Biometrics and Bioinformatics

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Encryption of Biometric Templates Using One Time Biometric Transform


Affiliations
1 Vishvakarma Institute of Information Technology, Pune, India
2 Hyderabad, India
3 Electrical and Computer Engineering Department, San Diego State University, San Diego, Canada
4 Clarkson University, NY, United States
     

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Securing biometric information has become essential with growing biometric applications in different sectors of society. Vulnerability assessment plays a key role in improving the security of any security system by identifying the potential vulnerabilities and proposing countermeasures to mitigate the threats posed by them. In this work self-generated and dynamic helper data based system is proposed to encrypt the biometric templates. Biometric information is statistically learned and probabilistic matching is performed to discriminate genuine from imposters. We call this system as One Time Biometric Transformation (OTBT) system. The system was tested using CASIA iris database and by probabilistic matching an EER of 1.96% is achieved. Strength analysis of the system for three different challenging databases is also presented.
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  • Encryption of Biometric Templates Using One Time Biometric Transform

Abstract Views: 213  |  PDF Views: 4

Authors

Aditya Abhyankar
Vishvakarma Institute of Information Technology, Pune, India
Amit Vijayat
Hyderabad, India
Sunil Kumar
Electrical and Computer Engineering Department, San Diego State University, San Diego, Canada
Stephanie Schuckers
Clarkson University, NY, United States

Abstract


Securing biometric information has become essential with growing biometric applications in different sectors of society. Vulnerability assessment plays a key role in improving the security of any security system by identifying the potential vulnerabilities and proposing countermeasures to mitigate the threats posed by them. In this work self-generated and dynamic helper data based system is proposed to encrypt the biometric templates. Biometric information is statistically learned and probabilistic matching is performed to discriminate genuine from imposters. We call this system as One Time Biometric Transformation (OTBT) system. The system was tested using CASIA iris database and by probabilistic matching an EER of 1.96% is achieved. Strength analysis of the system for three different challenging databases is also presented.