Hybrid Approaches for Intrusion Prediction in IoV (Internet of Vehicles)
Naveen Joshi, Nirmal Kaur · Gurukul multidisciplinary research journal. · 2024
Hybrid Approaches for Intrusion Prediction in IoV (Internet of Vehicles) Authors : Naveen Joshi1, Dr Nirmal Kaur2 1Research Scholar, SBBSU, Jalandhar, [email protected] 2 Associate Professor, SBBSU, Jalandhar Abstract The Internet of Vehicles (IoV) is a burgeoning field integrating smart vehicles into a connected ecosystem, enabling Vehicle-to-Everything (V2X) communications. However, this connectivity increases vulnerability to cyber threats, necessitating robust intrusion detection systems (IDS). This paper explores hybrid approaches combining signature-based and anomaly-based detection methods to enhance security in IoV. We discuss the architecture, algorithms, and performance metrics of hybrid IDS, emphasizing their advantages and potential challenges. A detailed analysis of hybrid IDS implementations is presented, supported by diagrams and empirical data. Keywords: Internet of Vehicles (IoV), Intrusion Detection Systems (IDS), Machine Learning (ML), Deep Learning (DL), Hybrid Approaches, Cyber security, Vehicle-to-Everything (V2X), Anomaly Detection, Predictive Security, Network Security.