This paper proposes a continuous identification scheme monitoring a driver's behavior and a detection scheme for an impostor. The proposed scheme uses Long Short-Term Memory (LSTM) to create a classifier of the driver's behavior according to acceleration data and classifies a driver. Additionally, it also detects an impostor according to statistical information of output from the classifier. Experimental results show that an acceleration sensor on a real vehicle is enough to classify 15 drivers according to real-time driver's behavior. Additionally, the proposed scheme can detect an impostor through the verification of real experimental data.
Proposal for Identification Scheme of Driver and Impostor based on Acceleration Data
2019-11-01
380039 byte
Conference paper
Electronic Resource
English
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