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k-TEVS: A k-Times E-Voting Scheme on Blockchain With Supervision

IEEE Transactions on Dependable and Secure computing 2025年第3期22卷 2326-2337页

作者： Liu, Yang He, Debiao Luo, Min Wang, Lianhai Peng, Cong Wuhan University School of Cyber Science and Engineering Wuhan430072 China Shenzhen Institute of Information Technology Institute of Information Technology Shenzhen518172 China Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center Jinan250014 China Matrix Elements Technologies Shanghai Technology Innovation Centre of Distributed Privacy-Preserving Artificial Intelligence Shanghai200232 China Shandong Fundamental Research Center for Computer Science Shandong Provincial Key Laboratory of Industrial Network and Information System Security Jinan250014 China

Thee-vote is regarded as a waytoexpress the opinion that the voters ask for. Actually, the e-vote could be applied wildly likequestionnaire,***,thecoexistences of efficiency and security as well as transparency and privacy could be considered as building blocks in the e-vote system. The blockchain could provide a public access board to reduce the storagecostsforthefieldconsistedofthevotegroupmanager(GM) with its vote assistants (VA). Particularly the k-times anonymous authentication (k-TAA) could also be a practical approach to pre serve voters’ privacy and reduce the computation costs during the ***,thee-voteschemewithpurek-TAAstrategy could damage either the supervision of voting or the efficiency and consistency of authentication process. What’s more, the impacts of dishonest voters couldn’t be stopped until the vote end. To tackle these problems, we apply the accumulator technology to add or revoke the voters at any time and extend the framework of k-TAA with the update process for the e-vote on blockchain for supervision (k-TEVS). In our scheme, the voter updates his membership witness and proves the fact that he is still a valid member with respective VA under the latest accumulator value. What’s more, this witness update operation is not contained in the authentication process, which means that the authentication process is still constant and efficient. Moreover, our add or delete update process with signature of knowledge needs only one pairing operation. For the security, we prove that the relaxed anonymity still holds in the k-TEVS framework. Finally, We implement k TEVS scheme, the Emura’s work [1] and the Huang’s work [2] for comparison. Then we make time cost and communication cost experiments, which present the feasibility and practicality of this scheme. © 2004-2012 IEEE.

关键词： Efficiency

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SMDPG: Identifying Metabolite-Disease Associations via Optimized Negative Sampling and Sparse Graph Convolutional network

IEEE Transactions on Computational Biology and Bioinformatic...

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IEEE Transactions on Computational Biology and Bioinformatics 2025年第2期22卷 672-683页

作者： Yiran Huang Qiulong Pu Wei Lan Cuiyu Huang Cheng Zhong School of Computer Electronics and Information Guangxi University Nanning China Guangxi Universities Key Laboratory of Parallel and Distributed Computing and Guangxi Key Laboratory of Multimedia Communications and Network Technology Guangxi University Nanning China College of Chemistry Nankai University Tianjin China

Identifying disease-associated metabolites could provide critical clues for the diagnosis and treatment of diseases. Although computational approaches have been proposed to predict disease-associated metabolites by training models using positive and negative samples, few efforts have paid attention to optimize the reliability of negative samples, which could possibly improve the prediction accuracy of model. In this work, we propose a novel method called SMDPG to leverage optimized negative sampling and sparse graph convolutional network to predict metabolite-disease associations. In SMDPG, we first build a metabolite-disease bipartite graph based on less similar metabolites and diseases and propose a negative sampling method to select reliable negative metabolite-disease samples from the bipartite graph to reduce the effect of noisy samples. Then a homogeneous metabolite-disease pair graph is constructed based on the selected negative samples and known metabolite-disease associations. Further, an edge sparseness operation is designed to simplify the connection of the homogeneous graph. Finally, the simplified homogeneous graph is fed into the graph convolutional network to predict metabolite-disease associations. Experimental results show that SMDPG can more accurately predicts metabolite-disease associations as compared to the existing methods. Moreover, the study case demonstrates that SMDPG is an effective framework for identifying potential metabolite-disease associations.

