Robust deployment strategy for security data collection agent

Abstract

With the frequent occurrence of “network black production” incidents,attackers strategically launch target attacks with the idea of “profit-seeking”.Existing network monitoring systems lack accurate and effective monitoring strategies for “strategic attacks”.Therefore,in an adversarial environment,how to optimize the deployment of collection agents for better monitoring results becomes an extremely important issue.Based on this,a robust deployment strategy of collection agents was proposed for the above mentioned problem.Firstly,the idea of attack-defense game was introduced to measure the collection agents,threat events and their relations,then the MADG model was built.Secondly,considering that the traditional accurate solution algorithm cannot solve the problem,the robust acquisition agent deployment algorithm called RCD algorithm was designed to approximate the problem by using the sub-module and non-growths of the objective function.Finally,the RCD algorithm was verified.The experimental results show that the above model and method is feasible,effective and expandable.

Keywords

• collection agent;security data;defender-attacker game theory;robust;deployment strategy