An Intrusion Intention Analysis Algorithm Based on Attack Graph

Abstract

The discovery of intrusion intention is one of the challenging tasks faced by network security managers. To detect intrusion detections, this paper presents a domain-device attack graph, and collects and analyzes the underlying data of the network topology. On this basis, the attack graph Map was quantified by the Bayesian theory. The minimum weight spanning tree (Min-WFS) algorithm was adopted to automatically recognize the calculation cost of key devices in the network topology, providing an important basis for network maintenance. Experimental results show that the intrusion intentions can be effectively identified with the aid of the quantified domain-device attack graph Map, and this identification method is easy to implement.