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2023 International Conference on Computer Application and Information security, ICCAIS 2023

作者： Huang, Xiuli Zhu, Hongbin Yu, Pengfei Zhai, Yujia State Grid Laboratory of Power cyber-Security Protection and Monitoring Technology State Grid Smart Grid Research Institute Co. Ltd. No.8 NanRui Road Gulou District Jiangsu Nanjing China Big Data Center of State Grid Corporation of China China Reinsurance Building No.18 Luoma St. Xicheng District Beijing China

ISBN: (纸本)9781510675032

To obtain carbon peaking and carbon neutrality goals, it is necessary to establish a national carbon emission platform for monitoring and reporting carbon dioxide equivalent. Energy data contains a good deal of important data and hence is required to be securely shared. Secure data aggregation solutions are an effective method that enables the process of adding up the contributions from several parties without revealing their inputs. Most of these solutions can be achieved using Paillier encryption, which inherently has multiple rounds of communication for aggregating ciphertexts. In this work, we present a privacy-preserving and verifiable secure data aggregation for a national carbon emissions monitoring service system, which can be verifiable encryption. To achieve verification, we apply zero-knowledge proofs to enable underlying threshold encryption and bilinear aggregate signature to detect the validity of the summation results. Finally, we show the correctness, verification, and informal security analysis of our solution. Compared with the existing scheme, our work can reduce the number of rounds for aggregating ciphertexts and is suitable for the national carbon emission platform. © 2024 SPIE.

关键词： Carbon dioxide

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Research on interconnection technology of heterogeneous platforms for privacy computing for energy big data

Research on interconnection technology of heterogeneous plat...

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Energy and power Engineering, Control Engineering (EPECE), International Conference on

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

ISBN: (数字)9798350366099

ISBN: (纸本)9798350366105

Energy data, especially power data, has the advantages of covering a wide range of industries, high value density, and good accuracy, relying on energy big data can widely describe all kinds of terminal production and life activities. However, the privacy computing platforms of various vendors often adopt different technical architectures and algorithm protocols in the early implementation process, which makes the implementation of various platforms have great differences, resulting in the direct interconnection between heterogeneous privacy computing platforms of various organizations. Aiming at the interoperability needs and problems of energy big data privacy computing platforms with different technical architectures, this paper decouple the management plane and data plane of the privacy computing platform, and in accordance with the principle of business priority, proposes a new privacy computing interconnection model of “unified business collaboration component + flexible configuration algorithm engine” suitable for energy big data. Through the design of the east-west and North-South interface framework of the privacy computing platform and the security access principle of the algorithm engine, the whole process control, cross-platform interconnection, and internal and external network penetration modeling and analysis of energy big data collaboration with the outside world are realized, which meets the key data security protection requirements of the state grid such as distributed computing and storage of data inside and outside the platform. It is of great significance to promote energy big data to empower external institutions such as governments, banks and operators.

关键词： Data privacy Privacy Computational modeling Government Collaboration Computer architecture Big Data

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Deep Learning-Based Control Model for Electronic Evidence Access Rights 4

Deep Learning-Based Control Model for Electronic Evidence Ac...

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4th International Conference on Information Science, Parallel and Distributed Systems, ISPDS 2023

作者： Chen, Peng Li, Yongliang Gao, Xianzhou State Grid Ningxia Electric Power Co.Ltd. Ningxia750001 China State Grid Ningxia Electric Power Co.Ltd. Electric Power Research Institute Ningxia750002 China State Grid Smart Grid Research Institute Co. Ltd. Nanjing210003 China State Grid Laboratory of Power Cyber-Security Protection and Monitoring Technology Nanjing210003 China

ISBN: (纸本)9798350337181

With the rapid development of digitalization and intelligence in smart grids, how to identify untrusted users in the electric power system and implement user access control based on electronic evidence has become an important research topic. A credible assessment needs to be made on the subject users accessing electronic evidence. In this paper, we propose a deep learning-based user multi-dimensional attribute feature extraction access control model, which considers multi-dimensional attribute features such as user identity, behaviour, and device information, and determines whether the user is a legitimate access user by using CNN-Transformer deep learning framework to extract user features and determine their trust value. Through simulation experiments, it is proved that the access permission control model proposed in this paper has high accuracy and reliability and can meet the access requirements of different electronic evidence users. © 2023 IEEE.