关键词： Diseases Feature extraction Semantics Databases Reliability Graph convolutional networks Training Sparse matrices Predictive models Bipartite graph

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ATHENA: An In-vehicle CAN Intrusion Detection Framework Based on Physical Characteristics of Vehicle Systems

arXiv

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arXiv 2025年

作者： Wang, Kai Sun, Zhen Wang, Bailing Fan, Qilin Li, Ming Zhang, Hongke School of Computer Science and Technology Harbin Institute of Technology Weihai China Shandong Key Laboratory of Industrial Network Security China School of Big Data and Software Engineering Chongqing University Chongqing China Key Laboratory of Dependable Service Computing in Cyber Physical Society of Ministry of Education Chongqing University Chongqing China Jinan Key Laboratory of Distributed Databases Shandong Inspur Database Technology Co. Ltd Jinan China School of Electronic and Information Engineering Beijing Jiaotong University Beijing China

With the growing interconnection between In-Vehicle networks (IVNs) and external environments, intelligent vehicles are increasingly vulnerable to sophisticated external network attacks. This paper proposes ATHENA, the first IVN intrusion detection framework that adopts a vehicle-cloud integrated architecture to achieve better security performance for the resource-constrained vehicular environment. Specifically, in the cloud with sufficient resources, ATHENA uses the clustering method of multi-distribution mixture model combined with deep data mining technology to generate the raw Payload Rule Bank of IVN CAN messages, and then improves the rule quality with the help of exploitation on the first-principled physical knowledge of the vehicle system, after which the payload rules are periodically sent to the vehicle terminal. At the vehicle terminal, a simple LSTM component is used to generate the Time Rule Bank representing the long-term time series dependencies and the periodic characteristics of CAN messages, but not for any detection tasks as in traditional usage scenarios, where only the generated time rules are the candidates for further IVN intrusion detection tasks. Based on both the payload and time rules generated from cloud and vehicle terminal, ATHENA can achieve efficient intrusion detection capability by simple rule-base matching operations, rather than using complex black-box reasoning of resource-intensive neural network models, which is in fact only used for rule logic generation phase instead of the actual intrusion detection phase in our framework. Comparative experimental results on the ROAD dataset, which is current the most outstanding real-world in-vehicle CAN dataset covering new instances of sophisticated and stealthy masquerade attacks, demonstrate ATHENA significantly outperforms the state-of-the-art IVN intrusion detection methods in detecting complex attacks. We make the code available at https://***/wangkai-tech23/ATHENA. Copyright

关键词： network intrusion

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network Traffic Generation Based on Statistical Packet-Level Characteristics

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China Communications 2015年第S2期12卷 144-148页

作者： WANG Dongbin ZHUO Weihan ZHANG Junhui WU Kexin OUYANG Wen School of Software Engineering Beijing University of Posts and Telecommunications National Engineering Laboratory for Mobile Network Security (BUPT) Key Laboratory of Trustworthy Distributed Computing and Service (BUPT) Ministry of Education

network traffic is very important for testing network equipment, network services, and security products. A new method of generating traffic based on statistical packet-level characteristics is proposed. In every time unit, the generator determines the sent packets number, the type and size of every sent packet according to the statistical characteristics of the original traffic. Then every packet, in which the protocol headers of transport layer, network layer and ethernet layer are encapsulated, is sent via the responding network interface card in the time unit. The results in the experiment show that the correlation coefficients between the bandwidth, the packet number, packet size distribution, the fragment number of the generated network traffic and those of the original traffic are all more than 0.96. The generated traffic and original traffic are very highly related and similar.

关键词： network traffic generation packet-level traffic characteristics

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A New Pipeline for Knowledge Graph Reasoning Enhanced by Large Language Models Without Fine-Tuning

A New Pipeline for Knowledge Graph Reasoning Enhanced by Lar...

