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2020 2nd International Conference on Computer Modeling, Simulation and Algorithm, CMSA 2020

作者： He, Jindong Wu, Dan Zhao, Zhichao Guo, Qian State Grid Fujian Electric Power Research Institute Fuzhou China Global Energy Interconnection Research Institute Co. Ltd State Grid Key Laboratory of Information and Network Security Nanjing China

The whole process security of power information system is the key to make power grid operation safe and stable. Firstly, the concept and characteristics of whole life cycle management (WLCM) are summarized by this paper systematically. Secondly, the power network security architecture based on full life cycle security management is constructed, which is designed to protect the cyber security of power grid from three aspects: control flow, technical support system and mechanism guarantee system. Thirdly, the cyber security's management and control flow of power grid, the technical support system of power grid cyber security (PGIS) and the mechanism guarantee system based on life cycle management are proposed. And the control flow, technical support and guarantee mechanism were designed in detail. Finally, the method proposed in this paper is carried out in a provincial power-grid company. The results show that this method can significantly reduce the power network security risk and improve the power grid network security level, which is of great significance to the operation safety of the power grid and has strong engineering application value. © Published under licence by IOP Publishing Ltd.

关键词： network security

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Trusted Auditing of Data Operation Behaviors in Cloud based on Blockchain and TEE 21

Trusted Auditing of Data Operation Behaviors in Cloud based ...

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21st IEEE International Symposium on Parallel and Distributed Processing with Applications, 13th IEEE International Conference on Big Data and Cloud computing, 16th IEEE International Conference on Social computing and networking and 13th International Conference on Sustainable computing and Communications, ISPA/BDCloud/SocialCom/SustainCom 2023

作者： Xu, Shujiang Wang, Fansheng Wang, Lianhai Mihaljevic, Miodrag J. Zhang, Shuhui Shao, Wei Huang, Qihao Qilu University of Technology Shandong Academy of Sciences Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center Jinan China Mathematical Institute The Serbian Academy of Sciences and Arts Belgrade Serbia Shandong Provincial Key Laboratory of Computer Networks Shandong Fundamental Research Center for Computer Science Jinan China

ISBN: (纸本)9798350329223

With the rapid development of the new generation of information technologies, including cloud computing, 5G, and the Internet of Things, data outsourcing storage in the cloud has brought great convenience to data storage or access anytime and anywhere. Due to the separation of ownership and management of outsourced stored data, it faces data security risks, including data loss and personal privacy disclosure. The third-party audit of data operational behavior by logs is often employed to strengthen the security of outsourced data. However, some privacy breach incidents in recent years show that third parties who may leak information about data and users' identities are not always trustworthy. To achieve data security and privacy protection, an operation behavior auditing scheme for outsourced data is proposed with the blockchain rather than third parties. The data operation behavior audit is carried out from three dimensions: integrity of the operation behavior log, the credibility of the operation behavior information, and compliance of operation behavior. The security analysis and experiment results indicate that this scheme is secure and feasible. © 2023 IEEE.

关键词： Blockchain

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A New Method to Enhance Container with vTPM 8

A New Method to Enhance Container with vTPM

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8th IEEE International Conference on Computer and Communications, ICCC 2022

作者： Jian, Zhang Xiao Peng, Zhou Qi, Wang Peng, Gao Liang, Wang Yi State Grid Smart Grid Research Institute Co. Ltd. State Grid Key Laboratory of Information & Network Security Nanjing China State Grid Zhejiang Electric Power Corporation Information & Telecommunication Branch Hangzhou China

ISBN: (纸本)9781665450515

This paper proposes a new container security enhancement system and method for containers running on 5G edge computing nodes. The system consists of vTPM module, physical TPM, container manager, vTPM manager, MEC controller and physical host. vTPM module is responsible for not only container image integrity measurement and starting up the container with trust, but also the trustworthiness measurement of container runtime file system and process. Physical TPM undertakes data encryption and password protection. Container manager performs trustworthiness measurement and verification of container. The MEC controller stores the measurement reference value for the physical TPM and issues keys and certificates for the physical TPM. The container enhancing method based on this system establishes a complete trust chain from the host to the container manager, and finally to containers. This ensures the trusted startup of the container, preventing the container itself and its runtime environment from being maliciously tampered with. It also dynamically measures the file system of the container in runtime to ensure the trustworthiness of the container. The experimental results indicate that this method is able to meet the requirements of container security enhancement for power 5G edge computing nodes. © 2022 IEEE.

关键词： Containers

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Research on Automated Penetration Testing Framework for power Web System Integrating Property information and Expert Experience 9th

Research on Automated Penetration Testing Framework for Powe...

