29 research outputs found

    Biometric Keys for the Encryption of Multimodal Signatures

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    Electricity, electromagnetism & magnetis

    On fuzzy syndrome hashing with LDPC coding

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    The last decades have seen a growing interest in hash functions that allow some sort of tolerance, e.g. for the purpose of biometric authentication. Among these, the syndrome fuzzy hashing construction allows to securely store biometric data and to perform user authentication without the need of sharing any secret key. This paper analyzes this model, showing that it offers a suitable protection against information leakage and several advantages with respect to similar solutions, such as the fuzzy commitment scheme. Furthermore, the design and characterization of LDPC codes to be used for this purpose is addressed.Comment: in Proceedings 4th International Symposium on Applied Sciences in Biomedical and Communication Technologies (ISABEL), ACM 2011. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistributio

    Using Distributed Source Coding to Secure Fingerprint Biometrics

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    Exploiting Channel Diversity in Secret Key Generation from Multipath Fading Randomness

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    We design and analyze a method to extract secret keys from the randomness inherent to wireless channels. We study a channel model for multipath wireless channel and exploit the channel diversity in generating secret key bits. We compare the key extraction methods based both on entire channel state information (CSI) and on single channel parameter such as the received signal strength indicators (RSSI). Due to the reduction in the degree-of-freedom when going from CSI to RSSI, the rate of key extraction based on CSI is far higher than that based on RSSI. This suggests that exploiting channel diversity and making CSI information available to higher layers would greatly benefit the secret key generation. We propose a key generation system based on low-density parity-check (LDPC) codes and describe the design and performance of two systems: one based on binary LDPC codes and the other (useful at higher signal-to-noise ratios) based on four-ary LDPC codes

    Quantization effects in biometric systems

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    The fundamental secret-key rate vs. privacy-leakage rate trade-offs for secret-key generation and transmission for i.i.d. Gaussian biometric sources are determined. These results are the Gaussian equivalents of the results that were obtained for the discrete case by the authors and independently by Lai et al. in 2008. Also the effect that binary quantization of the biometric sequences has on the ratio of the secret-key rate and privacy-leakage rate is considered. It is shown that the squared correlation coefficient must be increased by a factor of pi2/4 to compensate for such a quantization action, for values of the privacy-leakage rate that approach zero, when the correlation coefficient is close to zero

    Recent Application in Biometrics

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    In the recent years, a number of recognition and authentication systems based on biometric measurements have been proposed. Algorithms and sensors have been developed to acquire and process many different biometric traits. Moreover, the biometric technology is being used in novel ways, with potential commercial and practical implications to our daily activities. The key objective of the book is to provide a collection of comprehensive references on some recent theoretical development as well as novel applications in biometrics. The topics covered in this book reflect well both aspects of development. They include biometric sample quality, privacy preserving and cancellable biometrics, contactless biometrics, novel and unconventional biometrics, and the technical challenges in implementing the technology in portable devices. The book consists of 15 chapters. It is divided into four sections, namely, biometric applications on mobile platforms, cancelable biometrics, biometric encryption, and other applications. The book was reviewed by editors Dr. Jucheng Yang and Dr. Norman Poh. We deeply appreciate the efforts of our guest editors: Dr. Girija Chetty, Dr. Loris Nanni, Dr. Jianjiang Feng, Dr. Dongsun Park and Dr. Sook Yoon, as well as a number of anonymous reviewers
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