A Defense Method for False Data Injection Attacks in Power System Networks Based on KNN Classification Algorithm
Previous methods for defending against false data injection attacks only calculate a single parameter of the attack mod-el,resulting in poor defense effectiveness.To this end,a defense method for false data injection attacks in power system net-works based on KNN classification algorithm is designed.A theoretical and mathematical model is designed for false data injec-tion attacks based on the characteristics of the attack data,and the complexity and performance parameters of the attack model are calculated.With the support of KNN classification algorithm,the distance between different defense nodes is calculated,and the confidence level of the nodes is described.Through information authentication,the position of the defense nodes is de-termined.The data transfer function and trend function of nodes are calculatd,different types of attacks are analyzed,and dif-ferent defense strategies are adopted.The experimental test results show that compared with traditional methods,the success rate of attack and intrusion and data loss rate are lower after applying this method,indicating that this method has better practi-cal application effect.
KNN classification algorithmpower systemfalse network datafalse data injection attackdefense method
万方数据
维普
