active distribution network, cyber physical system, network attack, FP-Growth algorithm, event sequence, Telecommunication, TK5101-6720, Technology

In order to effectively analyze and identify the cyber physical system (CPS) status of active distribution network, a network attack detection method based on FP-Growth algorithm for active distribution network cyber physical system was proposed. Firstly, the active distribution network control model considering network attack and the impact mechanism of CPS network attack were analyzed, and the raw data was obtained by monitoring the CPS information side and physical side of the active distribution network through the real-time simulation platform. Then, the data discretization rules were formulated through the rated voltage and current values, and the original data were discretized and quantized according to the rules to generate event sequences. On this basis, the FP-Growth algorithm was used to mine the frequent items and strong correlations of abnormal signals in historical data, and new attack categories and fault points were identified through the existing frequent sequence features. The detection of CPS network attack on active distribution network was realized. Finally, the feasibility and effectiveness of the proposed method were verified by a simulation experiment.