An Efficient Impersonation Attack DetectionMethod in Fog Computing

Jianlin Wan, Muhammad Waqas, Shanshan Tu, Syed Mudassir Hussain, Ahsan Ali, Sadaqat Ur Rehman, Muhammad Hanif

Research output: Contribution to journalArticlepeer-review

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, 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).
Original languageEnglish
Pages (from-to)267-281
Number of pages15
JournalComputers, Materials & Continua
Volume68
Issue number01
Publication statusPublished - 1 Mar 2021

Keywords

  • Fog computing
  • double Sarsa
  • attack detection
  • physical layer key security

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