Open Access

ARTICLE

Central Aggregator Intrusion Detection System for Denial of Service Attacks

by Sajjad Ahmad¹, Imran Raza¹, M. Hasan Jamal¹, Sirojiddin Djuraev², Soojung Hur³, Imran Ashraf^3,*

1 Department of Computer Science, COMSATS University Islamabad, Lahore Campus, Lahore, 54000, Pakistan
2 Department of Software Engineering, New Uzbekistan University, Tashkent, 100007, Uzbekistan
3 Department of Information and Communication Engineering, Yeungnam University, Gyeongsan-si, 38541, Korea

* Corresponding Author: Imran Ashraf. Email:

Computers, Materials & Continua 2023, 74(2), 2363-2377. https://doi.org/10.32604/cmc.2023.032694

Received 26 May 2022; Accepted 29 June 2022; Issue published 31 October 2022

Abstract

Vehicle-to-grid technology is an emerging field that allows unused power from Electric Vehicles (EVs) to be used by the smart grid through the central aggregator. Since the central aggregator is connected to the smart grid through a wireless network, it is prone to cyber-attacks that can be detected and mitigated using an intrusion detection system. However, existing intrusion detection systems cannot be used in the vehicle-to-grid network because of the special requirements and characteristics of the vehicle-to-grid network. In this paper, the effect of denial-of-service attacks of malicious electric vehicles on the central aggregator of the vehicle-to-grid network is investigated and an intrusion detection system for the vehicle-to-grid network is proposed. The proposed system, central aggregator–intrusion detection system (CA-IDS), works as a security gateway for EVs to analyze and monitor incoming traffic for possible DoS attacks. EVs are registered with a Central Aggregator (CAG) to exchange authenticated messages, and malicious EVs are added to a blacklist for violating a set of predefined policies to limit their interaction with the CAG. A denial of service (DoS) attack is simulated at CAG in a vehicle-to-grid (V2G) network manipulating various network parameters such as transmission overhead, receiving capacity of destination, average packet size, and channel availability. The proposed system is compared with existing intrusion detection systems using different parameters such as throughput, jitter, and accuracy. The analysis shows that the proposed system has a higher throughput, lower jitter, and higher accuracy as compared to the existing schemes.

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Keywords

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