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检索条件"机构=State Grid Laboratory of Power cyberSecurity Protection and Monitoring Technology"

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Merkel Tree Combines the "Cloud-Edge-to-End" Multi-Level Collaborative Security Architecture of Blockchain

Merkel Tree Combines the "Cloud-Edge-to-End" Multi-Level Col...

引用

Artificial Intelligence technology (ACAIT), Asian Conference on

作者： Nige Li Tengyan Wang Mu Chen Xinjian Zhao Jing Zhang Yong Li China Electric Power Research Institute State Grid Laboratory of Power Cyber-Security Protection and Monitoring Technology Nanjing China State Grid Jiangsu Electric Power Co. Ltd Nanjing China State Grid Information & Telecommunication Branch Beijing China

ISBN: (数字)9798331517090

ISBN: (纸本)9798331517106

The security data processing module in the existing blockchain is difficult to deal with malicious behavior that exploits the flaw. In order to reduce security risks, the research carries out innovation from the aspects of logic correct verification, computing architecture and computing mode, and implements network security protection for each layer based on Merkel tree to solve the problem that existing vulnerabilities and defects are not exploited by attackers, and proposes a cloud-edge-end multi-level collaborative security architecture with unified attack and defense. The results show that the proposed scheme can actively defend against the known attacks of the authentication key agreement protocol, and can overcome the shortcomings of the other four systems such as the lack of pre-validation and replay attacks. The calculation cost of the proposed scheme in the research is 21.039ms at the resource-limited terminal, 3.285ms at the edge server, and the total calculation time in the authentication stage is 24.324ms, which is lower than the other four schemes. This research can provide computing environment planning and safeguard measures for safe operation for edge-cloud-end security protection.

关键词： Cross layer design Costs Protocols Collaboration Authentication Computer architecture Blockchains Security protection Certification

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Research and Application of Electronic Data Retrieval in Material Supply Chain Enhanced by Large Language Models and Knowledge Graph

Research and Application of Electronic Data Retrieval in Mat...

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Information technology, Communication Ecosystem and Management (ITCEM), International Conference on

作者： Xing Ge Yafei Liu Pei Yang Xin Sun Junfeng Qiao Luyao Qu Jingyi Qiu State Grid Jiangsu Electric Power CO. LTD. Material Branch Nanjing China State Grid Laboratory of Power cyber-Security Protection and Monitoring Technology & China Electric Power Research Institute Beijing China

ISBN: (数字)9798331542696

ISBN: (纸本)9798331542702

In response to the new goals of building green and modern smart supply chains, the electric power equipment supply chain is experiencing a shift toward digital intelligence and low-carbon, environmentally friendly development [1]. However, traditional search platforms based on relational databases face challenges in handling vast amounts of multimodal electronic data. These platforms often suffer from low search accuracy, limited cross-dimensional correlation analysis capabilities, and inefficiencies, making them inadequate for constructing comprehensive big data platforms that integrate and share information across the entire green, modern, smart supply chain. This paper introduces an innovative electronic data retrieval method designed to meet the data retrieval needs of material supply chains. By integrating large language models with knowledge graph technology, it proposes an electronic data retrieval system that leverages vector database technology for text embedding of multimodal data. Additionally, artificial intelligence is used to enable knowledge retrieval and augmented generation, significantly enhancing data retrieval capabilities within the specialized domain of material supply chains.

关键词： Green buildings Large language models Supply chains Knowledge graphs Relational databases Data retrieval Vectors power systems Information technology Faces

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Semi-supervised power Microservices Log Anomaly Detection Based on BiLSTM and BERT with Attention

Semi-supervised Power Microservices Log Anomaly Detection Ba...

引用

Advanced Electronics, Electrical and Green Energy (AEEGE), International Conference on

作者： Dai Zaojian Li Yong Chen Mu Chen Liang Fang Wengao Lu Ziang State Grid Smart Grid Research Institute Co. Ltd. State Grid Laboratory of Power cyber-Security Protection and Monitoring Technology Nanjing China

The software industry has seen a rise in the size and intricacy of software in recent years, leading to a growing concern about how to accurately identify, analyze, and pinpoint abnormal behavior that may occur during system operation. power system microservices are becoming increasingly popular as a way to manage and monitor the complex and distributed attributes of modern power grids. System logs of power system microservices are used to document the status of power system and important occurrences at crucial points in order to help with troubleshooting performance problems and malfunctions, which plays a crucial role in maintaining the stability and reliability of power grids. Traditional anomaly detection methods based on white-box testing require access to the system source code and may not be applicable. Current abnormality detection methods based on system logs primarily focus on extracting log template characteristics, but they pay little attention to the semantic meaning of logs. In order to detect anomalies from system logs more effectively, this work proposes a log execution path anomaly detection method based on Bi-directional Long Short-Term Memory (BiLSTM) with attention. The semantics of log key is also taken into consideration using BERT model for semantic information extraction. Additionally, attention mechanism is used to adjust feature weights at different time steps and select important words. In training phase, a sliding window generates log key sequences from parsed logs to train the model. In detection phase, the model takes as input the parsed log sequence and outputs the probability distribution of the next log key. Experimental results indicate that the proposed method has outperformed conventional approaches on several metrics, including recall rate and F1 score.

