Combining dynamic data with physical biometric verification to counteract spoofing

• Autorzy: Nishiuchi N.
• Języki publikacji: EN

Abstrakty

EN

Current physical biometric verification systems are hampered by a major vulnerability: spoofing. Keeping biological information, such as the face, fingerprints, and irises, concealed from others in daily life is difficult, and therefore theft and counterfeit of exposed biological information can be relatively easily accomplished by first capturing an individual's targeted information as an image and then using the data to reproduce a model. Here, I propose a new method of physical biometric verification that uses dynamic data which are difficult to spoof. This basic concept can be applied to several types of biometric verification, such as those based on finger geometry, finger veins, irises, and the contour of the eyelid. I also propose an algorithm for this new verification method and provide experimental examples of its application.

Słowa kluczowe

EN

physical biometrics; dynamic data; anti-spoofing

PL

biometryczne cechy fizyczne; dane dynamiczne; antyfałszowanie

• Wydawca: University of Silesia, Institute of Informatics, Computer Systems Department
• Czasopismo: Journal of Medical Informatics & Technologies
• Rocznik: 2010
• Tom: Vol. 15
• Strony: 11--17
• Opis fizyczny: Bibliogr. 10 poz., rys., tab.

Twórcy

autor

Nishiuchi N.

• Associate Professor in the Department of Management Systems Engineering, Graduate School of System Design at Tokyo Metropolitan University, Japan

Bibliografia

• [1] YAMADA K., MATSUMOTO H., MATSUMOTO T., Can we make artificial fingers that fool fingerprint systems?, Technical Report of Institute of Electronics, Information and Communication Engineers, 2000, pp. 159–166.
• [2] HIRABAYASHI M., TANABE T., MATSUMOTO T., Can we make artificial fingers that fool fingerprint systems? (Part VI), Technical Report of Institute of Electronics, Information and Communication Engineers, 2004, pp. 151–154.
• [3] MATSUMOTO T., Biometric authentication systems: vulnerability of biometric authentication – on the issue of physiological spoofing, IPSJ Magazine, Vol. 47, No. 6, Information Processing Society of Japan, 2006, pp. 589–594.
• [4] RYBNIK M., PANASIUK P., SAEED K., User authentication with keystroke dynamics using fixed text, Proceedings of the 2009 International Conference on Biometrics and Kansei Engineering, 2009, pp. 70–75.
• [5] YAMANA N., INBE A., MIURA F., MAEJIMA A., MORISHIMA S., Face authentication system using 3D frequency component of moving image, IEICE Technical Report, 2006, pp. 13–18.
• [6] RYGUŁA A., Driving style identification method based on speed graph analysis, Proceedings of the 2009 International Conference on Biometrics and Kansei Engineering, 2009, pp. 76–79.
• [7] SANO T., SATO E., YAMAGUCHI T., Personal authentication based on buying history applying classification method, International Journal of Biometrics, Vol. 1, No. 2, 2008, pp. 209–230.
• [8] NANDINI C., KUMAR C. N. R., Comprehensive framework to gait recognition, International Journal of Biometrics, Vol. 1, No. 1, 2008, pp. 129–137.
• [9] OSADA R., AOKI T., YASUDA H., A real time verification system based on individual characteristic extraction of hand motion, Technical Report of Information and Communication Engineers, Vol. J84–D–II, No. 2, 2001, pp. 258–265.
• [10] YAMPOLSKIY R. V., GOVINDARAJU V., Behavioural biometrics: a survey and classification, International Journal of Biometrics, Vol. 1, No. 1, 2008, pp. 81–113.