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2024 Conference on Empirical Methods in Natural Language Processing, EMNLP 2024

作者： Chen, Zhongwu Bai, Long Li, Zixuan Huang, Zhen Jin, Xiaolong Dou, Yong National Key Laboratory of Parallel and Distributed Computing National University of Defense Technology China CAS Key Laboratory of Network Data Science and Technology Institute of Computing Technology Chinese Academy of Sciences China

ISBN: (纸本)9798891761643

Conventional Knowledge Graph Reasoning (KGR) models learn the embeddings of KG components over the structure of KGs, but their performances are limited when the KGs are severely incomplete. Recent LLM-enhanced KGR models input KG structural information into LLMs. However, they require fine-tuning on open-source LLMs and are not applicable to closed-source LLMs. Therefore, in this paper, to leverage the knowledge in LLMs without fine-tuning to assist and enhance conventional KGR models, we propose a new three-stage pipeline, including knowledge alignment, KG reasoning and entity reranking. Specifically, in the alignment stage, we propose three strategies to align the knowledge in LLMs to the KG schema by explicitly associating unconnected nodes with semantic relations. Based on the enriched KGs, we train structure-aware KGR models to integrate aligned knowledge to original knowledge existing in KGs. In the reranking stage, after obtaining the results of KGR models, we rerank the top-scored entities with LLMs to recall correct answers further. Experiments show our pipeline can enhance the KGR performance in both incomplete and general situations. © 2024 Association for Computational Linguistics.

关键词： Semantics

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Fog computing for vehicular Ad-hoc networks: paradigms, scenarios, and issues

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The Journal of China Universities of Posts and Telecommunications 2016年第2期23卷 56-65,96页

作者： Kang Kai Wang Cong Luo Tao School of Software Engineering Beijing University of Posts and Telecommunications Key Laboratory of Trustworthy Distributed Computing and Service Beijing University of Posts Telecommunications School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing Key Laboratory of Network System Architecture and Convergence Beijing University of Posts Telecommunications

Vehicular Ad-hoc networks（VANETs） are kinds of mobile Ad-hoc networks（MANETs）, which consist of mobile vehicles with on-board units（OBUs） and roadside units（RSUs）. With the rapid development of computation and communication technologies, peripheral or incremental changes in VANETs evolve into a revolution in process. Cloud computing as a solution has been deployed to satisfy vehicles in VANETs which are expected to require resources（such as computing, storage and networking）. Recently, with special requirements of mobility, location awareness, and low latency, there has been growing interest in research into the role of fog computing in VANETs. The merging of fog computing with VANETs opens an area of possibilities for applications and services on the edge of the cloud computing. Fog computing deploys highly virtualized computing and communication facilities at the proximity of mobile vehicles in VANET. Mobile vehicles in VANET can also demand services of low-latency and short-distance local connections via fog computing. This paper presents the current state of the research and future perspectives of fog computing in VANETs. Moreover, we discuss the characteristics of fog computing and services based on fog computing platform provided for VANETs. In this paper, some opportunities for challenges and issues are mentioned, related techniques that need to be considered have been discussed in the context of fog computing in VANETs. Finally, we discuss about research directions of potential future work for fog computing in VANETs. Within this article, readers can have a more thorough understanding of fog computing for VANETs and the trends in this domain.

关键词： VANET fog computing cloud computing application vehicular cloud computing

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Predicting cement compressive strength using double-layer multi-expression programming

Predicting cement compressive strength using double-layer mu...

