Name
Title | ||
|---|---|---|
VCIDS: Collaborative Intrusion Detection of Sensor and Actuator Attacks on Connected Vehicles. |
Abstract | ||
|---|---|---|
Modern urban vehicles adopt sensing, communication and computing modules into almost every functioning aspect to assist humans in driving. However, the advanced technologies are inherently vulnerable to attacks, exposing vehicles to severe security risks. In this work, we focus on the detection of sensor and actuator attacks that are capable of actively altering vehicle behavior and directly causing damages to human beings and vehicles. We develop a collaborative intrusion detection system where each vehicle leverages sensing data from its onboard sensors and neighboring vehicles to detect sensor and actuator attacks without a centralized authority. The detection utilizes the unique feature that clean data and contaminated data are correlated through the physical dynamics of the vehicle. We demonstrate the effectiveness of the detection system in a scaled autonomous vehicle testbed by launching attacks through various attack channels. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1007/978-3-319-78813-5_19 | Lecture Notes of the Institute for Computer Sciences Social Informatics and Telecommunications Engineering |
Keywords | Field | DocType |
Urban vehicular networks,Intrusion detection,Cyber-physical systems | Computer science,Sensing data,Testbed,Communication channel,Real-time computing,Cyber-physical system,Intrusion detection system,Actuator | Conference |
Volume | ISSN | Citations |
238 | 1867-8211 | 0 |
PageRank | References | Authors |
0.34 | 20 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Pinyao Guo | 1 | 24 | 4.66 |
| Hunmin Kim | 2 | 6 | 1.86 |
| Guan Le | 3 | 38 | 10.01 |
| Minghui Zhu | 4 | 44 | 12.11 |
| P. Liu | 5 | 378 | 41.58 |