关键词： Smart power grids

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A Multi-source Log Hidden Anomaly Detection Method Integrating Trans-Encoder and LSTM

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IEEE Access 2025年

作者： Luo, Chen Jiang, Hongcheng Zhou, Peng Wang, Xinzhe Shao, Zhipeng Sun, Wangshu State Grid Laboratory of Power Cyber-Security Protection and Monitoring Technology China Electric Power Research Institute Jiangsu Nanjing210003 China State Grid Zhejiang Electric Power CO. Ltd Zhejiang Hangzhou310007 China

Identifying hidden anomalous behavior is a major challenge in anomaly detection, particularly in complex systems where anomalies are buried within massive log data and cannot be easily identified through simple patterns or rules. To address this issue, we propose a novel approach that integrates a Transformer encoder module with Long Short-Term Memory (LSTM) to detect covert anomalies in logs using only normal class datasets for training. First, we enhance feature extraction from multi-source log data by improving the Transformer encoder structure with an added masking mechanism. Then, we apply LSTM for time-series modeling to capture temporal correlations between extracted features, improving the model’s ability to analyze sequential dependencies. Finally, we evaluate the semantic and temporal consistency of operations to refine anomaly detection. Experimental results demonstrate that our approach effectively detects hidden anomalies, achieving improvements of 2.3% in precision, 4.9% in recall, and 3.4% in F1 score. Moreover, it maintains stable performance with just 10% of the training data and improves computational efficiency in the test phase by 16.98% compared to DeepLog, highlighting its potential for practical application in anomaly detection. © 2013 IEEE.

关键词： Unsupervised learning

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Enhancing Cross-Domain Access Efficiency in Zero-Trust Scenarios Oriented to the Access Process

Enhancing Cross-Domain Access Efficiency in Zero-Trust Scena...

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Electrical Automation and Artificial Intelligence (ICEAAI), International Conference on

作者： Xian Li Shijun Zhang Jing Zeng Shuo Li Ruxia Yang State Grid Jibei Information & Telecommunication Company State Grid Beijing China State Grid Laboratory of Power cyber-Security Protection and Monitoring Technology China Electric Power Research Institute Nanjing China

ISBN: (数字)9798331506797

ISBN: (纸本)9798331506803

During cross-domain access, both communication ends need zero-trust evaluation by the trust assessment node and policy matching for permission. Nodes handling these may face concurrent computing and policy search tasks that need to be performed. We propose a new method to enhance security and efficiency. By introducing a trust hash value from access-end features and optimizing the policy tree, along with a better trust calc method, experiments show improved cross-domain access efficiency and accuracy, offering a new view for power grid services.

关键词： Concurrent computing Accuracy Automation power system dynamics Decision making Process control Authentication power grids Zero Trust Faces

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A Zero-Shot Learning-Based Detection Model Against Zero-Day Attacks in IoT

A Zero-Shot Learning-Based Detection Model Against Zero-Day ...

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Electronic technology and Information Science (ICETIS), International Conference on

作者： Xueqin Gao Kai Chen Yufei Zhao Peng Zhang Longxi Han Daojuan Zhang SGRI Power Grid Digitizing Technology Department State Grid Laboratory of Power Cyber-Security Protection and Monitoring Technology State Grid Smart Grid Research Institute co. Ltd Beijing China

ISBN: (数字)9798350388343

ISBN: (纸本)9798350388350

With the large-scale deployment of loT devices, loT security faces huge threats from zero-day attacks, and there is an urgent need to conduct research on loT zero-day attack detection technologies. Aiming at the problem of lack of available samples for zero-day attack detection in loT, we propose a zero-day attack detection method based on generative zero-shot learning. Feature extraction is performed based on the LightGBM model, and then multi-layer perceptron is used to generate attribute vectors. We generate pseudo feature space of data category based on conditional variational autoencoders to train zero-day attack detectors. To comply with real attack detection scenarios, we adopt the generalized zero-shot learning method to conduct verification on the UNSW-NB15 data set. Experiment results show that the precision, recall and Fl of most attack types are above 90%. The average accuracy of our method in detecting zero-day attacks is 93.6%, which is much higher than the baseline method and achieve great detection results.

关键词： Information science Accuracy Zero-shot learning Detectors Feature extraction Vectors security

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Research on Digital Twin Modeling technology for Distribution Networks Integrating Multiple Digital Resources 3

Research on Digital Twin Modeling Technology for Distributio...

