Multi-factor EEG-based User Authentication
Authentication plays a very important role in security systems; however, the current methods, such as password-based, token-based, and biometrics-based authentication, have been exposed their own security weaknesses. Password-based authentication is not immune from malicious attacks such as offline dictionary attack, popular password attack, exploiting user mistakes, and exploiting multiple password use [9].
Token-based authentication requires users always bringing and providing tokens when accessing the systems. Presenting a token, which is not a part of a human body, can cause inconvenient.
Moreover, all the tokens require special readers and tokens can be physically stolen, be duplicated, as well as be hacked
[7] [9]. Although biometric authentication can avoid some disadvantages of password-based and token-based authentication systems, the biometrics modalities have some drawbacks. Face, fingerprint, and iris information can be
photographed. Voice could be recorded, and handwriting may be mimicked [6] [23].
Individuals can also be lost or changed their biometric characteristics such as finger or face. These disadvantages of the 3 current authentication methods require a better modality for security systems.