An Attack defense Stochastic Game Approach for Malicious Nodes in MANETs
Attack prediction is very critical for cyber homeland security. This project presents an attack defense stochastic game approach that focuses on active defense using the Attack Defense Stochastic Game (ADSG) model. The interactions between the attacker and the defender is taken as two players. Second is to present Markov chain for privilege model to predict attacker's behavior and strategies. Third one is to present new privilege escalating attack taxonomy, with respect to the attacker's privileges elevation from lower level to higher level. Finally the work is systematically identifies cost factors of cost sensitive model and introduces the attack strategies prediction and optimal active defense strategy decision algorithm. Game theoretical analysis is useful for decision, analyzing, modeling, and control processes to provide network security.