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9th International Conference on Computer Engineering and networks, CENet2019

作者： Xi, Zesheng Cui, Jie Zhang, Bo Institute of Information and Communication Global Energy Interconnection Research Institute NanjingJiangsu China State Grid Key Laboratory of Information & Network Security NanjingJiangsu China State Grid Tianjin Electric Power Research Institute Tianjin China

ISBN: (纸本)9789811537523

Faced with the heterogeneous, intelligent and interconnected massive power Web system environment, it is difficult to meet the needs of existing and incremental services in efficiency by mining and verifying vulnerabilities manually. Therefore, an automated penetration testing framework for power Web system is proposed. Integrating property information and expert experience, the framework guides vulnerability mining path and vulnerability exploiting method selection, and realizing automatic vulnerability verification and exploitation of Web system through autonomous decision module. The experimental results show that the framework can simulate real attack behavior and efficiently verify and exploit common Web system vulnerabilities. © 2021, Springer Nature Singapore Pte Ltd.

关键词： Websites

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A DoS-attack Resilient Control Approach for AIOT-enabled Systems

A DoS-attack Resilient Control Approach for AIOT-enabled Sys...

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2023 International Conference on Artificial Intelligence of Things and Systems, AIoTSys 2023

作者： Cao, Xiaoya Chen, Zhenya Liu, Weisheng Liu, Yuanlong Wang, Wenting Wang, Xin Yang, Ming Qilu University of Technology Shandong Academy of Sciences Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center Jinan China Shandong Fundamental Research Center for Computer Science Shandong Provincial Key Laboratory of Computer Networks Jinan China State Grid Shandong Electric Power Company Jinan China State Grid Shandong Electric Power Research Institute Jinan China

ISBN: (纸本)9798350312270

This paper presents a novel controller design for dealing with the challenges posed by Denial-of-Service (DoS) attacks in the context of Artificial Intelligence of Things (AIOT). The proposed design employs a prediction approach that utilizes uniform quantization for both encoder and decoder, aiming to effectively mitigate data loss during data transmission in scenarios involving DoS attacks. Furthermore, the study investigates the application of dynamic system design as a means to enhance the security defense mechanisms of AIOT, consequently bolstering the overall resilience of the system. The effectiveness and practicality of the proposed approach are validated through comprehensive simulations, providing empirical evidence of its efficacy. © 2023 IEEE.

关键词： System stability

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An Adaptive Heterogeneous Credit Card Fraud Detection Model Based on Deep Reinforcement Training Subset Selection

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2024年第8期5卷 4026-4041页

作者： Zhu, Kun Zhang, Nana Ding, Weiping Jiang, Changjun the Key Laboratory of Embedded System and Service Computing Ministry of Education Shanghai201804 China Collaborative Innovation Center for Financial Network Security Tongji University Shanghai201804 China the School of Computer Science and Technology Donghua University Shanghai201620 China the School of Information Science and Technology Nantong University Nantong226019 China

Heterogeneous fraud detection is an important means of credit card security assurance, which can utilize historical transaction records in a source and target domain to build an effective fraud detection model. Nevertheless, large feature distribution differences between source and target transaction instances and the complex intrinsic structure hidden behind transaction data make it difficult for existing credit card fraud detection (CCFD) models to capture and transfer the most informative feature representations and seriously hinder detection performance. In this work, we propose a novel adaptive heterogeneous CCFD model named adaptive heterogeneous credit card fraud detection model based on deep reinforcement training subset selection (RTAHC) based on deep reinforcement training subset selection, which mainly contains two components: selection distribution generator (SDG) and transaction fraud detector (TFD, including feature extractor with an attention mechanism and classifier). The SDG can generate the selection probability distribution vector via the reinforcement reward mechanism, and then transaction instances in the source domain relevant to the target domain are selected. The feature extractor with an attention mechanism can learn the abstract deep semantic feature representations of selected source transaction instances and the target domain. The joint training of SDG and TFD can provide more real-time and accurate transaction feature representations to reduce the distribution discrepancy between the two domains. We verify the detection performance of RTAHC across a large real-world credit card transaction dataset and four public datasets. Experimental results demonstrate that the RTAHC model can exhibit competitive CCFD performance. Impact Statement—With the rise of artificial intelligence (AI)generated models, credit card fraud has become increasingly rampant, which also causes tens of billions of U.S. dollars in credit card losses worldwide every year

关键词： Hidden Markov models

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A Study on a Reduced Indicator System for the network security Situational Assessment Model

A Study on a Reduced Indicator System for the Network Securi...

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2023 International Conference on networking and network Applications, NaNA 2023

作者： Zhang, Hongbin Bai, Yikang Zhao, Dongmei Liu, Bin Xu, Ying Hebei Normal University Hebei Key Laboratory of Network and Information Security Shijiazhuang China Hebei University of Science and Technology School of Information Science and Engineering Shijiazhuang China School of Economics and Management Research Center of Big Data and Social Computing Shijiazhuang China

ISBN: (纸本)9798350327380

It is a challenge to monitor the network security state in a large-scale network environment because the selection of situation assessment indicators is overrun by massive observational information. To address this issue, this paper proposes a network security situational assessment model based on a reduced indicator system. The model categorises the characteristics of network assets and threats into endogenous situational factors and exogenous situational factors. By applying the multi-label extremely random tree algorithm to select the importance of network features, a reduced indicator system with independence and strong comprehensiveness is established. Additionally, the weights of the reduced indicator system are calculated using an improved analytical hierarchy process, which yields the evaluation results for network security situations. The experimental results show that the model improves the accuracy and timeliness of the situation assessment model, and the method can reflect the network situation in real time. © 2023 IEEE.

