Security Strategy For Power Terminal In Smart Grid

As the next generation of the power system,smart grid develops towards automated and intellectualized.Along with the benefits brought by smart grids,e.g.,improved energy conversion rate,power utilization rate,and power supply quality,are the security challenges.In the smart grid,the power terminal plays a pivotal role in controlling,monitoring,and regulating the production process of electricity.Therefore,the most important security issue in the smart grid is to ensure the safety of power terminals.Existing methods usually monitor the power terminals by monitoring the power terminal traffic.However,those strategies can only detect the attack behaviors that are reflected on the traffic patterns,so they cannot be applied in today's smart grids directly.To address it,we propose a security monitoring mechanism for power terminals based on deep learning,which provides comprehensive protection for power terminals from both the equipment level and the network level.At the equipment level,we monitor the side channel information of the power terminal,and map it with the working state through data mining,to realize non-invasive security monitoring for power terminals.At the network level,we explore the mode of the attack message targeting at power terminals through deep neural network(DNN),and realize the network level security monitoring of power terminals through feature engineering and data enhancement.We built a physical simulation platform to verify the feasibility of the proposed method and the evaluation results show that the proposed strategy can improve the safety level of the power terminal.