Open Access iconOpen Access

ARTICLE

crossmark

An Efficient Impersonation Attack Detection Method in Fog Computing

Jialin Wan1, Muhammad Waqas1,2, Shanshan Tu1,*, Syed Mudassir Hussain3, Ahsan Shah2, Sadaqat Ur Rehman4, Muhammad Hanif2

1 Engineering Research Center of Intelligent Perception and Autonomous Control, Faculty of Information Technology, Beijing University of Technology, Beijing, 100124, China
2 Faculty of Computer Science and Engineering, Ghulam Ishaq Khan Institute of Engineering Sciences and Technology, Topi, 23460, Pakistan
3 Department of Electronics Engineering, FICT, Balochistan University of Information Technology, Engineering and Management Sciences, Quetta, 87300, Pakistan
4 Department of Computer Science, Namal Institute, Mianwali, 42200, Pakistan

* Corresponding Author: Shanshan Tu. Email: email

Computers, Materials & Continua 2021, 68(1), 267-281. https://doi.org/10.32604/cmc.2021.016260

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).

Keywords


Cite This Article

J. Wan, M. Waqas, S. Tu, S. Mudassir Hussain, A. Shah et al., "An efficient impersonation attack detection method in fog computing," Computers, Materials & Continua, vol. 68, no.1, pp. 267–281, 2021.

Citations




cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
  • 2274

    View

  • 1429

    Download

  • 0

    Like

Share Link