A cyber‐attack detection method for load control system based on cyber and physical layer crosscheck mechanism

Abstract

Cyber‐attack has become one of the main threats to the safe operation of the load control system in the distribution network. Currently, a large number of methods are developed to detect cyber‐attacks. However, most of these methods make decisions based on information from a single cyber layer or physical layer. If the decision is wrong, there is no way to verify it. Therefore, if the separate decisions can be made in the cyber layer and physical layer at the same time, and a final judgment is received throughout the two decisions, then the accuracy and credibility of cyber‐attack detection can be improved. First, the particle swarm optimization‐based backpropagation neural network is adopted to detect attacks in the cyber layer, at the same time, the criteria importance though intercrieria correlation‐based grey relational analysis is adopted for the assessment of node risk level in the physical layer. Then, based on the incidence matrix model between the cyber layer and the physical layer, a crosscheck mechanism is proposed to detect the cyber‐attack through the verification of the two decisions. Finally, taking the IEEE 33‐node system as an example, the validity of the proposed method to detect the denial of service attack is verified.

Dynamic load altering attack detection based on adaptive fading Kalman filter in smart grid

“…Smart grids are very complex, cyber-attacks may occur in any link of smart grids [7]. There are many kinds of cyber-attacks in smart grid, including integrity tampering [8], availability jamming [9], replay, wormhole [10], DoS [11], false data injection [12], password pilfering, masquerading [13] and other cyber-attacks [14,15].…”

Vulnerability assessment of cyber‐physical power systems considering failure propagation: A percolation‐based approach

“…Such interdependencies are beneficial for formulating smarter management strategies and promoting economic development, but also dramatically increase the vulnerability of systems [4] due to double threats from cyber-attacks (e.g. modern malware or malicious code) [5,6] and physical attacks (e.g. adversar-ial disruptions to substations or transmissions) [7].…”