Network Node Resource Risk Assessment Based on SCM-ANFIS

Abstract

Network security has become a major concern to the people, the Adaptive Neuro Fuzzy Inference System (ANFIS) has intelligent features not available in conventional methods, can handle uncertainties, and has the ability to self-learn and acquire knowledge. This paper proposes a model for risk assessment of network node resources using ANFIS, which divides network behavior into normal behavior and attack behavior, and analyzes network changes such as traffic, CPU, disk, and memory resource occupancy; the risk level of the node resource, so as to get better accuracy. The experimental results show that the adaptive neuro fuzzy inference system (SCM-ANFIS) model based on subtractive clustering can better evaluate the resource risk of network nodes.