Change Point Models for Real-Time Cyber Attack Detection in Connected Vehicle Environment
نویسندگان
چکیده
Connected vehicle (CV) systems are subject to potential cyber attacks because of increasing connectivity between its different components, such as vehicles, roadside infrastructure, and traffic management centers. However, it is a challenge detect security threats in real-time develop appropriate or effective countermeasures for CV system the dynamic behavior attacks, high computational power requirement, historical data requirement training detection models. To address these challenges, statistical models, especially change point have potentials anomaly detection. Thus, objective this study investigate efficacy two models; Expectation Maximization (EM) forms Cumulative Summation (CUSUM) algorithms (i.e., typical adaptive), vehicle-to-infrastructure (V2I) attack Environment. prove we evaluated models three types attack, denial service (DOS), impersonation, false information, using basic safety messages (BSMs) generated from CVs through simulation. Results numerical analysis revealed that EM, CUSUM, adaptive CUSUM (aCUSUM) could cyberattacks, DOS, information with low positives.
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ژورنال
عنوان ژورنال: IEEE Transactions on Intelligent Transportation Systems
سال: 2022
ISSN: ['1558-0016', '1524-9050']
DOI: https://doi.org/10.1109/tits.2021.3113675