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3rd International Conference on Intelligent Computing, Communication and Convergence, ICI3C 2023

作者： Qiao, Junfeng Zhou, Aihua Peng, Lin Su, Hang Qian, Zhonghao Xu, Min Pan, Sen Yang, Pei State Grid Laboratory of Power Cyber-Security Protection and Monitoring Technology State Grid Smart Grid Research Institute Co. Ltd Jiangsu Nanjing210003 China Xuzhou Power Supply Company State Grid Jiangsu Electric Power Co. Ltd Jiangsu Xuzhou221005 China Nantong Power Supply Company State Grid Jiangsu Electric Power Co. Ltd Jiangsu Nantong226006 China

ISBN: (纸本)9798350343922

The sources of digital resources in the distribution network mainly include three aspects: equipment ontology, production operation, and management. The data is described in various forms and stored in various types of systems and data platforms. However, with the continuous development and upgrading of distribution network business, the fusion of diverse data resources to drive decision-making has become a current development trend. Therefore, how to integrate and apply diverse digital resources is the key to the current development of distribution networks. In response to this issue, the article proposes a digital twin modeling technique for distribution networks that integrates multiple digital resources. Firstly, build a cross platform data mapping system based on the production and operation data management rules of the distribution network, and then use data access and integration technology to integrate diverse data resources into a unified data platform. Utilize the unified data model of the power grid to align multiple data resources and map the aligned data resources to the digital twin model. Simultaneously defining data synchronization update interfaces to ensure real-time and accurate data in the digital twin model. Finally, a typical scenario application of the distribution network based on the digital twin model is carried out to verify the effectiveness and practicality of the model. © 2023 IEEE.

关键词： digital resources digital twin mapping distribution network digital twin model distribution network operation management integration of diverse digital resources

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Research and Application of Reconfigurable Computing Approaches in power Network security Processing

Research and Application of Reconfigurable Computing Approac...

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New Energy and power Engineering (ICNEPE), International Conference on

作者： Xiaojuan Guan Chen Wang Cheng Zhou Sheng Zhu State Grid Laboratory of Power Cyber-Security Protection and Monitoring Technology China Electric Power Research Institute Co. Ltd Nanjing China

ISBN: (数字)9798331516086

ISBN: (纸本)9798331516093

Given the issue that certain key components of the dedicated security protection equipment for the power system rely heavily on large-scale imported FPGA chips and specialized integrated circuits, and mature domestic alternatives and solutions have not yet been formed, this paper proposes the application concept of reconfigurable computing technology in the process of high-performance network security processing. The reconfigurable CGRA chip is led by China, with independently controllable technology, combining energy efficiency and flexibility, enabling efficient processing of computation-intensive tasks and completing the substitution for foreign FPGA chips.

关键词： Computers power engineering Process control Switches Network security Energy efficiency power systems Computational efficiency protection Field programmable gate arrays

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Research on Heterogeneous Computing technology Based on Domestic CPUs and Reconfigurable Chips

Research on Heterogeneous Computing Technology Based on Dome...

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Intelligent power and Systems (ICIPS), International Conference on

作者： Xiaojuan Guan Chen Wang Cheng Zhou Sheng Zhu State Grid Laboratory of Power Cyber-Security Protection and Monitoring Technology China Electric Power Research Institute Co. Ltd Nanjing China

ISBN: (数字)9798331532765

ISBN: (纸本)9798331532772

In view of the performance and security problems existing after the replacement of specialized security protection equipment for power grids with domestic software and hardware, and in response to the security protection requirements of different application scenarios, the research on heterogeneous fusion computing technology based on domestic CPUs and reconfigurable chips is proposed. The optimal mapping of national secret algorithms, isolation exchange, protocol processing, and data analysis on reconfigurable chips is realized, supporting the parallel computing of special processors for scene acceleration and domestic CPUs, and meeting the requirements of different network security analysis and computing scenarios in the power system.

关键词： Protocols Program processors Data analysis Software algorithms Heterogeneous networks power grids Hardware Encryption security protection

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Research and Application of Constructing a Comprehensive Dynamic Topology for Distribution Networks Based on a Real-Time Measurement Center 24

Research and Application of Constructing a Comprehensive Dyn...

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

作者： Pei Yang Min Xu Gang Wang State Grid Laboratory of Power cyber-Security Protection and Monitoring Technology Nanjing Jiangsu China State Grid Smart Grid Research Institute CO. LTD Nanjing Jiangsu China

ISBN: (纸本)9798400707087

With the rapid development of massive distributed energy resources integration and load demand-side response in the power grid, distribution network power flows have become bidirectional, and the grid topology has exhibited characteristics of complexity, high-dimensionality, and multi-state. This has created an urgent need for comprehensive dynamic topology service capabilities, bringing new challenges in areas such as topology data mapping, topology state synchronization, and full-domain topology computation. In response to these needs, this paper investigates the technology for constructing and maintaining power grid topology and proposes a method for constructing a comprehensive dynamic topology for distribution networks based on a real-time measurement center. By integrating measurement data with distribution network topology information, a fine-grained foundational topology model is constructed, which is then dynamically adjusted based on real-time switch state information to form a comprehensive dynamic topology. This approach effectively supports the business analysis needs of multiple dimensions and multiple time states, aiming to enhance the grid's response speed and processing performance.

关键词： Comprehensive Dynamic Topology

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