Quantum Bayesian Game Modeling for Intrusion Detection
Abstract
In cybersecurity, Intrusion detection plays a vital role in the network boundary detection. It develops the preventive measures for network defense. In this paper, it is presented the quantum cognition with the game theory strategy to detect the target attacks and normal packet classification in the network. The Quantum Bayesian game theory offers an efficient model of cognition to human rationality rather than the classical Bayesian game theory. This is inspired cognitive defense model in which a game modeling acts as the brain to determine the abnormal activity of network traffic rationally. It also analyzes the operation of the quantum game model between the attacker and defender detection system. The defender takes effective decision strategy in this model which maximizes their payoffs, according to the non-cooperative and incomplete imperfect information game strategy. Our modeling emphasized that quantum game theory is the effective dynamic solution, as a procedure of two player game to improve the probability of a defender issued a correct alarm and reduced the probability of defender issued a false alarm. It is as well to establish a rapid response of the system that uses in real time reconfiguration network security system.References
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