Central Aggregator Intrusion Detection System for Denial of Service Attacks

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.

Safeguarding the V2X Pathways: Exploring the Cybersecurity Landscape Through Systematic Review

“…In addition to detection methods, the literature also discusses strategies to mitigate the effects of DDoS attacks. For example, a Central Aggregator-Intrusion Detection System (CA-IDS) was proposed for EVs, noted for its higher throughput, lower jitter, and accuracy [108]. This system monitors and analyzes incoming traffic to EVs, effectively identifying and blocking malicious vehicles.…”

Simulation of Vehicular Bots-Based DDoS Attacks in Connected Vehicles Networks

“…The impact of vehicular bot-based DDoS attacks was measured based on the packet delivery ratio, packet loss ratio, throughput, jitter, and end-to-end delay by varying the number of bots, DDoS rate, and max bulk rate. By using NS-3, the mentioned variables can be used to analyze the efficiency and performance of the network [1,28].…”