关键词： network security

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Wrong-of-Thought: An Integrated Reasoning Framework with Multi-Perspective Verification and Wrong information

Wrong-of-Thought: An Integrated Reasoning Framework with Mul...

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

作者： Zhang, Yongheng Chen, Qiguang Zhou, Jingxuan Wang, Peng Si, Jiasheng Wang, Jin Lu, Wenpeng Qin, Libo School of Computer Science and Engineering Central South University China Research Center for SCIR Harbin Institute of Technology Harbin China Key Laboratory of Computing Power Network and Information Security Ministry of Education Qilu University of Technology Shandong Academy of Sciences China Yunnan University Kunming China

ISBN: (纸本)9798891761681

Chain-of-Thought (CoT) has become a vital technique for enhancing the performance of Large Language Models (LLMs), attracting increasing attention from researchers. One stream of approaches focuses on the iterative enhancement of LLMs by continuously verifying and refining their reasoning outputs for desired quality. Despite its impressive results, this paradigm faces two critical issues: (1) Single verification method: The current paradigm relies solely on a single verification method. (2) Wrong information Ignorance: The traditional paradigm directly ignores wrong information during reasoning and refines the logic paths from scratch each time. To address these challenges, we propose Wrong-of-Thought (WoT), which includes two core modules: (1) Multi-Perspective Verification: A multi-perspective verification method for accurately refining the reasoning process and result, and (2) Wrong information Utilization: Utilizing wrong information to alert LLMs and reduce the probability of LLMs making same mistakes. Experiments on 8 popular datasets and 5 LLMs demonstrate that WoT surpasses all previous baselines. In addition, WoT exhibits powerful capabilities in difficult computation tasks. © 2024 Association for Computational Linguistics.

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A Self-adaptive Single-Objective Multitasking Optimization Algorithm 1

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17th International Conference on Bio-Inspired computing: Theories and Applications, BIC-TA 2022

作者： Li, Xiaoyu Wang, Lei Jiang, Qiaoyong Li, Wei Wang, Bin The Key Laboratory of Network Computing and Security Technology of Shaanxi Province Xi’an University of Technology Xi’an710048 China The Key Laboratory of Industrial Automation of Shaanxi Province Shaanxi University of Technology Hanzhong723001 China School of Electronic and Information Engineering Ankang University Ankang725000 China

ISBN: (数字)9789819915491

ISBN: (纸本)9789819915484

Evolutionary multitasking optimization algorithms have been presented for dealing with multiple tasks simultaneously. Many studies have proved that EMTOs often perform better than conventional single-task evolutionary. Transferring knowledge plays a very important role in multitask optimization algorithms. Many existing methods transfer elite solutions between tasks to improve algorithm performance, however, these methods may or produce negative transfer if inter-task similarity is low or irrelevant. This paper presents a self-adaptive multitasking optimization algorithm, SAMTOA, to find more valuable transferred solutions between tasks. In SAMTOA, the solutions for the next generation transfer are adaptively determined based on the successful transfer solutions of the previous generation. The method can effectively reduce the probability of transferring useless solutions between tasks and effectively utilize valuable solutions in tasks to improve the efficiency of knowledge transfer between tasks. Experimental results on single-objective multitasking optimization benchmark problems indicate that SAMTOA outperforms the other the state-of-the-art EMTO algorithms. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Optimization

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Evaluation of network security State of Industrial Control System Based on BP Neural network 4

Evaluation of Network Security State of Industrial Control S...

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4th World Symposium on Artificial Intelligence, WSAI 2022

作者： Zhang, Daojuan Zhang, Peng Wang, Wenhui Jin, Minghui Xiao, Fei State Grid Key Laboratory of Information & Network Security State Grid Smart Grid Research Institute Co. Ltd Beijing China State Grid Shanghai Municipal Electric Power Company Shanghai China

ISBN: (数字)9781665498548

ISBN: (纸本)9781665498548

With the development of computer and network technology, industrial control systems are connecting with the Internet and other public networks in various ways, viruses, trojans and other threats are spreading to industrial control systems, industrial control system information security issues are becoming increasingly prominent. Under this background, it is necessary to construct the network security evaluation model of industrial control system based on the safety evaluation criteria and methods, and complete the safety evaluation of the industrial control system network according to the design scheme. Based on back propagation (BP) neural network's evaluation of the network security status of industrial control system, this paper determines the number of neurons in BP neural network input layer, hidden layer and output layer by analyzing the actual demand, empirical equation calculation and experimental comparison, and designs the network security evaluation index system of industrial control system according to factors affecting industrial control safety, and constructs a safety rating table. Finally, by comparing the performance of BP neural network and multilinear regression to the evaluation of the network security status of industrial control system through experimental simulation, it can be found that BP neural network has higher accuracy for the evaluation of network security status of industrial control system. © 2022 IEEE.

关键词： Cybersecurity

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