamp authority generates a public key embedded with the current time stamp for each *** our protocol for the renting house system,the TIPRE scheme is the primary building block,and the blockchain platform serves instead of a trusted third party,such as a real estate agency between landlords and *** TIPRE scheme allows the landlord to change the lock key at each time period for *** blockchain platform allows the landlords and tenants to directly interact,and all of the interactions are recorded in the blockchain database to provide the desired security requirements,such as nonrepudiation and ***,we provide the secure analysis of our protocol and test its performance by implementing it in the MacBook Pro and the Intel Edison development platforms.

关键词： identity-based proxy reencryption time stamp renting houses system blockchain

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Finite groups with the most Chermak-Delgado measures of subgroups

arXiv

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arXiv 2025年

作者： Liu, Guojie Qu, Haipeng An, Lijian Shanxi Key Laboratory of Cryptography and Data Security Shanxi Normal University Shanxi Taiyuan030031 China

Let G be a finite group and H ≤ G. The Chermak-Delgado measure of H is defined as the number |H| · |CG(H)|. In this paper, we identify finite groups that exhibit the maximum number of Chermak-Delgado measures un...

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Resisting Membership Inference Attacks by Dynamically Adjusting Loss Targets

Resisting Membership Inference Attacks by Dynamically Adjust...

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2023 International Conference on Networking and Network Applications, NaNA 2023

作者： Ma, Xihua Tian, Youliang Ding, Zehua Guizhou University State Key Laboratory of Public Big Data Guiyang550025 China College of Computer Science and Technology Guizhou University Guiyang550025 China Institute of Cryptography and Data Security Guizhou University Guiyang550025 China

ISBN: (纸本)9798350327380

Machine learning (ML) models are susceptible to membership inference attacks (MIAs), which aim to infer whether a particular sample was involved in model training. Previous research suggests that the difference in loss distribution between member and non-member sample is an essential factor of MIAs. In the latest mitigation strategies to reduce the loss distribution discrepancy, the model owner must manually set a loss target for the training task. However, this can be challenging due to differences in datasets and model structures. We propose a new mitigation strategy based on existing studies, which can dynamically adjust the loss target during the training process according to the model structure and dataset characteristics, to achieve a reduced loss gap. We extensively evaluated our strategy in white-box and black-box environments, respectively. Our experimental results show that our approach avoids the problem of setting loss targets and even improves the model's resistance to attacks in most cases. Specifically, the accuracy of the attacks is reduced by an average of 4.92% and 11.3% in the black-box and white-box environments, respectively. © 2023 IEEE.

关键词： Machine learning

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A circuit area optimization of MK-3 S-box

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Cybersecurity 2025年第1期8卷 61-71页

作者： Yanjun Li Weiguo Zhang Yiping Lin Jian Zou Jian Liu Information Industry Information Security Evaluation Center The 15th Research Institute of China Electronic Technology Group CorporationBeijing 100083China Henan Key Laboratory of Network Cryptography Technology Zhengzhou 450001China Beijing Electronic Science and Technology Institute No.7 Fufeng RoadFengtai DistricBeijing 100083China College of Computer and Data Science Fuzhou UniversityFuzhou 350108China

In MILCOM 2015,Kelly et *** the authentication encryption algorithm MK-3,which applied the 16-bit *** paper aims to implement the 16-bit S-box with less circuit ***,we classifed the irreducible polynomials over F_(2n)into three *** we compared the logic gates required for multiplication over the fnite feld constructed by the three types of irreducible *** to the comparison result,we constructed the composite felds, F_((2^(4))^(2))and F_((2^(8))^(2)).Based on the isomorphism of fnite felds,the operations over F_(2)^(16)can be conducted over F_((2^(8))^(2)).Similarly,elements over F28 can be mapped to the corresponding elements over F_((2^(4)))^(2).Next,the SAT solver was used to optimize the operations over smaller feld F_(2)^(4).At last,the architecture of the optimized MK-3 S-box was worked *** with the implementation proposed by the original designer,the circuit area of the MK-3 S-box in this paper is reduced by at least 55.9%.

关键词： irreducible operations optimization

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An Effective security Comparison Protocol in Cloud Computing

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Computers, Materials & Continua 2023年第6期75卷 5141-5158页

作者： Yuling Chen Junhong Tao Tao Li Jiangyuan Cai Xiaojun Ren State Key Laboratory of Public Big Data College of Computer Science and TechnologyGuizhou UniversityGuiyang550000China Guangxi Key Laboratory of Cryptography and Information Security Guilin University of Electronic TechnologyGuilin550000China POWERCHINA Guizhou Electric Power Engineering Co. Ltd.Guiyang550000China Blockchain Laboratory of Agricultural Vegetables Weifang University of Science and TechnologyWeifang261000China

With the development of cloud computing technology,more and more data owners upload their local data to the public cloud server for storage and *** this can save customers’operating costs,it also poses privacy and security *** challenges can be solved using secure multi-party computation(SMPC),but this still exposes more security *** cloud computing using SMPC,clients need to process their data and submit the processed data to the cloud server,which then performs the calculation and returns the results to each *** client and server must be *** there is cooperation or dishonest behavior between clients,some clients may profit from it or even disclose the private data of other *** paper proposes the SMPC based on a Partially-Homomorphic Encryption(PHE)scheme in which an addition homomorphic encryption algorithm with a lower computational cost is used to ensure data comparability and Zero-Knowledge Proof(ZKP)is used to limit the client’s malicious *** addition,the introduction of Oblivious Transfer(OT)technology also ensures that the semi-honest cloud server knows nothing about private data,so that the cloud server of this scheme can calculate the correct data in the case of malicious participant models and safely return the calculation results to each ***,the security analysis shows that the scheme not only ensures the privacy of participants,but also ensures the fairness of the comparison protocol data.

