Research on Edge Intelligence-based Security Analysis Method for Power Operation System

2020 7th IEEE International Conference on Cyber Security and Cloud Computing (CSCloud)/2020 6th IEEE International
Conference on Edge Computing and Scalable Cloud (EdgeCom)
Research on Edge Intelligence-based Security Analysis Method for Power Operation System
Zheng Zhu¹, Yingjie Tian¹, Fan Li¹, Hongshan Yang², Zheng Ma³, and Guoping Rong⁴
Shanghai Electric Power Research Institute, Shanghai, China
²Transwarp Inc, Shanghai, China
³The Maersk Mc-Kinney Moller Institute, University of Southern Denmark, Odense, Denmark
⁴Software Institute, Nanjing University, Nanjing, China
Email: {zheng.zhu, yingjie.tian, li.fan}@sh.sgcc.com.cn, [e-mail],
[e-mail],[e-mail]

978-1-7281-6550-9/20/$31.00 ©2020 IEEE 258
DOI 10.1109/CSCloud-EdgeCom49738.2020.00052


Abstract—At present, the on-site safety problems of substations and critical power equipment are mainly through inspection methods. Still, manual inspection is difficult, time-consuming, and uninterrupted inspection is not possible. The current safety management is mainly guaranteed by rules and regulations and standardized operating procedures. In the on-site environment, it is very dependent on manual execution and confirmation, and the requirements for safety supervision and operating personnel are relatively high. However, the reliability , the continuity of control and patrol cannot be fully guaranteed, and it is easy to cause security vulnerabilities and cause security accidents due to personnel slackness. In response to this shortcoming, this paper uses edge computing and image processing techniques to discover security risks in time and designs a deep convolution attention mechanism network to perform image processing. Then the network is cropped and compressed so that it can be processed at the edge, and the results are aggregated to the cloud for unified management. A comprehensive security assessment module is designed in the cloud to conduct an overall risk assessment of the results reported by all edges, and give an alarm prompt. The experimental results in the real environment show the effectiveness of this method.