Never Lost Keys:A Novel Key Generation Scheme Based on Motor Imagery EEG in End-Edge-Cloud System  

作　　者：Yichuan Wang Dan Wu Xiaoxue Liu Xinhong Hei 

机构地区：[1]School of computer science and Engineering,Xi’an University of Technology,Xi’an 710048,China [2]Shaanxi Key Laboratory for Network Computing and Security Technology,Xi’an 710048,China

出　　处：《China Communications》2022年第7期172-184,共13页中国通信（英文版）

基　　金：supported by the National Natural Science Founds of China (62072368, U20B2050);Key Research and Development Program of Shaanxi Province (2020GY-039, 2021ZDLGY05-09, 2022GY040)

摘　　要：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-edgecloud 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.

关 键 词：EEG biometric key generation end-edgecloud system information security 

分 类 号：TN918.4[电子电信—通信与信息系统]