Never lost keys: A novel key generation scheme based on motor imagery EEG in end-edge-cloud system

Biometric key is generated from the user's unique biometric features, and can effectively solve the security problems in cryptography. However, the current prevailing biometric key generation techniques such as fingerprint recognition and facial recognition are poor in randomness and can be forged easily. According to the characteristics of Electroencephalographic(EEG) signals such as the randomness, nonlinear and non-stationary etc., it can significantly avoid these flaws. This paper proposes a novel method to generate keys based on EEG signals with end-edge-cloud collaboration computing. Using sensors to measure motor imagery EEG data, the key is generated via pre-processing, feature extraction and classification. Experiments show the total time consumption of the key generation process is about 2.45s. Our scheme is practical and feasible, which provides a research route to generate biometric keys using EEG data.