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

IEEE Transactions on Dependable and Secure Computing 2024年

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

The e-vote is regarded as a way to express the opinion that the voters ask for. Actually, the e-vote could be applied wildly like questionnaire, survey and feedback. Moreover, the coexistences 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 storage costs for the field consisted of the vote group manager (GM) with its vote assistants (VA). Particularly the k-times anonymous authentication (k-TAA) could also be a practical approach to preserve voters’ privacy and reduce the computation costs during the vote process. However, the e-vote scheme with pure k-TAA strategy 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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Robust State Estimator Based on Hyperbolic Cosine Function

Robust State Estimator Based on Hyperbolic Cosine Function

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IEEE Power and Energy Society General Meeting

作者： Yanbo Chen Jin Ma Ji Zhang State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources and Beijing Engineering Research Center of Energy Electric Power Information Security School of Electrical & Electronic Engineering North China Electric Power Univ e School of Electrical and Information Engineering University of Sydney Economic & Technology Research Institute of Hubei Electric Power Company

In this paper, a novel robust state estimator based on hyperbolic cosine function (COSH) is proposed considering the uncertainty in the measurements. Simulations based on the IEEE benchmark systems demonstrate that th... 详细信息

ISBN: (纸本)9781538622131;9781538622124

关键词： Robustness Measurement uncertainty Power systems Linear programming Computational efficiency Uncertainty State estimation

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Quantum reversible circuits for multiplicative inverse

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EPJ Quantum Technology 2022年第1期9卷 1-17页

作者： Luo, Qing-bin Yang, Guo-wu Li, Xiao-yu Li, Qiang Department of Computer Science and Technology School of Information Engineering Hubei Minzu University Enshi China School of Information and Software Engineering University of Electronic Science and Technology of China Chengdu China Big data research Center & School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu China Advanced Cryptography and System Security Key Laboratory of Sichuan Province Chengdu University of Information Technology Chengdu China

The synthesis of quantum circuits for multiplicative inverse over $\operatorname{GF}(2^{8})$ are discussed in this paper. We first convert the multiplicative inverse operation in $\operatorname{GF}(2^{8})$ to arithmetic operations in the composite field $\operatorname{GF}((2^{4})^{2})$ , and then discuss the expressions of the square calculation, the inversion calculation and the multiplication calculation separately in the finite field $\operatorname{GF}(2^{4})$ , where the expressions of multiplication calculation in $\operatorname{GF}(2^{4})$ are given directly in $\operatorname{GF}(2^{4})$ and given through being transformed into the composite field $\operatorname{GF}((2^{2})^{2})$ . Then the quantum circuits of these calculations are realized one by one. Finally, two quantum circuits for multiplicative inverse over $\operatorname{GF}(2^{8})$ are synthesized. They both use 21 qubits, the first quantum circuit uses 55 Toffoli gates and 107 CNOT gates and the second one uses 37 Toffoli gates and 209 CNOT gates. As an example of the application of multiplication inverse, we apply these quantum circuits to the implementations of the S-box quantum circuit of the AES cryptographic algorithm. Two quantum circuits for implementing the S-box of the AES cryptographic algorithm are presented. The first quantum circuit uses 21 qubits, 55 Toffoli gates, 131 CNOT gates and 4 NOT gates and the second one uses 21 qubits, 37 Toffoli gates, 233 CNOT gates and 4 NOT gates. Through the evaluation of quantum cost, the two quantum circuits of the S-box of AES cryptographic algorithm use less quantum resources than the existing schemes.

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Active power regulation control of grid-tied system for transient stability enhancement

Active power regulation control of grid-tied system for tran...

