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Download e-book for iPad: Advances in Biometrics for Secure Human Authentication and by Tyler Justin Speed

By Tyler Justin Speed

ISBN-10: 1439809828

ISBN-13: 9781439809822

ISBN-10: 1466582421

ISBN-13: 9781466582422

ISBN-10: 146658243X

ISBN-13: 9781466582439

''Supplying a high-level assessment of ways to guard your company's actual and intangible resources, Asset defense via safety knowledge explains the easiest how you can enlist the help of your staff because the first defensive line in safeguarding corporation resources and mitigating safety dangers. It studies key issues surrounding desktop security--including privateness, entry controls, and danger management--to help Read more...

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Extra info for Advances in Biometrics for Secure Human Authentication and Recognition

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The factor is given in the range 0–1, and the exploitation potential is scaled by (1-DE) if a technique is used that would require significant effort for an attacker. The discovery effect is generally characterized by the 26 G AYAT RI MIR A JK A R computing power that might be required to implement the attack— for most biometric vulnerabilities, the discovery effort is sufficiently low that it can be considered as zero. 4 Vulnerabilities Assurance Level The result of the previous steps is the measurement of the exploitation potential for one point on the attack potential diagram.

Therefore, the best method for vitality detection is to use a characteristic that is distinctive to each individual, and not easily available to an adversary for copying. Such a unique characteristic is another biometric. For example, a multimodal biometric system can be built that combines a strong biometric, such as a fingerprint with another biometric (possibly, a weaker one) that is difficult to acquire covertly, such as face thermogram. Another approach might use a fingerprint SEC URIT Y A S SE S SM EN T F O R BI O M E T RI C SYS T EM S 29 system requiring each user to present several fingers in a specific order; a hacker would have to find latent fingerprints from multiple fingers from both hands and also know the order of presentation.

IEEE Transactions on Systems, Man, and Cybernetics, Part C 35(3):335–343, 2005. 12. A. Antonelli, R. Cappelli, D. Maio, and D. Maltoni. Fake finger detection by skin distortion analysis. IEEE Transactions on Information Forensics and Security 1(3):360–373, 2006. R. Setlak. Fingerprint sensor having spoof reduction features and related methods. US Patent no. 5953441, 1999. 14. A. K. Rowe. Multispectral fingerprint imaging for spoof detection. In Biometric Technology for Human Identification II, Proceedings of SPIE 5799, 214–225, Orlando, FL, 2005.

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Advances in Biometrics for Secure Human Authentication and Recognition by Tyler Justin Speed


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