Hybrid Intrusion Detection System using K-means and K-Nearest Neighbors Algorithms

2018 ◽  
Author(s):  
Yi Yi Aung ◽  
Myat Myat Min
Keyword(s):  
Intrusion Detection ◽  
Intrusion Detection System ◽  
Detection System ◽  
Nearest Neighbors ◽  
K Nearest Neighbors

scholarly journals An Intrusion Detection Scheme Based on Repeated Game in Smart Home

2020 ◽  
Vol 2020 ◽  
pp. 1-9
Author(s):  
Rui Zhang ◽  
Hui Xia ◽  
Shu-shu Shao ◽  
Hang Ren ◽  
Shuai Xu ◽  
...  
Keyword(s):  
Intrusion Detection ◽  
Intrusion Detection System ◽  
Smart Home ◽  
Life Experience ◽  
Detection System ◽  
Repeated Game ◽  
K Nearest Neighbors ◽  
Detection Scheme ◽  
Equipment Safety ◽  
Severe Punishment

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.

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