Biblio

Cyberspace is vulnerable to continuous malicious attacks. Traceability of network attacks is an effective defense means to curb and counter network attacks. In this paper, the evolutionary game model is used to analyze the network attack and defense behavior. On the basis of the quantification of attack and defense benefits, the replication dynamic learning mechanism is used to describe the change process of the selection probability of attack and defense strategies, and finally the evolutionary stability strategies and their solution curves of both sides are obtained. On this basis, the attack behavior is analyzed, and the probability curve of attack strategy and the optimal attack strategy are obtained, so as to realize the effective traceability of attack behavior.

Advanced Persistent Threat (APT) attack has the characteristics of complex attack means, long duration and great harmfulness. Based on the idea of dynamic deception, the paper proposed an APT defense system framework, and analyzed the deception defense process. The paper proposed a hybrid encryption communication mechanism based on socket, a dynamic IP address generation method based on SM4, a dynamic timing selection method based on Viterbi algorithm and a dynamic policy allocation mechanism based on DHCPv6. Tests show that the defense system can dynamically change and effectively defense APT attacks.