Research on Intrusion Detection Model based on Optimized Bayesian Edge Network

As mobile intelligent terminals, wireless networks and distributed computing technologies mature and spread, more and more data is generated and distributed in the network environment, and the network structure is changing dynamically, the instability of data security is increasing. In order to solve this problem, it is necessary to improve the ability of data security defense in Edge network. Therefore, an optimized Bayesian edge computing intrusion detection algorithm model is established: according to the needs of Edge network characteristics, the current mainstream intrusion detection algorithms are studied and analyzed, RDC curve is used to analyze and compare the two indexes of the common intrusion detection algorithm: pass-true positive rate and false positive rate, the practicability of Bayesian classification algorithm in Edge network intrusion detection is verified by three indexes: accuracy, precision and recall.