A Survey of Anomaly Detection for Connected Vehicle Cybersecurity and Safety

Anomaly detection techniques have been applied to the challenging problem of ensuring both cybersecurity and safety of connected vehicles. We propose a taxonomy of prior research in this domain. Our proposed taxonomy has 3 overarching dimensions subsuming 9 categories and 38 subcategories. Key observations emerging from the survey are: Real-world datasets are seldom used, but instead, most results are derived from simulations; V2V/V2I communications and in-vehicle communication are not considered together; proposed techniques are seldom evaluated against a baseline; safety of the vehicles does not attract as much attention as cybersecurity.