TY  - EJOU
AU  - Wan, Jialin 
AU  - Waqas, Muhammad 
AU  - Tu, Shanshan 
AU  - Hussain, Syed Mudassir 
AU  - Shah, Ahsan 
AU  - Rehman, Sadaqat Ur 
AU  - Hanif, Muhammad 

TI  - An Efficient Impersonation Attack Detection Method in Fog Computing
T2  - Computers, Materials \& Continua

PY  - 2021
VL  - 68
IS  - 1
SN  - 1546-2226

AB  - 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, we model 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 on Double Sarsa outperforms Sarsa and Q-learning approaches in terms of false alarm rate (FAR), miss detection rate (MDR), and average error rate (AER).
KW  - Fog computing; double Sarsa; attack detection; physical layer key security

DO  - 10.32604/cmc.2021.016260