Open AccessElectroencephalogram Authentication Access Control to Smart Car
Author(s) -
Yuhua Chen,
Jianqin Yin
Publication year - 2020
Publication title -
international journal of mathematical models and methods in applied sciences
Language(s) - English
Resource type - Journals
ISSN - 1998-0140
DOI - 10.46300/9101.2020.14.21
Subject(s) - biometrics , authentication (law) , access control , computer science , electroencephalography , signal (programming language) , control (management) , identity (music) , identification (biology) , computer security , artificial intelligence , pattern recognition (psychology) , psychology , physics , psychiatry , acoustics , programming language , botany , biology
In recent years, with the development of intelligent vehicles, the demand for security will be more and more big. One of the most important solutions is the use of new biometric technology. This paper presents an identity authentication system based on electroencephalogram (EEG) signals. The overall goal of this research is to design a new authentication method and develop the corresponding application. Therefore, we carried out a series of EEG experiments, and analyzed and discussed the experimental results. Based on these results, we study the algorithm of recognizing EEG signal features. Depended on the uniqueness of their EEG signals to be capable of authenticating access control to car, we build and present an Access Control System. The accuracy of authentication system is more than 87.3%.