关键词： Secure comparison protocols zero-knowledge proof homomorphic encryption cloud computing

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An Efficient Blockchain-Based Certificateless Anonymous Authentication Scheme for VANETs

An Efficient Blockchain-Based Certificateless Anonymous Auth...

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2023 International Conference on Networking and Network Applications, NaNA 2023

作者： Bi, Changbing Tian, Youliang Li, Ta Wu, Shihong Zhou, Hua Guizhou University State Key Laboratory of Public Big Data Guiyang550025 China College of Computer Science and Technology Guizhou University Guiyang550025 China Guizhou University Guizhou Province Key Laboratory of Cryptography and Block Chain Technology Guiyang550025 China Institute of Cryptography & Data Security Guizhou University Guiyang550025 China College of Big Data and Information Engineering Guizhou University Guiyang550025 China

ISBN: (纸本)9798350327380

Vehicle ad-hoc networks (VANETs) play a critical role in providing security and privacy protection for intelligent transportation systems. However, the limited network bandwidth and computing capacity within VANETs have resulted in existing authentication schemes having excessive computational overhead, which cannot meet the low-latency communication requirements of VANETs. To tackle these problems, we propose an efficient blockchain-based certificateless anonymous authentication scheme for VANETs. Firstly, we propose a novel signature scheme without bilinear pairing to reduce the computational overhead in VANETs. Secondly, we utilize blockchain to facilitate trusted information sharing. Thirdly, we provide privacy-preserving through the use of anonymous keys, and enable tracing of vehicle identities in the event of malicious behavior. Finally, security analysis and simulation experiments demonstrate that our proposed scheme has lower communication and computational overhead, while satisfying various security requirements for VANETs, such as anonymity, unlinkability, and traceability. © 2023 IEEE.

关键词： Authentication

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A C/C++ Smart Contract Vulnerability Detection Method Based on Intermediate Value Transformation 4

A C/C++ Smart Contract Vulnerability Detection Method Based ...

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4th International Conference on Blockchain Technology and Information security, ICBCTIS 2024

作者： Li, Yushu Xing, Ying Lu, Siqi Deng, Xiang Pan, Heng Si, Xueming Zhongyuan University of Technology Cyber Security Academy Zhengzhou China Software College Zhongyuan University of Technology Zhengzhou China Henan Key Laboratory of Network Cryptography Zhengzhou China College of Spatiotemporal Big Data Industry Henan Vocational College of Surveying and Mapping Zhengzhou China

ISBN: (纸本)9798331528324

Smart contracts have brought new developments to Blockchain technology, quickly finding widespread application in finance, law, and business sectors upon their emergence. However, security vulnerabilities in smart contracts have limited their growth. The existing methods for detecting vulnerabilities in smart contracts primarily focus on Ethereum's Solidity, lacking of vulnerability detection tools based on other smart contract languages such as C/C++. Therefore, this paper investigates the current state of vulnerability detection research for smart contract languages other than Ethereum's Solidity and proposes a vulnerability detection method for C/C++ smart contracts based on intermediate value transformation. This method combines Clang technology with the symbolic execution tool KLEE[l], utilizing the Intermediate Representation (IR) from LLVM (Low Level Virtual Machine) for research, andproduces a detection method capable of identifying eight types of code level vulnerabilities. Finally, it summarizes the current shortcomings of smart contract vulnerability detection methods and future research directions. © 2024 IEEE.

关键词： Smart contract

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Understanding User Passwords through Parsing Tree

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IEEE Transactions on Dependable and Secure Computing 2025年

作者： Wang, Ding Shan, Xuan Wu, Yuxuan Jia, Chunfu Nankai University College of Cryptology and Cyber Science Tianjin300350 China Ministry of Education of China Henan Key Laboratory of Network Cryptography Key Laboratory of Cyberspace Security China Nankai University Tianjin Key Laboratory of Network and Data Security Technology Tianjin300350 China

Passwords are today's dominant form of authentication, and password guessing is the most effective method for evaluating password strength. Most password guessing models (e.g., PCFG, Markov, and RFGuess) regard passwords as sequences composed of basic units (i.e., characters/segments), with the information flow being unidirectional (i.e., predicting the next unit based on the preceding units). However, modeling passwords in a single direction fails to capture users' password creation behavior that is actually impacted by the full password context. Through an in-depth analysis of real-world passwords, we reveal that users often create passwords around a central keyword, like common words, names, or dates, and then embellish them with numbers or symbols. Based on this observation, we, for the first time, attempt to parse passwords as trees. Unlike existing sequence models, trees can reveal the semantic connections within passwords and the logical thought processes users follow when creating passwords. For instance, in the password iloveyou, the basic units i and you are semantically dependent on the predicate love, forming a natural tree structure. We propose a trawling guessing model called PassTree and a targeted guessing model based on personally identifiable information (PII), named PassTree-PII. Our extensive experiments demonstrate the effectiveness of our models: (1) PassTree outperforms its leading counterparts by 0.38%-2.51% when guessing numbers are below 107 (2) PassTree-PII achieves a cracking rate comparable to the state-of-the-art RFGuess-PII proposed in USENIX security'23, but operates significantly more efficiently, using only 0.87% of the memory and being 16.60 times faster. Our work provides a new perspective on understanding user passwords and demonstrates a feasible technical route of applying tree structures to password guessing. © 2025 IEEE.

关键词： Markov processes

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