A Rule-Based Intrusion Detection System for NDN-Based VANETs

Vehicular Ad-Hoc Networks (VANETs), a specialized type of Mobile Ad-Hoc Networks, facilitate critical communications between vehicles such as vehicle-to-vehicle and vehicle-to-roadside infrastructures. Owing to the transmission of critical safety messages, the VANETs are prone to various cyberattacks aimed at compromising information such as safety message authenticity. To address VANETs' inherent need for robust safety message authentication, which traditional protocols often lack, Named Data Networking (NDN) appears as an alternative networking architecture, offering enhanced Data packet-level security. Utilizing NDN, this paper proposes a novel Intrusion Detection System (IDS) for VANETs with the precise aim of validating the authenticity of safety messages. To this end, the proposed scheme employs a rule-based approach leveraging vehicular sensor data to determine the integrity of received safety messages. The proposed IDS scheme is implemented and tested in a Python-based NDN-VANET simulation environment and demonstrates a minimum accuracy rate of 95% across various safety message categories.