Human Body Odor Based Authentication Using Machine Learning

被引:0
作者
Yang, Bin [1 ]
Lee, Wonjun [2 ]
机构
[1] Tianjin Inst Aerosp Mech & Elect Equipment, Intelligent Equipment Technol Lab, Tianjin, Peoples R China
[2] Univ Texas San Antonio, Dept Elect & Comp Engn, San Antonio, TX USA
来源
2018 IEEE SYMPOSIUM SERIES ON COMPUTATIONAL INTELLIGENCE (IEEE SSCI) | 2018年
关键词
Human odor; biometric; authentication; K-means; Principal Component Analysis; Neural Network; FACE RECOGNITION; PCA;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The wearable devices become very popular in the people's daily lives. Because the wearable device is close to human body and the human biometric is unique for individuals, more and more wearable devices use the biometric parameters such as fingerprint, face, voice, iris, and hand geometry to perform authentication. But the above authentication methods require human intervention to enter authentication information scanning human body. This paper proposes a new biometric authentication method using human body odor, which makes the authentication more convenient and effective. We show that the human odor based authentication is accurate since every human body odor is determined by the major histocompatibility complex genes through some measures using gas sensors and machine learning techniques. In our analysis, we use three machine learning methods: K-means, Principal Component Analysis, and Neural Network, and show that the authentication accuracy using human body odor is very high as a result of experiments.
引用
收藏
页码:1707 / 1714
页数:8
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