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4th International Conference on Computational and Information Sciences, ICCIS 2012

作者： Zhang, Qingke Yang, Bo Wang, Lin Zhu, Fuxiang Shandong Province Key Laboratory of Network Based Intelligent Computing University of Jinan Jinan China Computer Networks and Distributed Systems Laboratory Beijing Institute Technology Beijing China

ISBN: (纸本)9780769547893

This paper presents a novel algorithm named Double-layer Multi-expression Programming (DMEP). Then DMEP model is applied to the prediction of 28-day Portland cement compressive strength. We compare DMEP model with other four soft computing models, namely Multi-Expression Programming model (MEP), Gene Expression Programming model (GEP), Neural networks model (NN) and Fuzzy logic model (FL) on 28-day cement strength prediction. The experiment results show that DMEP model has a lower rate in RMSE and MAE, and the prediction average percentage error of the cement strength data using DMEP model is reduced to 2.18%, which is lower than other four models. The results obtained from the computational tests demonstrate that DMEP is a promising technique for the prediction of cement strength. © 2012 IEEE.

关键词： Soft computing

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Rigorous punishment promotes cooperation in prisoners’ dilemma game 7th

Rigorous punishment promotes cooperation in prisoners’ dile...

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7th International ICST Conference on Bio-Inspired Models of network, Information, and computing Systems, BIONETICS 2012

作者： Ling, Yun Liu, Jian Zhu, Ping Wei, Guiyi Networking and Distributed Computing Laboratory Zhejiang Gongshang University 18 Xuezheng St Xiasha Higher Education Park Hangzhou China Wasu Media Network Co. Ltd Hangzhou China

ISBN: (纸本)9783319069432

In this paper, we introduce a rigorous punishment mechanism into the prisoners’ dilemma game. In our model, the punisher punishes the defector with fine β at the cost of γ. Monte-Carlo simulations show the evolution of system is jointly affected by β, γ and system’s initial state. We find that when γ is small, the system can evolve into two steady states, i. e., coexisting of cooperators and defectors, and pure punishers. When γ is large, the system can evolve into the only steady state, i. e., coexisting of cooperators and defectors. However, in the middle value of γ, the system can evolve into three steady states, i. e., coexisting of cooperators and defectors, a rock-paper-scissors type of cyclic dominance, and pure cooperators. These results are explained by average total payoff, transition possibility and evolutionary snapshot. We also find the heterogeneity of population distribution can affect cooperation as well. © Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2014.

关键词： Monte Carlo methods

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Threshold signature scheme based on non-interactive Diffie-Hellman signature

Threshold signature scheme based on non-interactive Diffie-H...

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1st International Conference on networking and distributed computing, ICNDC 2010

作者： Wang, Xiuqun Huang, Lican Key Laboratory for Information System Security Ministry of Education Tsinghua University and Beijing Certification Authority Beijing China Institute of Network and Distributed Computing Zhejiang Sci-Tech University Hangzhou China

ISBN: (纸本)9780769542072

We present a threshold signature based on non-interactive Diffie-Hellman signature. It works in asynchronous communication system and can tolerate Byzantine faults with optimal resiliencen ≥ 3t + 1, where n is the number of the participants and t is the number of the fault participants. The security of this scheme bases on discrete logarithm intractability assumption. We give the security analysis of our proposed threshold signature scheme. © 2010 IEEE.

关键词： Authentication

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Modeling and design of notarial system supporting secure transactions in electronic commerce based on the Internet

Modeling and design of notarial system supporting secure tra...

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International Conference on Information networking

作者： Sung-Woo Tak Ryu-Seok Bae Jong-Moon Son Distributed Computing Laboratory Network Computing Department Systems Engineering Research Institute Daejeon South Korea

ISBN: (纸本)0818672250

In this paper, we analyze notarial requirements in the electronic commerce based on the Internet and design the notarial system to support secure transactions, which provides the notarial service for assurance of transactions between customer and merchant running shopping mall connected to the Internet. We suggest that electronic commerce should offer not only authentication service but also notarial service in order to provide secure transactions over the Internet.

关键词： Electronic commerce Authentication Web and internet services Access control IP networks distributed computing Cryptography Transaction databases Protocols Intelligent networks

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