Research on Intrusion Detection Technology of Computing Nodes in Digital Power Grid based on Artificial Intelligence

• Published in: EAI endorsed transactions on scalable information systems p. e20
• Main Authors: Lin, Xubin, Zhang, Situo, Hu, Feifei, Wu, Liu
• Format: Journal Article
• Language: English
• Published: 01.01.2023
• ISSN: 2032-9407; 2032-9407
• DOI: 10.4108/eetsis.v10i3.3092

This paper aims to investigate an intrusion detection network for digital power grid networks, which consists of an edge server and two computational nodes that work collaboratively to detect any potential intrusion in the network. The primary objective of this study is to enhance the effectiveness of intrusion detection in the network. To achieve this objective, we first define the outage probability of the intrusion detection system under consideration. This is done to provide a measure of the probability that the system fails to detect an intrusion when it occurs. We then derive a closed-form expression for the outage probability to enable further analysis on the system behavior. Since the system resources, such as transmit power, are limited, we further design a transmit power allocation strategy to improve the system performance. This strategy seeks to optimize the allocation of transmit power across the different nodes of the intrusion detection network to maximize the likelihood of detecting intrusions while minimizing the resource usage. Finally, to evaluate the performance of the proposed system, we conduct simulations and provide results that demonstrate the accuracy of the closed-form expression and the effectiveness of the transmit power allocation strategy. These simulation results serve as evidence of the efficacy of the proposed approach in detecting intrusions in a resource-constrained network, especially for the digital power grid networks.