Three factor scheme for biometric-based cryptographic key regeneration using iris

Kanade, Sanjay G.; Camara, Danielle; Krichen, Emine; Petrovska‐Delacrétaz, Dijana; Dorizzi, Bernadette

doi:10.1109/bsym.2008.4655523

Cited by 68 publications

(128 citation statements)

References 19 publications

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“…From our experiments [66], we found out that the majority coding does not work with iris data. Moreover, the assumption in [39] that the Hamming distance between genuine iris codes is 10% is too restrictive.…”

Section: Cryptographic Key Generation From Biometricsmentioning

confidence: 93%

Enhancing Information Security and Privacy by Combining Biometrics with Cryptography

Kanade

Petrovska‐Delacrétaz

Dorizzi

2012

Synthesis Lectures on Information Security, Privacy, and Trust

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Section: Cryptographic Key Generation From Biometricsmentioning

confidence: 93%

Enhancing Information Security and Privacy by Combining Biometrics with Cryptography

Kanade

Petrovska‐Delacrétaz

Dorizzi

2012

Synthesis Lectures on Information Security, Privacy, and Trust

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“…In an alternate formulation, Ratha et al [19] use the gradient of a mixture of Gaussian kernels to determine the direction of movement and the extent of movement is determined by the scaled value of the mixture. Some researchers proposed shuffling-based transformation to generate cancelable templates using a user-specified random key [24,25]. In these works, the iris code is divided into blocks and then the blocks are shuffled with a user-specified random shuffling key to generate cancelable iris template.…”

Section: Biometric Template Transformationmentioning

confidence: 99%

“…In the first approach, a randomly created cryptographic key is protected from unauthorized access with users' biometric data. Fuzzy vault [8][9][10] and fuzzy commitment scheme [24,25,30] fall under this category. In fuzzy vault scheme, biometric data (e.g., minutiae points) is considered as an unordered set s E = x 1 , x 2 , .…”

Section: Crypto-biometric Systemsmentioning

confidence: 99%

“…On the other side, in fuzzy commitment scheme, biometric data is represented in a binary vector b E and the vector is locked by a random secret key of less or equal bits of b E with XOR operation. In [24,25], iris code is combined with a random key using XOR operation and using the query iris code, the secret key is extracted from the combined iris code.…”

Section: Crypto-biometric Systemsmentioning

confidence: 99%

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Fingerprint-based crypto-biometric system for network security

Barman¹,

Samanta

Chattopadhyay

2015

EURASIP J. on Info. Security

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To ensure the secure transmission of data, cryptography is treated as the most effective solution. Cryptographic key is an important entity in this process. In general, randomly generated cryptographic key (of 256 bits) is difficult to remember. However, such a key needs to be stored in a protected place or transported through a shared communication line which, in fact, poses another threat to security. As an alternative to this, researchers advocate the generation of cryptographic key using the biometric traits of both sender and receiver during the sessions of communication, thus avoiding key storing and at the same time without compromising the strength in security. Nevertheless, the biometric-based cryptographic key generation has some difficulties: privacy of biometrics, sharing of biometric data between both communicating parties (i.e., sender and receiver), and generating revocable key from irrevocable biometric. This work addresses the above-mentioned concerns. We propose an approach to generate cryptographic key from cancelable fingerprint template of both communicating parties. Cancelable fingerprint templates of both sender and receiver are securely transmitted to each other using a key-based steganography. Both templates are combined with concatenation based feature level fusion technique and generate a combined template. Elements of combined template are shuffled using shuffle key and hash of the shuffled template generates a unique session key. In this approach, revocable key for symmetric cryptography is generated from irrevocable fingerprint and privacy of the fingerprints is protected by the cancelable transformation of fingerprint template. Our experimental results show that minimum, average, and maximum Hamming distances between genuine key and impostor's key are 80, 128, and 168 bits, respectively, with 256-bit cryptographic key. This fingerprint-based cryptographic key can be applied in symmetric cryptography where session based unique key is required.

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“…The system was tested with 700 images of 70 persons reaching an impressive FRR of 0.47%. Since the entropy of the generated keys was proven to be low Kanade et al [10,11] increase the entropy of produced keys by applying so-called shuffling keys based on passwords reporting a FRR of 4.61%. Providing a more comprehensible insight into the use of error correction codes in iris-based fuzzy commitment schemes we [18] have proposed a systematic way of constructing fuzzy commitment schemes in earlier work.…”

Section: Iris-biometric Cryptosystemsmentioning

confidence: 99%

Context-based texture analysis for secure revocable iris-biometric key generation

Rathgeb

Uhl

2009

3rd International Conference on Imaging for Crime Detection and Prevention (ICDP 2009)

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In this work we present an iris-biometric cryptosystem. Based on the idea of exploiting the most reliable components of iriscodes, cryptographic keys are extracted, long enough to be applied in common cryptosystems. The main benefit of our system is that cryptographic keys are directly derived from biometric data, thus, neither plain biometric data nor encrypted biometric data has to be stored in templates. Yet, we provide fully revocable cryptographic keys. Experimental results emphasize the worthiness of our approach.

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Three factor scheme for biometric-based cryptographic key regeneration using iris

Cited by 68 publications

References 19 publications

Enhancing Information Security and Privacy by Combining Biometrics with Cryptography

Enhancing Information Security and Privacy by Combining Biometrics with Cryptography

Fingerprint-based crypto-biometric system for network security

Context-based texture analysis for secure revocable iris-biometric key generation

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