An Intelligent Intrusion Detection System for VANETs Using Adaptive Fusion Models

International Journal of Computational and Experimental Science and Engineering, Journal Year: 2025, Volume and Issue: 11(1)

Published: Feb. 5, 2025

Vehicular Ad Hoc Networks (VANETs) play a vital role in the development of Cyber-Physical Systems (CPS) to enable real-time communication for improving road safety and traffic efficiency. Due VANETs' decentralized dynamic nature, they are prone various types cyber-attacks, including intrusion, spoofing, denial-of-service (DoS) attacks. This article presents an Adaptive Fusion Intrusion Detection Model (AFIDM), multi-level framework that uses machine learning techniques, such as Random Forest, XGBoost, Decision Trees, K-Nearest Neighbor (KNN), deal with vulnerabilities. AFIDM also employs weight adjusting mechanism adaptive feedback loop adapt evolving threats achieve better detection accuracy. achieved 98.7% accuracy, 96.5% precision, recall 95.8% on VeReMi dataset used training validation outperformed other baseline models. With low latency scalability, proposed model robust solution intrusion VANETs secure efficient operation intelligent transportation systems

Language: Английский

Development of Intrusion detection system for VANET using Machine Learning

International Journal of Computational and Experimental Science and Engineering, Journal Year: 2025, Volume and Issue: 11(2)

Published: March 31, 2025

With the proliferation of vehicular technology, modern vehicles are fortified with ever more electronic maneuvers. This advancement ratifies evolution Intelligent Transportation Systems (ITS)to provide services like shared travel, smart driving, on-the-go Internet, etc. As a traditional application ITS, Vehicular Ad hoc Network (VANET) enables communication between vehicle nodes and network infrastructures to various expedient such as road safety, data sharing, traffic management, parking assistance, entertainment, route recommendation, mobile payment, even cloud applications. The high-speed (vehicles) in VANET perform very differently from other wireless networks have set distinct features frequent link disconnection, highly dynamic topology, limited coverage area, heterogeneous system architecture that may affect performance service quality significantly. this motivation, work attempts develop distributed cooperative cluster-based IDS identify potential cyberattacks effectively. Firstly, develops stable reliable clustering method named Fuzzy Logic-based Clustering (FLC) create collaborative environment. A new fuzzy logic-based CH node selection algorithm is also developed based on degree, average velocity difference, relative robust structure minimum cost

Language: Английский