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User Identification based on Behavior Feature Analysis

User Identification based on Behavior Feature Analysis

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2023 7th International Conference on Electrical, Mechanical and Computer Engineering (ICEMCE)

作者： Yuwen Dai Peng Zhang Tianqi Wu Hongbin Wu Daojuan Zhang Zhuo Lv Cen Chen State Grid Laboratory of Power Cyber-Security Protection and Monitoring Technology State Grid Smart Grid Research Institute co. Ltd Beijing China State Grid Laboratory of Power Monitoring System Cyber Security Technical Standard Verification State Grid Henan Electric Power Research Institute Beijing China

The issue of identity management and information security in cyberspace is becoming increasingly important, and the issue of how to effectively identify through user behavior urgently needs to be addressed. At present, biometric recognition technologies have certain limitations. This article combines deep learning methods and uses the BERT model to extract input text information features to generate word vectors. It uses a bidirectional GRU network with local and global attention mechanisms for training, and finally uses a softmax classifier to classify the user identity recognition model. The model in this article has significantly improved its performance in user identity recognition tasks based on behavioral features.

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Research on the Integration and Fusion technology of Distribution Network Data Resources Considering New Energy 23

Research on the Integration and Fusion Technology of Distrib...

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Proceedings of the 6th International Conference on Information Technologies and Electrical Engineering

作者： Junfeng Qiao Aihua Zhou Lin Peng Yiqing Wang Xiaofeng Shen Sen Pan Pei Yang State Grid Laboratory of Power cyber-Security Protection and Monitoring Technology State Grid Smart Grid Research Institute Co. LTD China Xuzhou Power Supply Company of State Grid Jiangsu Electric Power Co. LTD China Qingpu Power Supply Company of State Grid Shanghai Municipal Electric Power Company China

ISBN: (纸本)9798400708299

The essence of the construction and development of new power systems is to improve the functionality and performance of existing power systems, and the distribution network is the key to the functionality of the power system. Therefore, the upgrading and optimization of the distribution network is the key to the success of the modern energy revolution, and the development of the distribution network is also faced with management and technical challenges brought by new equipment and resources. This article proposes a distribution network data resource integration and fusion method that takes into account new energy, integrating the constantly emerging new power equipment and facilities as well as their corresponding data resources into existing power information management systems. Using the integrated distribution network data platform as the data base to support the deepening and development of distribution network business applications. Firstly, the data description characteristics of the new power equipment and facilities are sorted out, and the description rule system is extracted using the methods of power equivalence processing and equipment profiling. Due to the lack of standardized description rules for new energy equipment, it is necessary to reorganize and construct a corresponding description rule system. Then map and correspond its description rules with existing power information description rules, find its mapping method, and build a mapping rule library. Finally, based on the mapping rule library, the fusion of new energy data and existing distribution network data resources is achieved, and the accuracy and applicability of data resource fusion are verified by selecting real data from business application scenarios.

关键词： Application validation Data mapping rules Data resource integration Distribution network New energy

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Microservice Anomaly monitoring Method based on Multi-dimensional Spatiotemporal Feature Reconstruction

Microservice Anomaly Monitoring Method based on Multi-dimens...

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Artificial Intelligence and Intelligent Manufacturing (AIIM), International Symposium on

作者： Jing Zeng Ji Lai Shuo Li Xian Li Ruxia Yang Information Communication Branch State Grid Jibei Electric Power Co. Ltd. Beijing China State Grid Laboratory of Power cyber-Security Protection and Monitoring Technology China Electric Power Research Institute Nanjing China

ISBN: (数字)9798331541729

ISBN: (纸本)9798331541736

In a modern microservice architecture, the largescale distribution of services and high concurrency access make anomaly monitoring particularly complex. Traditional monitoring methods usually rely on a single data dimension, such as request delay or resource utilization, making capturing complex abnormal patterns challenging. Therefore, this paper proposes a microservice anomaly monitoring method based on multidimensional spatiotemporal feature reconstruction, aiming to reconstruct the complete feature space by integrating different data sources to improve the accuracy and robustness of anomaly detection. This paper’s method first extracts adequate data, such as service response time and service call chain from the tracking dataset, with time and space as the core and constructs it into a multi-dimensional feature matrix, fully considering the spatial and temporal correlation between microservices. Second, this paper introduces a deep learning model combining convolutional neural networks and gated recurrent cells to capture dynamic dependence and feature interactions in spatiotemporal dimensions. The convolutional neural network module extracts the spatial dependence through the convolution operation, while the gating cycle unit module captures the changing trend of the time series. By paralleling two modules and introducing the attention mechanism, the model is optimized with the reconstruction error, and finally, the network abnormality is judged by setting the threshold.

关键词： Adaptation models Attention mechanisms Microservice architectures Computer architecture Feature extraction Robustness Spatiotemporal phenomena Convolutional neural networks monitoring Anomaly detection

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Multi Domain Ontology Model Fusion and Interoperability Method of Digital Twin in Distribution Network 24

Multi Domain Ontology Model Fusion and Interoperability Meth...

