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@article{179112,
        author = {Anubhav Kumar and Dr. Devender Kumar},
        title = {RISK-BASED SECURITY FRAMEWORKS FOR VANETS: A SYSTEMATIC REVIEW},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {12},
        pages = {5398-5405},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=179112},
        abstract = {Vehicular Ad-Hoc Networks (VANETs) are essential for intelligent transportation systems, facilitating real-time data communication between vehicles and infrastructure. Nonetheless, their decentralized and open-access characteristics render them susceptible to several cyber dangers, requiring stringent security measures. This systematic analysis analyzes risk-based security frameworks aimed at improving the resilience of VANET against attacks like spoofing, denial-of-service, and data tampering. Through the examination of existing literature, we classify security models according to quantitative risk assessment approaches, pinpointing critical vulnerabilities and corresponding mitigation strategies. The research emphasizes the significance of machine learning, cryptographic methods, and trust-centric frameworks in enhancing the security of VANETs. We also review risk assessment models that measure the likelihood and consequences of cyber threats, enabling proactive security strategies. The findings indicate that the incorporation of adaptive security methods alongside real-time risk assessments can markedly improve VANET reliability. This analysis offers insights into prospective research avenues, highlighting the necessity for scalable, efficient, and context-aware security frameworks specifically designed for automotive networks.},
        keywords = {Vehicular Networks, Risk Analysis, Security Analysis etc.},
        month = {May},
        }