| Title | Traceability Method of Network Attack Based on Evolutionary Game |
| Publication Type | Conference Paper |
| Year of Publication | 2022 |
| Authors | Zhang, Hengwei, Zhang, Xiaoning, Sun, Pengyu, Liu, Xiaohu, Ma, Junqiang, Zhang, Yuchen |
| Conference Name | 2022 International Conference on Networking and Network Applications (NaNA) |
| Keywords | Analytical models, attack and defense strategy, Behavioral sciences, Cyberspace, Evolutionary Game, game theoretic security, Games, Human Behavior, human factors, Learning systems, Metrics, Network security, pubcrawl, replicator dynamics, Scalability, Stability analysis, traceback |
| Abstract | 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. |
| DOI | 10.1109/NaNA56854.2022.00046 |
| Citation Key | zhang_traceability_2022 |
Traceability Method of Network Attack Based on Evolutionary Game