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12th International Conference on Renewable Power Generation (RPG 2023)

作者： Y. Ling M. Huang X. Fu X. Zha H. Zhang J. Deng Hubei Key Laboratory of Power Equipment & System Security for Integrated Energy School of Electrical Engineering and Automation Wuhan University Wuhan People's Republic of China China Electric Power Research Institute Nanjing People's Republic of China Power Research Institute of State Grid Shaanxi Electric Power Company Limited Xi'an People's Republic of China

With the high penetration of renewable energy sources, the grid stiffness goes weak. When the fault occurs, the system trends to be unstable in the weak grid. To enhance the transient stability of the system, it is vital to design the new control. Therefore, the paper builds the state-space model of the system with considering the DC voltage loop. The influence of the short-circuit ratio on the system is analysed. An active power regulation control is proposed to enhance the transient stability of the system. The control can regulate the active power with frequency feedback. The state-space model of the system with the proposed control is built. The impact of parameters on the system stability is analysed. The proposed control makes the system operate in the weaker grid and improve the transient stability of the system under fault. Finally, the simulation and experiment results validate the effectiveness of the proposed control.

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Correction to: A Tree-type Multiparty Quantum key Agreement Protocol Against Collusive Attacks

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International Journal of Theoretical Physics 2023年第5期62卷 1-1页

作者： Yang, Hao Lu, Songfeng Zhu, Jianxin Wu, Junjun Zhou, Qing Li, Tong Hubei Key Laboratory of Distributed System Security Hubei Engineering Research Center On Big Data Security School of Cyber Science and Engineering Huazhong University of Science and Technology Wuhan China Shenzhen Huazhong University of Science and Technology Research Institute Shenzhen China College of Management Shenzhen University Shenzhen China

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Secure and Privacy-preserving Data-sharing Framework based on Blockchain Technology for Al-Najaf/Iraq Oil Refinery

Secure and Privacy-preserving Data-sharing Framework based o...

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Symposia and Workshops on Ubiquitous, Autonomic and Trusted Computing, UIC-ATC

作者： Samir M. Umran SongFeng Lu Zaid Ameen Abduljabbar Zhi Lu Bingyan Feng Lu Zheng Hubei Key Laboratory of Distributed System Security Hubei Engineering Research Center on Big Data Security School of Cyber Science and Engineering Huazhong University of Science and Technology Wuhan China Ministry of Industry and Minerals Iraqi Cement State Company Baghdad Iraq Shenzhen Huazhong University of Science and Technology Research Institute Shenzhen China College of Education for Pure Sciences University of Basrah Technical Computer Engineering Department Al-Kunooze University College Basrah Iraq School of Cyber Science and Engineering Huazhong University of Science and Technology Wuhan China Wuhan Huazhong Numerical Control Co. Ltd Industrial Internet Research Institute Wuhan China College of Computer Science South-Central University for Nationalities Wuhan China

The Industrial Internet of Things or Industry 4.0 efficiently enhances the manufacturing process in terms of raising productivity, system performance, cost reduction, and building large-scale systems. It enables the connection of numerous heterogeneous devices and sensors into the internet network through the utilization of revolutionary techniques that transfer the manufacturing paradigm to intelligent processes. The traditional industrial internet of things adopts centralized architectures and complex encryption algorithms that suffer from several cyber-security threats and lead to data leakage, privacy disclosure, and high computational and communicational costs. In our work, we proposed a decentralized, efficient, low-power, scalable, secure, privacy-preserving, and trusting architecture based on a private blockchain network/smart contract and interplanetary file system technology for the Al-NajafyIraq oil refinery factory. That enables autonomous working and provides a high level of security authentication and privacy preservation, P2P communication, remote access, immutability and information backtracking. Traditional blockchain technology has storage limitation issues, most recent works adopted external servers or the cloud for storage purposes. Our proposed scheme addresses the limitations of blockchain data storage by adopting an interplanetary file system (IPFS) network; provides an efficient data encryption mechanism at the perceptual layer by adopting a lightweight encryption algorithm, high-performance, and ultra-low-power consumption ARM Cortex-M microcontroller. In addition, our architecture succeeds in merging blockchain technology, IoTs, and an IPFS with the oil refinery as an industrial application area. Moreover, it provides an efficient framework that resists common cyber-security attacks and realizes cyber-security requirements represented by data availability, integrity, and confidentiality.