引用

Proceedings of the 7th International Conference on Information Technologies and Electrical Engineering

作者： Gang Wang He Wang Min Xu Aihua Zhou Hai Yu Zhonghao Qian State Grid Smart Grid Research Institute CO. LTD Nanjing Jiangsu China State Grid Laboratory of Power cyber-Security Protection and Monitoring Technology Nanjing Jiangsu China State Grid Jiangsu Electric Power Co. Ltd. Nantong Power Supply Branch Nantong Jiangsu China

ISBN: (纸本)9798400707087

The digital twin of distribution network covers models including topology, geography, space, production, operation, control, measurement, marketing, electric field, etc. There is no unified rule framework for multi domain ontology modeling methods, and there is an urgent need for model fusion and comprehensive utilization. This article focuses on the cross domain joint modeling problem of distribution network ontology, conducts research on the fusion method of multi domain ontology models of distribution network digital twins, proposes a multi type model resource fusion and comprehensive utilization method with equipment and facilities as the core, integrates business models and power grid models, studies multi domain ontology model fusion interoperability technology for digital twins, and realizes the comprehensive utilization of distribution network digital twin model resources.

关键词： Digital twin

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Attack-Aware Capability Assessment Method Based on Specific Semantic Search

Attack-Aware Capability Assessment Method Based on Specific ...

引用

International Conference on Electronic Engineering and Informatics (EEI)

作者： Daojuan Zhang Qi Zhao Yuman Wang Shu Li Zheng Tian Yizhen Sun State Grid Laboratory of Power Cyber-Security Protection and Monitoring Technology State Grid Smart Grid Research Institute co. Ltd Beijing China Hunan Provincial Key Laboratory of Internet of Things in Electricity State Grid information & Communication Company of Hunan Electric Power Corporation Changsha China

ISBN: (数字)9798350353594

ISBN: (纸本)9798350353600

In this paper, we propose an attack perception capability assessment method based on the specific semantic search for the problem of attack perception capability assessment of security protection equipment for power monitoring systems. The method aims to improve the recognition and localization accuracy of common attacks by accurately correlating the output products of security equipment with the execution of attack test cases. The research employs an attack-specific semantic generation technique that combines attack attribute values with timestamps to form specific semantics for subsequent matching. Pattern matching algorithm, specifically the BM (Boyer-Moore) algorithm, is further utilized to match the specific semantics with the output products of the security device Snort to achieve attack localization. Experimental results demonstrate that Snort exhibits high accuracy in perceiving the majority of attack types and exhibits an enhanced perception rate compared to certain baseline methods. In summary, the method proposed in this paper effectively improves the sensing ability of security equipment to attacks on the power monitoring system and provides a new idea for the performance evaluation of security protection equipment.

关键词： Location awareness Performance evaluation Accuracy Semantic search Sensors Security protection Informatics monitoring Pattern matching

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Lightweight Blockchain-based Identity Authentication Scheme for power Terminal

Lightweight Blockchain-based Identity Authentication Scheme ...

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Electrical Engineering and Control Science (IC2ECS), International Conference on

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

In recent years, the construction of the power Internet of Things continues to advance, and the number of power terminal equipment is growing. However, the computing power and storage capacity of these terminal devices are limited, and the current blockchain-based identity authentication scheme has high requirements for computing and storage resources, limiting the participation of power terminal equipment with weak computing power and small storage space. Aiming at the problem that resource-limited power terminal equipment cannot join the blockchain, a lightweight consensus algorithm for power terminals is proposed, and a power terminal authentication scheme based on the lightweight consensus algorithm is designed to make up for the defect that resource-limited power terminal equipment does not support the use of blockchain. The security analysis shows that the scheme can effectively resist many kinds of network attacks and meet the security requirements of power terminal equipment. Performance analysis shows that the scheme has low computation cost and conforms to the principle of lightweight.

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Research on power System Cyber Security Defense based on ATT&CK Framework

Research on Power System Cyber Security Defense based on ATT...

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Energy Engineering and power Systems (EEPS), International Conference on

作者： Tengyan Wang Yuanyuan Ma Zhipeng Shao Zheng Xu State Grid Laboratory of Power Cyber-Security Protection and Monitoring Technology State Grid Smart Grid Research Institute Co. Ltd Nanjing China State Grid Shandong Electric Power Company Jinan China

Advanced persistent threat (APT) attack is one of the most serious threats to power system cyber security. ATT&CK framework integrates the known historical and practical APT attack tactics and techniques to form a general language for describing hacker behavior and an abstract knowledge base framework for hacker attacks. Combined with the ATT&CK for ICS framework, this paper combed the known attack techniques used by viruses or hacker groups aimed at cyberattacks on infrastructure, especially power systems. Then found the corresponding mitigations for each attack technique, and merged them. Next, we listed the high frequency and important mitigations for reference. At last, we proposed a cyber security defense model suitable for ICS to provide a reference for security teams on how to apply ATT&CK and other similar cyberattack frameworks.

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