Exploring Cyber Trends and Threats Towards V2X Connected Vehicles in Malaysia: A Systematic Literature Review

The rapid expansion of 5G enabled Vehicle to Everything (V2X) communication has evolved into an intelligent transportation system by supporting applications such as autonomous driving, real-time traffic optimization, and road safety management. However, the growing connectivity and diverse communication protocols also create major cybersecurity challenges, especially in the network tier of connected vehicles. This study conducts a systematic literature review following the PRISMA framework to examine cybersecurity threats and detection models in Malaysia's V2X ecosystem. It involves an analyzing phase towards 85 peer-reviewed studies published between 2016 and 2025. This addresses three research questions: (RQ1) What is the state-of-the-art in CVs in the aspect of network technology in Malaysia, (RQ2) What are the cybersecurity trends and threats towards CVs in the network tier, and (RQ3) What are the existing models in detecting and responding to cyber threats against CVs? Study identifies critical threats, including spoofing, jamming, and denial of service attacks, while evaluating intrusion detection systems that use machine learning, deep learning, and hybrid approaches. The existing approaches are yet to face limitations in real-time performance, contextual accuracy, and supply chain resilience under Malaysia's tropical urban conditions. This study proposes a conceptual model, the SCARF-V2X model, an NGSOC integrated concept that utilizes SIEM, SOAR, and Malaysian cyber threat intelligence platforms to enable automated detection and first-layer auto-response, specifically towards supply chain threats in CVs. The proposed model aims to improve Malaysia's V2X cybersecurity landscape and introduces a proactive and adaptive model to protect CVs against evolving cyber threats.