User Context Detection for Relay Attack Resistance in Passive Keyless Entry and Start System
| Autor: | Shengkai Fang, Jing Li, Yabo Dong, Haowen Zhang, Duanqing Xu |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
Computer science
PKES Real-time computing 020206 networking & telecommunications 02 engineering and technology relay attacks Accelerometer lcsh:Chemical technology smartphone Biochemistry Atomic and Molecular Physics and Optics Article Analytical Chemistry Relay attack ComputerSystemsOrganization_MISCELLANEOUS 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing lcsh:TP1-1185 Electrical and Electronic Engineering Instrumentation context detection |
| Zdroj: | Sensors (Basel, Switzerland) Sensors Volume 20 Issue 16 Sensors, Vol 20, Iss 4446, p 4446 (2020) |
| ISSN: | 1424-8220 |
| Popis: | In modern cars, the Passive Keyless Entry and Start system (PKES) has been extensively installed. The PKES enables drivers to unlock and start their cars without user interaction. However, it is vulnerable to relay attacks. In this paper, we propose a secure smartphone-type PKES system model based on user context detection. The proposed system uses the barometer and accelerometer embedded in smartphones to detect user context, including human activity and door closing event. These two types of events detection can be used by the PKES to determine the car owner&rsquo s position when the car receives an unlocking or a start command. We evaluated the performance of the proposed method using a dataset collected from user activity and 1526 door closing events. The results reveal that the proposed method can accurately and effectively detect user activities and door closing events. Therefore, smartphone-type PKES can prevent relay attacks. Furthermore, we tested the detection of door closing event under multiple environmental settings to demonstrate the robustness of the proposed method. |
| Databáze: | OpenAIRE |
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