Network Attack Detection Method of Power Equipment Communication System based on FP-Growth Algorithm

With the continuous development of information and communication technology, the impact of network attacks on power communication equipment systems is gradually increasing. Malicious network attacks can be forged into normal network faults, making it difficult to detect and identify such attacks. It seriously threatens the operation safety of power equipment communication systems, resulting in paralysis of power equipment communication systems. In order to analyze and identify the state of power equipment communication system more effectively, this paper proposes a network attack detection method for power equipment communication system based on FP-Growth algorithm. Firstly, the transmission model of power equipment communication system is analyzed, and the physical side and communication side of power equipment communication system are monitored by real-time simulation platform to obtain the original data. Then, the data discretization rules are formulated through the rated voltage / current value, and the original data is discretized and quantified according to the rules. Then, the event sequence is generated by encoding the data, and then the FP-Growth algorithm is used to mine the frequent itemsets and strong correlation of the abnormal signal of the historical data. Through the existing frequent sequence features, the new attack categories and fault points are identified to realize the detection of network attacks in power equipment communication system. Finally, the feasibility and effectiveness of the proposed method are verified by simulation results.