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Concept and Research Framework for Coordinated Situation Awareness and Active Defense of Cyber-physical power Systems Against Cyber-attacks

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Journal of Modern power Systems and Clean Energy 2021年第3期9卷 477-484页

作者： Ming Ni Manli Li Jun’e Li Yingjun Wu Qi Wang the NARI Group Corporation(State Grid Electric Power Research Institute) NARI Technology Co.Ltd.and the State Key Laboratory of Smart Grid Protection and ControlNanjing 211106China the School of Cyber Science and Engineering Wuhan Universityand the Key Laboratory of Aerospace Information Security and Trusted Computing of the Ministry of EducationWuhan 430072China the College of Energy and Electrical Engineering Hohai UniversityNanjing 211100China the School of Electrical Engineering Southeast UniversityNanjing 210096China

Due to the tight coupling between the cyber and physical sides of a cyber-physical power system(CPPS),the safe and reliable operation of CPPSs is being increasingly impacted by cyber *** situation poses a challenge to traditional security defense systems,which considers the threat from only one side,i.e.,cyber or *** cope with cyberattacks,this paper reaches beyond the traditional one-side security defense systems and proposes the concept of cyber-physical coordinated situation awareness and active defense to improve the ability of *** example of a regional frequency control system is used to show the validness and potential of this ***,the research framework is presented for studying and implementing this ***,key technologies for cyber-physical coordinated situation awareness and active defense against cyber-attacks are introduced.

关键词： Cyber-physical power system(CPPS) cyber security cyber-attack situation awareness active defense

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Fusion and Localization Technology of 3D Model Attitude and Real Physical Environment Visualization information of power Inspection Site 1

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Annual International Conference on 3D Imaging Technology, IC3DIT 2019

作者： Min, Xu Hai, Yu Zhansheng, Hou Nige, Li Xingchuan, Bao Lin, Peng Gang, Wang Liang, Zhu Hao, Lu Zhifeng, Wang Peng, Zhao Global Energy Interconnection Research Institute Nanjing Jiangsu210003 China State Grid Key Laboratory of Information & Network Security Nanjing210003 China State Grid Shanxi Electric Power Information & Communication Company Shanxi Xian710048 China

ISBN: (数字)9789811538674

ISBN: (纸本)9789811538667

In this paper, the closed loop detection technology of depth vision scene recognition is adopted to overcome the problem that the visual odometer cannot initially locate, and the disadvantage that the location and azimuth can only be estimated publicly, which is easy to accumulate positioning errors. Through closed-loop detection, the scene map collected at present is matched with the scene in the atlas in real time, and the binocular vision attitude adjustment algorithm is assisted to obtain the topological determination with high accuracy. In this way, the navigation and positioning accuracy based on depth vision sensor in the indoor environment of the substation is greatly improved, and the accurate positioning of substation personnel is realized. Thus, the dangerous area is delimited, and the safety control of personnel on-site operation station is realized, which greatly improves personal safety. © 2020, Springer Nature Singapore Pte Ltd.

关键词： Personnel

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Research on Mimic Defence Technology for Smart Unit Application Environment of power Grid 3

Research on Mimic Defence Technology for Smart Unit Applicat...

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2019 3rd International Conference on Electrical, Mechanical and Computer Engineering, ICEMCE 2019

作者： Xi, Zesheng Zhang, Bo Sun, Xin Guan, Xiaojuan Institute of Information and Communication Global Energy Interconnection Research Institute Nanjing Jiangsu China State Grid Key Laboratory of Information and Network Security Nanjing Jiangsu China State Grid Zhejiang Electric Power Research Institute Hangzhou Zhejiang China

Aiming at the problem that the new network attack cannot be effectively defended at present, this paper proposes a framework of application-level mimic defense technology for smart grid units to solve the active attack defense problem of smart terminal units in the source grid environment. In this paper, the application security mimic defense architecture and interactive instruction level heterogeneous redundancy technology for smart grid units are studied to achieve universal and self-immune active immunity against grid application-level attacks. Furthermore, the dynamic change and heterogeneous redundancy characteristics of application level are constructed by mimetic defense technology. The risk and vulnerability of terminal application security vulnerabilities are actively hidden to actively avoid attacks, so as to enhance the active defense capability of industrial control terminal side of power grid. © Published under licence by IOP Publishing Ltd.

