May 13, 2025 · Modern vehicles are no longer just machines — they're intelligent, connected systems forming the Internet of Vehicles (IoV). But with connectivity comes vulnerability.

The main intention of the MDMIoV-DLXAI model is to enhance the malware detection and classification model in IoV by utilizing advanced two-tier optimization models.

Dec 18, 2025 · This phase of the project focused on developing, training, and evaluating machine learning models to detect intrusions in the Internet of Vehicles (IoV) network using the CICIoV2024 …

Oct 23, 2025 · The rapid growth of the Internet of Vehicles (IoVs) and smart consumer electronics has generated cybersecurity concerns that require an intelligent, adaptable, and privacy-preserving …

Table IX compares the proposed ZTID-IoV technique with recent federated and meta-learning-based intrusion detection approaches. The comparison includes several performance metrics, such as …

This imbalance makes such datasets unsuit- able for supervised learning, which relies on well-labeled and balanced training data. In order to cope with these issues, this study offers a hybrid IDS that …

The Internet of Vehicles (IoV) ecosystem is rapidly expanding with connected vehicles, which has made the need for secure, scalable, and real-time Int…

Grateful to collaborate with my co-authors: Dr. Akshatha P S, Udayaprasad P K, Pruthvi C N , Dr. Dharamendra Chouhan, and Dr. Swathika R. 📌 Publisher: IEEE 📌 Conference: 2025 International ...

This paper first briefly introduces the concept and features of IoV, and then reviews the related research on AI-based IoV intrusion detection systems (IDSs).

This approach enables training ML models on decentralized data without transferring or sharing sensitive data. This paper proposes a SL-based privacy-preserving intrusion detection system for IoV …