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检索条件"机构=State Grid Laboratory of Power Cyber-security Protection and Monitoring Technology"

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Research and Implementation of Operation monitoring and Resource Scheduling Methods Based on the Digital Twin Model of the power grid 5

Research and Implementation of Operation Monitoring and Reso...

引用

5th International Conference on Applied Machine Learning, ICAML 2023

作者： Qiao, Junfeng Yu, Hai He, Zhimin Shen, Lianteng Du, Xiaodong State Grid Smart Grid Research Institute Co. Ltd State Grid Laboratory of Power Cyber-Security Protection & Monitoring Technology Nanjing China China Electric Power Research Institute Co. Ltd Beijing China State Grid Hebei Electric Power Co. Ltd Shijiazhuang China

ISBN: (纸本)9798350341416

The digital twin model of the power grid has been widely applied in fields such as power equipment status acquisition and power equipment fault analysis. The use of digital twin models to virtual equipment status parameters provides strong model support for the acquisition and display of power equipment status. The digital twin model describes the physical entity in the power grid as digital indicators, and superimposes effective business analysis logic, making it widely provide digital services for data using departments. Similarly, the virtualization and visualization of device status parameters can also provide technical support for monitoring power operation status and scheduling power resources. This article proposes an operation monitoring and resource scheduling method based on the digital twin model of the power grid, which abstracts the status data of power grid equipment into key indicators of the digital twin model. Then, high-performance data collection and transmission technology is used to push the status data of power grid equipment and power grid operation status information to the power management department in a way that is easy to observe and edit. By adopting this approach, power managers do not need to conduct on-site surveys to monitor the operating status of electricity, and then develop resource scheduling plans to schedule electricity resources and achieve secondary distribution, providing better power supply services for electricity customers. © 2023 IEEE.

关键词： Data acquisition

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Hardware feature extraction technology for resource aggregation control communication channel and signal source 6

Hardware feature extraction technology for resource aggregat...

引用

6th International Conference on Intelligent Computing, Communication, and Devices, ICCD 2023

作者： Nige, Li Zhipeng, Shao Wenting, Wang Ziang, Lu Tengyan, Wang State Grid Smart Grid Research Institute Co. Ltd. Jiangsu Nanjing210003 China State Grid Laboratory of Power Cyber-Security Protection and Monitoring Technology Jiangsu Nanjing210003 China State Grid Shandong Electric Power Research Institute Shandong Jinan250013 China

ISBN: (数字)9781510666269

ISBN: (纸本)9781510666252

In the distributed resource access scenario, the growing number of terminal devices brings pressure and test to the wireless communication network. Unauthenticated terminal access to the network will bring huge security risks. This paper focuses on the hardware features of resource aggregation control communication channel and signal source. For the distributed power system with complex environment, this paper proposes a hardware feature extraction technology for resource aggregation-oriented control communication channel and signal source. On the basis of the research on the theory of generic feature extraction of hardware fingerprint, the specific feature extraction methods of several common communication methods in typical distributed resource aggregation and control scenarios are studied. This paper designs a hardware fingerprint implementation scheme in a typical distributed resource aggregation and control scenario. Experiments show that the proposed fingerprint extraction scheme can effectively distinguish different devices according to different characteristics of devices. It provides a terminal access method with high security and low complexity in the distributed edge aggregation control network of power system. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Feature extraction

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An Intelligent Arrangement Method for New Distribution Network Data Sharing Service

An Intelligent Arrangement Method for New Distribution Netwo...

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International Conference on Artificial Intelligence and Communication Technologies, ICAICT 2023

作者： Xu, Min Zhou, Aihua Shen, Xiaofeng Chen, Jingde Gu, Hua Huang, Chenhong Peng, Lin Li, Nige Wang, Gang Wang, He Wang, Ning State Grid Smart Grid Research Institute Co. LTD Jiangsu Nanjing210003 China State Grid Shanghai Electric Power Company Shanghai200122 China Qingpu Power Supply Company State Grid Shanghai Municipal Electric Power Company Shanghai200122 China State Grid Laboratory of Power Cyber-Security Protection and Monitoring Technology Nanjing210003 China State Grid Jiangsu Electric Power Co. LTD Jiangsu Nanjing210024 China

ISBN: (纸本)9789819969555

With the extensive access of new power system distribution and distributed new energy, its data volume is also rapidly expanding, and the traditional relational database is difficult to support the elastic storage and topological relationship analysis of such a huge amount of data;At the same time, the amount of data between different businesses in the power grid is increasing exponentially. The traditional data architecture based on the tree organization relationship also causes a serious waste of resources and computing power to the background server. This paper innovatively designs an intelligent orchestration method for power distribution and distributed new energy data resources, defines the relevant component orchestration process according to different business scenarios, uses data extraction and conversion tools to access the power grid data center and real-time measurement center, obtains online and offline data resources of the power grid, and carries out the topology association orchestration of data with equipment as the core, The designed data model library will classify and store the collected data and distribute the strategy. The designed execution engine will instantiate the topology of the data required for the business of the strategy. The designed AI model will conduct in-depth learning and training of the topology instantiation data and add it to the designed state, so as to realize the intelligent closed-loop cycle. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Extraction

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Abnormal Network Traffic Detection Algorithm Based on Improved Convolutional Neural Network

Abnormal Network Traffic Detection Algorithm Based on Improv...