关键词： Smart power grids

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Control flow integrity check based on LBR register in power 5G environment 10

Control flow integrity check based on LBR register in power ...

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10th China International Conference on Electricity Distribution, CICED 2022

作者： Li, Nige Zhou, Peng Wang, Tengyan Chen, Jingnan State Grid Smart Grid Research Institute Co. Ltd. State Grid Key Laboratory of Information & Network Security Nanjing210003 China State Grid Zhejiang Electric Power Corporation Information &Telecommunication Branch Hangzhou China

ISBN: (数字)9781665452687

ISBN: (纸本)9781665452687

This paper proposes a control flow integrity checking method based on the LBR register: through an analysis of the static target program loaded binary modules, gain function attributes such as borders and build the initial transfer of legal control flow boundary, real-time maintenance when combined with the dynamic execution of the program flow of control transfer record, build a complete profile control flow transfer security;Get the call location of/bin/sh or system() in the program to build an internal monitor for control-flow integrity checks. In the process of program execution, on the one hand, the control flow transfer outside the outline is judged as the abnormal control flow transfer with attack threat;On the other hand, abnormal transitions across the contour are picked up by an internal detector. In this method, by identifying abnormal control flow transitions, attacks are initially detected before the attack code is executed, while some attacks that bypass the coarse-grained verification of security profile are captured by the refined internal detector of control flow integrity. This method reduces the cost of control flow integrity check by using the safety profile analysis of coarse-grained check. In addition, a fine-grained shell internal detector is inserted into the contour to improve the safety performance of the system and achieve a good balance between performance and efficiency. © 2022 IEEE.

关键词： Internet of things

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Research and Application of Smart Water Meter Monitoring System Based on NB-IoT 7

Research and Application of Smart Water Meter Monitoring Sys...

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7th IEEE information Technology and Mechatronics Engineering Conference, ITOEC 2023

作者： Zhao, Yuanyuan Zhang, Tixiang Hao, Huijuan Zhang, Xiaojie Shandong Computer Science Center Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Provincial Key Laboratory of Computer Networks Shandong Fundamental Research Center for Computer Science No. 19 Keyuan Road Shandong Jinan250014 China Shandong Yonate Environmental Technology Co. Ltd. Shandong Jinan250014 China

ISBN: (纸本)9798350334197

With the increasing shortage of water resources and the improvement of environmental awareness, intelligent water meter monitoring systems have become a hot research topic in the field of water conservation. This paper studies and designs a smart water meter system based on NB-IoT, and discusses its effect in practical applications. This smart water meter monitoring system adopts STM8 microcontroller as the main control chip of the water meter, and adopts the low-power NB-IoT module BC28 module to upload the monitored voltage data, network signal quantity, current water consumption and collection time to the TLink cloud platform in real time, which solves the problems of unstable communication in the working environment, high power consumption of long-term sensor collection and transmission data. At the same time, the water meter can achieve the function of remote control of the water valve switch by driving the stepper motor, which perfectly solves the problems and shortcomings of the current traditional water meter and smart water meter, and greatly meets the development needs of the water industry. © 2023 IEEE.

关键词： Electric power utilization

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Research and Implementation of Data Feature Extraction Technology for Multisource Heterogeneous Data in Electric Distribution network

Research and Implementation of Data Feature Extraction Techn...

