LAUSR

Currently it becomes more difficult for a single intrusion detection system (IDS) to detect complex attacks. Based on some cooperative intrusion detection mechanisms, multiple IDSs increase the detection performance against network attacks by sharing their knowledge and consulting with each other. However, these related works hardly consider the IDS configuration optimization problem and the adaptive collaborative attack problem. In this paper, we first propose an advanced adaptive attack based on intrusion-sharing incentive mechanism to promote mutual consultation and collaboration among intelligent attackers; then in order to detect and defend this attack, an IDS intelligent configuration scheme based on evolutionary game is proposed, where each IDS in network can intelligently configure its detection libraries according to the related evolutionary stability strategy. Based on our experimental analysis, the proposed scheme can achieve optimal IDS configuration against the advanced adaptive attack, which is superior to other IDS configuration schemes.