Name
Abstract | ||
|---|---|---|
With the growing reliance on driving direction applications that dynamically account for live traffic updates, drivers are much more likely to act optimally, by taking the shortest path to their destination, and therefore more predictably. As city networks transition into being made up of connected and autonomous vehicles, autonomous driving pilots are even more likely to act optimally and predictably. The predictability that comes from acting optimally allows motivated attackers to manipulate driver(s) to travel chosen slower alternative routes by causing disruptions on road segments that are part of faster routes. A motivated attacker could use this method to cause a number of different harms such as forcing specific vehicles to take unnecessarily long routes, forcing all vehicles traveling between popular locations to follow a chosen route, or making vehicles travel specific road segments that the attacker chose, such as toll roads. In this work, we show the feasibility and practicality of conducting such attacks on several real traffic networks of major North American cities. We analyze several attack objectives under different attacker constraints and we demonstrated that an attacker could find an attack strategy in a matter of seconds. |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1109/DSN-W54100.2022.00014 | 2022 52nd Annual IEEE/IFIP International Conference on Dependable Systems and Networks Workshops (DSN-W) |
Keywords | DocType | ISSN |
Security,Connected and Autonomous Vehicles,Alternative route-based attacks | Conference | 2325-6648 |
ISBN | Citations | PageRank |
978-1-6654-0263-7 | 0 | 0.34 |
References | Authors | |
5 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Sidney La Fontaine | 1 | 0 | 0.34 |
| Naveen Muralidhar | 2 | 0 | 0.34 |
| Michael Clifford | 3 | 0 | 0.34 |
| Tina Eliassi-Rad | 4 | 1597 | 108.63 |
| Cristina Nita-Rotaru | 5 | 1855 | 100.14 |