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Interactive Intelligent Systems and Techniques (IIST), International Conference on

作者： Lu Chen Tao Zhang Yuanyuan Ma Mu Chen Protection and Monitoring Technology State Grid Smart Grid Research Institute Co. Ltd Nanjing China Protection and Monitoring Technology State Grid Laboratory of Power Cyber-Security Nanjing China

ISBN: (数字)9798350374421

ISBN: (纸本)9798350374438

With the increasing complexity, automation, and intelligence of network attacks, new types of attacks are constantly emerging in the network, posing great challenges to network attack detection and timely response based on prior rules. In order to more effectively and accurately identify abnormal traffic, a network abnormal traffic detection algorithm based on improved convolutional neural networks is proposed. The algorithm first inputs the key features of traffic anomaly monitoring, converts them into color images through visualization technology, extracts higher dimensional features, and then uses neural structure search technology to find a lightweight convolutional network structure with high accuracy and less time consumption. The optimal model is used to output the type of traffic anomaly. The results indicate that the algorithm has a higher accuracy and the shortest classification time for a single image.

关键词： Visualization Accuracy Convolution Telecommunication traffic Reinforcement learning Predictive models Feature extraction Convolutional neural networks Detection algorithms monitoring

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cyber-Attack Detection Approach In Photovoltaic Microgrids Using LSTM-based Autoencoders 4

Cyber-Attack Detection Approach In Photovoltaic Microgrids U...

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4th International Conference on power Engineering, ICPE 2023

作者： Liu, Quan Guo, Shiang Qiu, Shenjian Fei, Jiaxuan Zhang, Bo Yu, Xiang Pan, Kaikai State Grid Jiangsu Electric Power Co. Ltd. Yangzhou Power Supply Branch Yangzhou China Zhejiang University School of Electrical Engineering Hangzhou China State Grid Smart Grid Research Institute Co. LTD. State Grid Laboratory of Power cyber-Security Protection and Monitoring Technology Nanjing China

ISBN: (纸本)9798350340020

Photovoltaic (PV) microgrids have been exposed to serious cyber threats for the integration of information and communication technologies (ICT) and renewable energy. In this article, a data-driven detection approach using an LSTM-based autoencoder has been developed against cyberattacks including fake data injection attacks (FDIA) and denial of service (DoS) attacks in PV microgrids. The proposed detection algorithm applies the unsupervised learning method that uses an LSTM neural network to capture the temporal feature and autoencoder to get reconstructed residuals of given input sequence data of measurements. By comparing residuals with the given threshold, the decision can be made on whether the system is attacked. The proposed algorithm has been evaluated for its performance in the PV microgrid model considering PV generation, energy storage system, and grid-tied function under various cyberattacks. © 2023 IEEE.

关键词： Long short-term memory

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Research and Application of Digital Modeling technology Based on Multi-source Data of power grid

Research and Application of Digital Modeling Technology Base...

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作者： Qiao, Junfeng Yu, Hai He, Zhimin Shen, Lianteng Du, Xiaodong State Grid Laboratory of Power Cyber-Security Protection and Monitoring Technology State Grid Smart Grid Research Institute Co. Ltd. Nanjing China China Electric Power Research Institute Co. Ltd. Beijing China State Grid Hebei Electric Power Co. Ltd. Shijiazhuang China

During the production and operation process, power enterprises generate rich power data, which is distributed and stored in multiple power application information systems. Due to past management reasons, there are significant differences in the description rules of data among different power application information systems, and due to the different data structures of various business processes, their storage structures and media also vary greatly. For example, for the operation and maintenance data generated during the operation and maintenance work, mainly photo and video data, this data must be stored in a large file storage server. The power consumption information sales data, which is composed of discrete numerical data, is stored in the relational database. In response to the above issues, this article proposes a method for constructing a power multi-source data model, which unifies the modeling of heterogeneous power data from multiple sources to meet the digital construction and service needs of power business. For file system data, build a file retrieval directory, store it in a relational data table, and establish an association model with relational data to achieve data connectivity of business meaning. This model can provide data services for power application scenarios, and power business application managers can directly call the model interface to meet the needs of power applications. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

关键词： Information systems

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power Terminal Identity Authentication Scheme for Disaster Recovery Environment 23

Power Terminal Identity Authentication Scheme for Disaster R...

