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Title

An Efficient Impersonation Attack Detection Method in Fog Computing.

Authors

Jialin Wan; Waqas, Muhammad; Shanshan Tu; Hussain, Syed Mudassir; Shah, Ahsan; Ur Rehman, Sadaqat; Hanif, Muhammad

Abstract

Fog computing paradigm extends computing, communication, storage, and network resources to the network's edge. As the fog layer is located between cloud and end-users, it can provide more convenience and timely services to end-users. However, in fog computing (FC), attackers can behave as real fog nodes or end-users to provide malicious services in the network. The attacker acts as an impersonator to impersonate other legitimate users. Therefore, in this work, we present a detection technique to secure the FC environment. First, wemodel a physical layer key generation based on wireless channel characteristics. To generate the secret keys between the legitimate users and avoid impersonators, we then consider a Double Sarsa technique to identify the impersonators at the receiver end. We compare our proposed Double Sarsa technique with the other two methods to validate our work, i.e., Sarsa and Q-learning. The simulation results demonstrate that the method based onDouble Sarsa outperforms Sarsa andQ-learning approaches in terms of false alarm rate (FAR), miss detection rate (MDR), and average error rate (AER).

Subjects

IMPERSONATION; WIRELESS channels; ERROR rates; FALSE alarms

Publication

Computers, Materials & Continua, 2021, Vol 68, Issue 1, p267

ISSN

1546-2218

Publication type

Academic Journal

DOI

10.32604/cmc.2021.016260

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