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International Conference on Artificial Intelligence and Communication Technology, ICAICT 2023

作者： Qiao, Junfeng Zhou, Aihua Peng, Lin Shen, Xiaofeng Huang, Chenhong State Grid Key Laboratory of Information & Network Security State Grid Smart Grid Research Institute Co LTD Jiangsu Nanjing210003 China Qingpu Power Supply Company State Grid Shanghai Electric Power Company Shanghai201799 China

ISBN: (纸本)9789819966400

With the development of information technology, the degree of information of electric power enterprises is getting higher and higher, and the data generated by business systems is also growing rapidly. Data has become the new power of enterprise production and plays a vital role in the business growth of power companies. State Grid Corporation of China has brought the benefits of rapid business growth by using data, but at the same time, it is also faced with data redundancy, difficult data discovery, low efficiency, resource consumption, and other issues, as is the case in the power industry. In the power industry, the data preparation stage of the distribution network will also occupy most of the time and energy of data scientists. The high degree of specialization of data extraction and feature engineering work will result in a high threshold, which will increase obstacles for business personnel to participate in data value exploration. As long as traditional automatic data extraction and automatic feature engineering are based on business experience, data analysis and data extraction must be carried out from top to bottom, which is far from enough in the era of artificial intelligence. In order to reduce the technical threshold of data utilization, this paper fully integrates data science with power grid business, carries out research on multisource heterogeneous data extraction and automatic feature engineering technology, and realizes intelligent data management, improves data availability, improves data management level, and reduces the threshold of data utilization through automatic feature engineering methods, Finally, it supports typical business scenarios such as Internet of data management or power consumption information acquisition data management of State Grid Corporation of China. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： information management

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A Hybrid Loss network for Localization of Image Manipulation 19th

A Hybrid Loss Network for Localization of Image Manipulation

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19th International Workshop on Digital Forensics and Watermarking, IWDW 2020

作者： Yin, Qilin Wang, Jinwei Luo, Xiangyang Nanjing University of Information Science and Technology and Engineering Research Center of Digital Forensics Ministry of Education Nanjing210044 China State Key Laboratory of Mathematical Engineering and Advanced Computing Henan450001 China Shanxi Key Laboratory of Network and System Security Xidian University Xi’an710071 China

ISBN: (纸本)9783030694487

With the development of information security, localization of image manipulations havs become a hot topic. In this paper, a hybrid loss network is proposed for the manipulated image forensics. First, the patch prediction module extracts corresponding features representing the discrepancy of the tampered region boundaries. Then, these features are constrained by the Pixel Normalization, thereby improving the classification performance for the tampered patches. Finally, multi-scale patch prediction masks and semantic information are fused to segment out the tampered regions. The experiments demonstrate the proposed model can achieve high performance. © 2021, Springer Nature Switzerland AG.

关键词： Pixels

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Adversarial Attacks on Deep Neural networks for Time Series Prediction 10

Adversarial Attacks on Deep Neural Networks for Time Series ...

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10th International Conference on Internet computing for Science and Engineering, ICICSE 2021

作者： Xu, Aidong Wang, Xuechun Zhang, Yunan Wu, Tao Xian, Xingping Guangdong Provincial Key Laboratory of Power System Network Security Electric Power Research Institute CSG China School of Computer Science and Technology Chongqing University of Posts and Telecommunications China School of Cybersecurity and Information Law Chongqing University of Posts and Telecommunications China

ISBN: (纸本)9781450384957

Time series data is widespread in real-world scenarios. To recover and infer missing information in practical domains, such as stock price monitoring, electricity load forecasting, traffic flows analysis, climate trend prediction, etc., the problem of time series prediction has been widely studied as a classical research topic in data mining. Over the past decade, deep learning architectures are introduced as a vital part of the next generation of time series prediction models. However, recent studies showed that deep learning models are vulnerable to adversarial attacks. In this paper, we study the adversarial attacks on the time series prediction models prospectively. We propose an attack strategy to generate adversarial samples by adding imperceptible perturbed data to the original time series with the goal of reducing the accuracy of time series prediction models. Specifically, the perturbation-based adversarial example generation algorithm is proposed using gradient information of time series prediction model. Moreover, adversarial examples should be imperceptible to humans. To address the challenge, we craft adversarial samples based on importance measuring to perturb the original data locally. We evaluate our attacks on state-of-the-art time series prediction models using three time series datasets. Our results demonstrate that our attacks can effectively evade the time series prediction models, and the adversarial attacks mechanisms can be used as robustness metric for constructing robust time series prediction models. © 2021 ACM.

