Vulnerability association evaluation of Internet of thing devices based on attack graph

Abstract

Device vulnerabilities emerge one after another in the Internet of thing environment, the attackers attack vulnerabilities on several low-level devices simultaneously by multi-step attack method to trigger the vulnerabilities on other high-level devices to damage or control the information system. Considering the correlation between device vulnerabilities, we proposed a method based on attack graph to evaluate vulnerability risk in order to ensure Internet of thing network security. First, according to the type, version, and other relevant information of device vulnerabilities in the Internet of thing environment, hidden Markov model can be used to model the association between device states. Second, analyze the possible attacks on the vulnerabilities on the device, and generate the attack graph according to the correlation between the device states and the relevant information of the vulnerabilities in the device. Finally, the vulnerabilities are objectively and accurately evaluated according to the attack graph. The experiments results show that the proposed method can map the relationship between devices more accurately and objectively and improve the efficiency and accuracy of the vulnerability evaluation.