Abstract
Smart Home brings a new people-oriented home life experience. However, the edge devices in this system are facing severe threats such as data security and equipment safety. To solve the above problems, this paper proposes an intrusion detection scheme based on repeated game. We first use the K-Nearest Neighbors (KNN) algorithm to classify edge devices and equip the intrusion detection system to cluster heads. Secondly, we use the regret minimization algorithm to determine the mixed strategy Nash equilibrium of the one-order game and then take a severe punishment strategy to domesticate malicious attackers. Thirdly, the intrusion detection system can detect malicious attackers by reduction of payoff. Finally, the detailed experimental results show that the proposed scheme can reduce the loss of attacked intrusion detection system and then achieve the purpose of defending against the attacker.
Highlights
Internet of things (IoT) is entering people’s lives and makes the production and life of human beings more intelligent and convenient
Mobile Information Systems as the repeated game and proposes an intrusion detection scheme based on repeated game to protect the security of Smart Home. e main contributions are as follows: (1) To reduce the cost of equipping the intrusion detection system, this paper uses the K-Nearest Neighbors (KNN) algorithm to classify edge devices and equips the intrusion detection system for cluster heads to achieve the purpose of protecting Smart Home system
−r′i pjd − rj where ci is the cost of attacking cluster heads Ci, c′i is the cost of attacking cluster heads Ci after T times, ri is the cost of persistently protecting cluster heads Ci, r′i is the cost of protecting cluster heads Ci after T times, pia is the payoff of attacking cluster heads Ci, and pid is the payoff of intrusion detection systems against attacks
Summary
Internet of things (IoT) is entering people’s lives and makes the production and life of human beings more intelligent and convenient. Some equipment uses outdated versions that are unable to remotely upgrade weaknesses and vulnerabilities, making Smart Home devices vulnerable to attacks Equipment such as cameras and smart thermostats collect information about people’s daily lives which can be traced directly or indirectly back to the person. Mobile Information Systems as the repeated game and proposes an intrusion detection scheme based on repeated game to protect the security of Smart Home. (1) To reduce the cost of equipping the intrusion detection system, this paper uses the K-Nearest Neighbors (KNN) algorithm to classify edge devices and equips the intrusion detection system for cluster heads to achieve the purpose of protecting Smart Home system.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
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 call