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Simulation of Nuclear Reactor Accident Scenarios using Physics-Informed Neural Networks and Transfer-Learning

Simulation of Nuclear Reactor Accident Scenarios using Physi...

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Electronic Information Engineering and Computer Science (EIECS), 2021 International Conference on

作者： Yang Yu Yufei Xie Wenlin Wang Guohua Wu Haitao Lan Enbo Lin Ping An Zibin Sun Haichuan Zhang Yixian Wu National Key Laboratory of Parallel and Distributed Computing National University of Defense Technology Changsha China Science and Technology on Reactor System Design Technology Laboratory Nuclear Power Institute of China Chengdu China School of Automation Wuhan University of Technology Wuhan China Sino-German College of Intelligent Manufacturing Shenzhen Technology University Shenzhen China Institute of Automotive Engineers Hubei University of Automotive Technology Shiyan China Nuclear Power Institute of China Chengdu China

ISBN: (数字)9798331531409

ISBN: (纸本)9798331531416

In a Loss of Coolant Accident (LOCA), reactor core temperatures can rise rapidly, leading to potential fuel damage and radioactive material release. This research presents a groundbreaking method that combines the power of Monte Carlo Sampling and Physics-Informed Neural Networks (PINNs) to simulate and effectively address the challenging Loss of Coolant Accidents (LOCA) in nuclear reactors. In the event of a LOCA, reactor core temperatures can soar rapidly, posing a significant threat to fuel integrity and potentially leading to the release of radioactive materials. By leveraging the strengths of both Monte Carlo Sampling and PINNs, this approach aims to provide a comprehensive and accurate simulation framework for assessing and mitigating the consequences of such accidents. The method yields high prediction accuracy (MAE: 0.033, RMSE: 0.098, R2: 0.814) and demonstrates robustness through transfer learning, maintaining strong performance (MAE: 0.064, RMSE: 0.163, R 2 : 0.735).

关键词： Radioactive materials Accuracy Monte Carlo methods Transfer learning Neural networks Robustness Data models Fuels Inductors Accidents

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Unbalanced incomplete multi-view clustering via the scheme of view evolution: Weak views are meat;strong views do eat

arXiv

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arXiv 2020年

作者： Fang, Xiang Hu, Yuchong Zhou, Pan Wu, Dapeng Oliver The School of Computer Science and Technology Key Laboratory of Information Storage System Ministry of Education of China Huazhong University of Science and Technology Wuhan430074 China The Hubei Engineering Research Center on Big Data Security School of Cyber Science and Engineering Huazhong University of Science and Technology Wuhan430074 China The Department of Electrical and Computer Engineering University of Florida GainesvilleFL32611 United States

Incomplete multi-view clustering is an important technique to deal with real-world incomplete multi-view data. Previous methods assume that all views have the same incompleteness, i.e., balanced incompleteness. However, different views often have distinct incompleteness, i.e., unbalanced incompleteness, which results in strong views (low-incompleteness views) and weak views (high-incompleteness views). The unbalanced incompleteness prevents us from directly using previous methods. In this paper, inspired by the effective biological evolution theory, we design the novel scheme of view evolution to cluster strong and weak views. Moreover, we propose an Unbalanced Incomplete Multi-view Clustering method (UIMC), which is the first effective method based on view evolution for unbalanced incomplete multi-view clustering. Compared with previous methods, UIMC has two unique advantages: 1) it proposes weighted multi-view subspace clustering to integrate unbalanced incomplete views, which effectively solves the unbalanced incomplete multi-view clustering problem;2) it designs the low-rank representation to recover the data, which diminishes the impact of the incompleteness and noises. Extensive experimental results demonstrate that UIMC improves the clustering performance by up to 40% on three evaluation metrics over other state-of-the-art methods. We provide codes for all of our experiments in https://***/ZeusDavide/TETCI_UIMC. Copyright © 2020, The Authors. All rights reserved.