关键词： Time series

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A Novel CP-ABE Based Sidechain Protocol for Distributed power System Data Storage Management with the Blockchain 2021

A Novel CP-ABE Based Sidechain Protocol for Distributed Powe...

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2nd International Conference on computing and Data Science, CONF-CDS 2021

作者： Gao, Xianzhou Huang, Xiuli Zhang, Wei Yang, Ruxia State Grid Key Laboratory of Information and Network Security Global Energy Interconnection Research Institute Co. Ltd. Nanjing China Changzhou Power Supply Branch State Grid Jiangsu Electric Power Co. Ltd Changzhou China

ISBN: (纸本)9781450389570

Due to technical bottlenecks such as systems vulnerable to attacks and data are easily tampered with, and it is difficult for the distributed power system data storage management to achieve multi-agent integration and development. Known as the "trust machine,"the Blockchain has an essential role in promoting the energy Internet construction with its distributed storage, tamper-proof, traceable, and multi-node sharing technical characteristics. Its technical advantages have great potential application value in the power industry. Most of the existing blockchain schemes directly combine the CP-ABE algorithm with the Blockchain. However, due to the lack of permission inheritance, these schemes have permission to redundancy and waste computing resources. In this paper, a new user-controlled on-chain permission management scheme is proposed. The original CP-ABE model is extended in this scheme, and the concept of role assignment and attribute tree is proposed. The attribute tree uses the multi-tree structure to realize the attribute set's specification description. The connectivity between roles in the attribute tree represents the inheritance relationship of permission so that the permission inheritance and permission granting can be realized. In this paper, a sidechain prototype system is developed for evaluating the scheme, and its performance is tested and analyzed. The experimental results show that the prototype system can realize the user-controlled permission assignment and permission inheritance function of data owner on the Blockchain. © 2021 ACM.

关键词： Blockchain

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Time Series Anomaly Detection Based on Normalized Flow and Bayesian networks 9

Time Series Anomaly Detection Based on Normalized Flow and B...

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9th IEEE International Conference on Data Science in Cyberspace, DSC 2024

作者： Yao, Honglei Liu, Donglan Chang, Yingxian Liu, Xin Tang, Chaofan State Grid Shandong Electric Power Research Institute Jinan China State Grid Shandong Electric Power Company Jinan China Qilu University of Technology Shandong Academy of Sciences Shandong Provincial Key Laboratory of Computer Networks Shandong Fundamental Research Center for Computer Science Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center National Supercomputer Center in Jinan Jinan China

ISBN: (纸本)9798350391367

Time series anomaly detection often faces significant challenges due to the high dimensionality, interdependence, and label sparsity of the data. Traditional methods struggle to model the intricate relationships between multiple time series components and often fail to accurately detect anomalies due to insufficient data dependence mining. To address these issues, we introduce GCRNF, a novel Graph-Enhanced Standardized Flow Model that incorporates a Bayesian network for causality modeling. This model decomposes joint probabilities into conditional probabilities and utilizes a graph dependency encoder with hybrid CNN-RNN models and Graph Convolutional networks (GCNs). Our experimental results demonstrate that GCRNF outperforms existing methods in density estimation, anomaly detection, and drift identification within time series distributions. Specifically, GCRNF showed a significant improvement in detection accuracy and robustness compared to traditional methods, providing a more effective solution for identifying anomalies in complex multivariate time series data. © 2024 IEEE.

关键词： Markov processes

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