Adaptive Attack Mitigation for IoV Flood Attacks
Erol Gelenbe, Mohammed Nasereddin

TL;DR
This paper introduces an adaptive attack mitigation system for IoV gateways that dynamically manages traffic during flood attacks, ensuring attack detection and system performance.
Contribution
It proposes a novel Adaptive Attack Mitigation system that optimizes traffic sampling and packet dropping to counter flood attacks in IoV networks.
Findings
The AAM system effectively reduces attack impact in experiments.
Theoretical analysis confirms the optimality of the AAM approach.
Experimental results demonstrate improved QoS during attacks.
Abstract
Gateway Servers for the Internet of Vehicles (IoV) must meet stringent Security and Quality of Service (QoS) requirements, including cyberattack protection, low delays and minimal packet loss, to offer secure real-time data exchange for human and vehicle safety and efficient road traffic management. Therefore, it is vital to protect these systems from cyberattacks with adequate Attack Detection (AD) and Mitigation mechanisms. Such attacks often include packet Floods that impair the QoS of the networks and Gateways and even impede the Gateways capability to carry out AD. Thus, this paper first evaluates these effects using system measurements during Flood attacks. It then demonstrates how a Smart Quasi-Deterministic Policy Forwarder (SQF) at the entrance of the Gateway can regulate the incoming traffic to ensure that the Gateway supports the AD to operate promptly during an attack. Since…
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Taxonomy
TopicsNetwork Security and Intrusion Detection · Smart Grid Security and Resilience · Advanced Malware Detection Techniques
