A unified threat-scoring detection algorithm for cybersecurity attacks in automotive CAN networks
DOI:
https://doi.org/10.29114/ajtuv.vol9.iss2.350Keywords:
CAN bus; in-vehicle network security; threat modeling; intrusion detectionAbstract
Controller Area Network (CAN) is the primary in-vehicle communication backbone but provides no built-in security, leaving vehicles susceptible to message-injection attacks. This study presents a novel algorithm that (1) systematically classifies CAN attack types, (2) computes an impact-weighted probabilistic risk score per attack instance, (3) supplies an on-bus simulation environment for controlled injections, and (4) embeds a lightweight hybrid detector combining an ensemble classifier for known patterns with anomaly scoring for unknown activity. The main contribution is a compact, interpretable scoring model (likelihood × impact × weight) integrated with a reproducible evaluation protocol and reference implementation for benchmarking on public CAN corpora.
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