Abstract
IoT security is very crucial to IoT applications, and security situational awareness can assess the overall security status of the IoT. Traditional situational awareness methods only consider the unilateral impact of attack or defense, but lackconsideration of joint actions by both parties. Applying game theory to security situational awareness can measure the impact of the opposition and interdependence of the offensive and defensive parties. This paper proposes an IoT security situational awareness method based on Q-Learning and Bayesian game. Through Q-Learning update, the long-term benefits of action strategies in specific states were obtained, and static Bayesian game methods were used to solve the Bayesian Nash Equilibrium of participants of different types. The proposed method comprehensively considers offensive and defensive actions, obtains optimal defense decisions in multi-state and multi-type situations, and evaluates security situation. Experimental results prove the effectiveness of this method.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
