生物识别
计算机科学
认证(法律)
脑-机接口
鉴定(生物学)
脑电图
眼球运动
接口(物质)
特征提取
人工智能
支持向量机
机器学习
数据挖掘
模式识别(心理学)
计算机视觉
计算机安全
最大气泡压力法
精神科
生物
植物
气泡
并行计算
心理学
作者
Shiwei Cheng,Wang Jialing,Sheng Danyi,Chen Yijian
出处
期刊:IEEE Transactions on Instrumentation and Measurement
[Institute of Electrical and Electronics Engineers]
日期:2023-01-01
卷期号:72: 1-14
被引量:1
标识
DOI:10.1109/tim.2023.3241081
摘要
Biometric authentication has been applied in many domains due to the promoting awareness of privacy and security risks. Most of the previous work has shown the performance of single biometric, but a few studies explored the feasibility of hybrid biometrics. On this basis, we proposed a hybrid brain–computer interface (BCI) authentication approach that combined user’s electroencephalogram (EEG) and eye movement data features simultaneously. In anti-shoulder-surfing experiments, the proposed approach reached the average accuracy of 84.36% (the highest was 88.35%) to identify shoulder surfers and outperformed the only EEG and only eye movement data-based authentication approach. In additional experiments, the approach was proven to be useful in reducing the possibility of user misidentification. Our approach holds a great potential in providing references for implementing hybrid BCI authentication for anti-shoulder-surfing applications.
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