关键词： Clustering algorithms

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Contrastive Learning for Robust Android Malware Familial Classification

arXiv

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arXiv 2021年

作者： Wu, Yueming Dou, Shihan Zou, Deqing Yang, Wei Qiang, Weizhong Jin, Hai National Engineering Research Center for Big Data Technology and System Services Computing Technology and System Lab Hubei Engineering Research Center on Big Data Security School of Cyber Science and Engineering Huazhong University of Science and Technology Wuhan430074 China Shanghai Key Laboratory of Intelligent Information Processing School of Computer Science Fudan University Shanghai200433 China University of Texas at Dallas Dallas United States National Engineering Research Center for Big Data Technology and System Services Computing Technology and System Lab Cluster and Grid Computing Lab School of Computer Science and Technology Huazhong University of Science and Technology Wuhan430074 China

Due to its open-source nature, Android operating system has been the main target of attackers to exploit. Malware creators always perform different code obfuscations on their apps to hide malicious activities. Features extracted from these obfuscated samples through program analysis contain many useless and disguised features, which leads to many false negatives. To address the issue, in this paper, we demonstrate that obfuscation-resilient malware family analysis can be achieved through contrastive learning. The key insight behind our analysis is that contrastive learning can be used to reduce the difference introduced by obfuscation while amplifying the difference between malware and other types of malware. Based on the proposed analysis, we design a system that can achieve robust and interpretable classification of Android malware. To achieve robust classification, we perform contrastive learning on malware samples to learn an encoder that can automatically extract robust features from malware samples. To achieve interpretable classification, we transform the function call graph of a sample into an image by centrality analysis. Then the corresponding heatmaps can be obtained by visualization techniques. These heatmaps can help users understand why the malware is classified as this family. We implement IFDroid and perform extensive evaluations on two datasets. Experimental results show that IFDroid is superior to state-of-the-art Android malware familial classification systems. Moreover, IFDroid is capable of maintaining a 98.4% F1 on classifying 69,421 obfuscated malware samples. © 2021, CC0.

关键词： Android (operating system)

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Simulation of Propagation Pattern of Partial Discharge’s Ultrasonic Signal in Oil-Immersed Transformer

Simulation of Propagation Pattern of Partial Discharge’s Ul...

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Advanced Electrical Equipment and Reliable Operation (AEERO), International Conference on

作者： Guochao Qian Qingjun Peng Zhongchang Wang Yuepei Zou Jiali Lei Zhixian Zhang Kejie Wu Yuxuan Song Electric Power Research Institute of Yunnan Power Grid Corporation Kunming Yunnan China Three Gorges Water Conservancy Project Cascade Dispatching Communication Center Yichang Hubei China Kunming Power Supply Bureau of Yunnan Power Grid Co. Ltd Kunming Yunnan China State Key Laboratory of Power Transmission Equipment & System Security and New Technology Chongqing University Chongqing China

ISBN: (纸本)9781665402651

The breakdown of insulation caused by partial discharge inside the transformer is an important cause of transformer failure. Ultrasonic detection is a common method for detecting and positioning partial discharge in transformers. According to the needs of rationally arranging ultrasonic sensors and optimizing the positioning algorithm, this paper carries out a simulation analysis of the propagation pattern of partial discharge ultrasonic signals inside the oil-immersed transformer. Based on the finite element simulation software, an oil-immersed transformer model was built, and different geometric structures and material parameters were designed for the transformer’s box, iron core, winding, and oil. The propagation mode of the partial discharge occurring in the oil passage between the high and low voltage windings, the high voltage winding and the outside of the winding in the transformer is analyzed, and the attenuation of the partial discharge ultrasonic signal in the transformer by the winding is studied. This article provides a certain reference for the layout and optimization of built-in ultrasonic sensors in oil-immersed power transformers.

关键词： Partial discharges Optical fiber sensors Oils Windings Oil insulation Acoustics Software

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