NETWORK ATTACK PATH PREDICTION BASED ON VULNERABILITY DATA AND KNOWLEDGE GRAPH

摘要

With the increase in network security problems, accurately predicting the possible attack path of an attacker and fixing bugs has become a concern of network security administrators. To overcome the shortcomings of existing methods that mainly focus on the path prediction under the ideal attack scenario and ignore the key position of nodes in the network, a network attack path prediction method based on knowledge graph and attack graph model is proposed, which takes the knowledge graph as the core, uses CVSS's quantitative indicators for a single vulnerability, and combines the network security evaluation method to calculate the possible path. Experimental results show that this method can evaluate the security risk value of networks and nodes, which can point out the possible attack path of the attacker and calculate the risk value of the corresponding path. It can also rank the network node on the path and give repair suggestions. Hence, this method can provide a basis for the implementation of security protection strategies.