引用

Proceedings of the 2023 3rd Guangdong-Hong Kong-Macao Greater Bay Area Artificial Intelligence and Big Data Forum

作者： Lu Chen Yuanyuan Ma Tao Zhang State Grid Laboratory of Power cyber-Security Protection and Monitoring Technology State Grid Smart Grid Research Institute Co. Ltd China

ISBN: (纸本)9798400716362

In order to ensure the trusted access of power collection terminals in a disaster recovery environment, this paper proposes a cross-domain authentication scheme based on blockchain. Firstly, an improved PBFT algorithm based on reputation value election is designed, which increases the calculation of node reputation value and improves the dynamic addition and removal of consensus nodes and the election of master nodes based on node reputation value and failure conditions. Then, a cross-domain authentication model for power collection terminals based on blockchain is constructed. The blockchain certificate format and cross-domain authentication protocol are designed, and the security and efficiency are analyzed. The analysis results show that the scheme has security properties such as resistance to distributed attacks, and the communication overhead is lower than that of the traditional PBFT algorithm.

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A Web Attack Detection Method Based on DistilBERT and Feature Fusion for power Micro-Application Server 2

A Web Attack Detection Method Based on DistilBERT and Featur...

引用

2nd International Conference on Advanced Electronics, Electrical and Green Energy, AEEGE 2023

作者： Nige, Li Lu, Chen Lei, Zhao Zhenning, Teng Zhiqiang, Wang Yiyang, Shao Xiaolin, Gui State Grid Laboratory of Power Cyber-Security Protection and Monitoring Technology State Grid Smart Grid Research Institute Co.Ltd. Nanjing China Xi'an Jiaotong University Faculty of Electronic and Information Engineering Shaanxi Province Key Laboratory of Computer Network Xi'an China

ISBN: (纸本)9798350322866

The widespread use of power micro-applications has significantly expanded the attack surface of their server side, thus increasing the risk of vulnerability attacks such as SQL injection, XSS, and CRLF injection. To ensure the security of power systems, these attacks must be detected precisely and timely. Therefore, this paper proposes a server-side web attack detection method based on DistilBERT and feature fusion for HTTP and HTTPS requests. The method treats HTTP and HTTPS requests as text data, specifically, extracts deep semantic features using DistilBERT, and fuses them with well-designed empirical features to comprehensively characterize and classify the request. Consequently, anomalous requests can be detected. The experimental results show that the accuracy, precision, recall, and F1 score of the method on HTTP CSIC 2010 and FWAF datasets are close to or higher than 99%. Compared with other methods as far as we known, this method has better performance and efficiency. © 2023 IEEE.

关键词： cybersecurity

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Design of an Automated security protection System for power System 4

Design of an Automated Security Protection System for Power ...

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2023 4th International Conference on Computer Engineering and Intelligent Control, ICCEIC 2023

作者： Xia, Jun Li, Jun Jiang, Xinfan Zhou, Bo Xi, Zesheng State Grid Hunan Electric Power Co. Ltd Changsha China State Grid Hunan Electric Power Co. Ltd. Hunan Energy Big Data Intelligence Ltd Changsha China State Grid Laboratory of Power Cyber-Security Protection and Monitoring Technology State Grid Smart Grid Research Institute Co. Ltd Nanjing China

ISBN: (纸本)9798350308877

In situations involving power system applications, a design plan for a new kind of automated security protection system has been put out. The self-repair vulnerability module, attack detection module, security policy configuration automation module, and front-end monitoring interface have all been designed for this article. This prototype system can secure device privacy and system stability while generating security policies automatically, responding to attacks quickly, and operating and maintaining expenses. This mostly entails the creation of self-repair and mining techniques for terminal vulnerabilities as well as detection techniques for malicious terminal-based assaults. In order to automatically create security protection device linkage methods, the automation module is configured to accept vulnerability and attack alert information. Each module opens its own database or offers interface forms for interactive operation and administration, while the front-end monitoring interface is created concurrently. © 2023 IEEE.

关键词： Automation

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Research on Business Consistency Verification Techniques for Energy Big Data Privacy protection

Research on Business Consistency Verification Techniques for...

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International Conference on Computer Engineering and Applications (ICCEA)

作者： Xiuli Huang Pengfei Yu Yujia Zhai State Grid Laboratory of Power Cyber-Security Protection and Monitoring Technology State Grid Smart Grid Research Institute Co. LTD Nanjing China

ISBN: (数字)9798350386776

ISBN: (纸本)9798350386783

In this paper, we study the consistency verification technology for multi-party collaborative privacy-preserving operations of energy big data, and propose a consistency assessment algorithm based on minimum hash signatures for the privacy and consistency challenges in energy big data processing. The algorithm realizes the assessment of the consistency of the target dataset through data compression and signature design of the data source, avoids direct access to the original data, and guarantees data privacy and consistency of processing results. The experimental results show that the algorithm is able to effectively assess data consistency on energy big datasets such as electricity and gas consumption, and the results are close to the exact algorithm with high credibility and efficiency.

关键词： Data privacy Soft sensors Electricity Data compression Collaboration Big Data Reliability engineering

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