Name
Abstract | ||
|---|---|---|
Ensuring the safety of autonomous vehicles (AVs) is critical for their mass deployment and public adoption. However, security attacks that violate safety constraints and cause accidents are a significant deterrent to achieving public trust in AVs, and that hinders a vendor's ability to deploy AVs. Creating a security hazard that results in a severe safety compromise (for example, an accident) is compelling from an attacker's perspective. In this paper, we introduce an attack model, a method to deploy the attack in the form of smart malware, and an experimental evaluation of its impact on production-grade autonomous driving software. We find that determining the time interval during which to launch the attack is{ critically} important for causing safety hazards (such as collisions) with a high degree of success. For example, the smart malware caused 33X more forced emergency braking than random attacks did, and accidents in 52.6% of the driving simulations. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1109/DSN48063.2020.00030 | 2020 50th Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN) |
Keywords | DocType | ISSN |
Autonomous Vehicles, Security, Safety | Conference | 1530-0889 |
ISBN | Citations | PageRank |
978-1-7281-5810-5 | 1 | 0.36 |
References | Authors | |
9 | 7 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Saurabh Jha | 1 | 13 | 2.61 |
| Shengkun Cui | 2 | 1 | 0.69 |
| Subho S. Banerjee | 3 | 26 | 6.88 |
| James Cyriac | 4 | 1 | 0.36 |
| Timothy Tsai | 5 | 9 | 3.56 |
| ?zg???ner | 6 | 33 | 18.65 |
| Ravishankar K. Iyer | 7 | 3489 | 504.32 |