### Detection Scheme of Impersonation Attack Based on DQL Algorithm in Fog Computing

MENG Yuan, TU Shanshan, YU Jinliang

1. 1.Faculty of Information Technology, Beijing University of Technology, Beijing 100124, China
2.Beijing Key Laboratory of Trusted Computing, Beijing 100124, China
• Online:2020-05-15 Published:2020-05-13

### 雾计算中基于DQL算法的伪装攻击检测方案

1. 1.北京工业大学 信息学部，北京 100124
2.可信计算北京市重点实验室，北京 100124

Abstract:

Fog computing is a technology that provides distributed computing, storage and other services between cloud data centers and Internet of Things（IoT） devices. It can utilize network edges to authenticate and provide ways to interact with the clouds. In fog computing, traditional security technology is not perfect enough to realize the security between users and fog nodes. It still faces security threats such as eavesdropping attack and impersonation attack, which poses new challenges to detection technology. To solve this problem, an impersonation attack detection scheme based on DQL（Double Q-learning） algorithm for fog computing is proposed. With the help of channel parameters in the physical layer security technology, at first this proposed scheme processes the overestimation of Q value on the basis of Q-learning algorithm to obtain the optimal impersonation attack test threshold. Then the detection of impersonation attack between users and fog nodes is realized by this threshold. Finally, experimental results show that this algorithm is better than the traditional Q-learning algorithm in detecting impersonation attack, and has advantages in the security protection of fog computing.