Abstract
With the rapid development of brain-computer interface technology, as a new biometric feature, EEG signal has been widely concerned in recent years. The safety of brain-computer interface and the long-term insecurity of biometric authentication have a new solution. This review analyzes the biometrics of EEG signals, and the latest research is involved in the authentication process. This review mainly introduced the method of EEG-based authentication and systematically introduced EEG-based biometric cryptosystems for authentication for the first time. In cryptography, the key is the core basis of authentication in the cryptographic system, and cryptographic technology can effectively improve the security of biometric authentication and protect biometrics. The revocability of EEG-based biometric cryptosystems is an advantage that traditional biometric authentication does not have. Finally, the existing problems and future development directions of identity authentication technology based on EEG signals are proposed, providing a reference for the related studies.
Highlights
In computer science and cryptography, authentication is defined as the confirmation of a user’s claimed identity
As long as the physiological or behavioral features of people meet the requirements of universality, uniqueness, stability, and anti-fraud, they can be used as biometric features for authentication, such as the face, fingerprint, iris, voice print, DNA, and gait
Studies have shown that different individuals produce different EEG signals by endogenous spontaneous generation and exogenous stimuli-induced generation [6], confirming the uniqueness of human EEG signals to a certain extent. e EEG signals under stimulus are different from those under a normal condition; that is, EEG signals can be used as a kind of biometric feature to monitor the abnormal state of people
Summary
In computer science and cryptography, authentication is defined as the confirmation of a user’s claimed identity. As long as the physiological or behavioral features of people meet the requirements of universality, uniqueness, stability, and anti-fraud, they can be used as biometric features for authentication, such as the face, fingerprint, iris, voice print, DNA, and gait. These features are prone to be tampered with, forged, coerced, and irrevocable. E token-based authentication technology, such as digital certificate [3], in which users hold a private key corresponding to their own identity for authentication, is considered the most secure cryptography approach. E electroencephalogram (EEG)-based authentication takes the individual difference in the EEG signals as the only
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