A Survey of Remote Automotive Attack Surfaces
summary
Survey catalogs network diagrams for dozens of makes, scores cars by a three-step model (remote ECU compromise → CAN message injection → cyber‑physical actuation), and flags Bluetooth, cellular and in‑car browsers as largest remote surfaces. Methods: vendor docs and service manuals, correlation of features and network topology, and two demos — a learning CAN anomaly device (CAN intrusion detector) that detects attacks in seconds and severs the bus, and a Chrysler/Jeep jailbreak via ISO timing that bypasses update checks. A 95‑page dataset paper accompanies the results.
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chapters (10)
- 0:00Introduction and motivation
- 4:39Remote attack methodology
- 9:29Assessing hackability
- 12:23Remote attack surfaces
- 20:15Cyber-physical features
- 27:20Research data gathering
- 32:05Network architecture analysis
- 43:59Security implications
- 48:47IDS and defense solutions
- 52:21Jailbreaking demonstration
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