Optics based biohashing using joint transform correlator

Saini, Nirmala; Sinha, Aloka

doi:10.1016/j.optcom.2009.11.003

Cited by 8 publications

(6 citation statements)

References 28 publications

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“…This scheme combines the photon counting imaging technique in the encryption system to make the recognition process noninvertible [16]. Recently, some researchers have proposed cancellable biometrics based on biohashing [17][18][19][20][21]. Saini et al presented a new biohashing scheme optically based on a joint transform correlator for a biometric recognition system [20].…”

Section: Introductionmentioning

confidence: 99%

Digital holographic-based cancellable biometric for personal authentication

Verma

Sinha

2016

J. Opt.

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In this paper, we propose a new digital holographic-based cancellable biometric scheme for personal authentication and verification. The realization of cancellable biometric is presented by using an optoelectronic experimental approach, in which an optically recorded hologram of the fingerprint of a person is numerically reconstructed. Each reconstructed feature has its own perspective, which is utilized to generate user-specific fingerprint features by using a feature-extraction process. New representations of the user-specific fingerprint features can be obtained from the same hologram, by changing the reconstruction distance (d) by an amount Δd between the recording plane and the reconstruction plane. This parameter is the key to make the cancellable user-specific fingerprint features using a digital holographic technique, which allows us to choose different reconstruction distances when reissuing the user-specific fingerprint features in the event of compromise. We have shown theoretically that each user-specific fingerprint feature has a unique identity with a high discrimination ability, and the chances of a match between them are minimal. In this aspect, a recognition system has also been demonstrated using the fingerprint biometric of the enrolled person at a particular reconstruction distance. For the performance evaluation of a fingerprint recognition system—the false acceptance ratio, the false rejection ratio and the equal error rate are calculated using correlation. The obtained results show good discrimination ability between the genuine and the impostor populations with the highest recognition rate of 98.23%.

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Section: Introductionmentioning

confidence: 99%

Digital holographic-based cancellable biometric for personal authentication

Verma

Sinha

2016

J. Opt.

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“…These biological codes are inherent biological characteristics of the human body. Once they are leaked, they will cause immeasurable losses for users [32][33][34].…”

Section: Fingerprint Recording and Encryption Processmentioning

confidence: 99%

A Multi-User Encryption and Authentication System Based on Joint Transform Correlation

Zhao

Chi

2019

Entropy

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Optical image encryption technology based on joint transform correlation (JTC) has attracted increasing attention from researchers. We propose a multi-user secure communication system based on the special properties of JTC. Multiple users utilize their own fingerprints to encrypt the plain-text in the encryption process, and each user must be first authenticated at the beginning of the decryption process. Only users with legitimate identities can perform the decryption process, whereas unauthorized users with false identities cannot, so the security of the system is greatly improved. Furthermore, we propose a multi-user double-image encryption method, which can better meet the needs of different security environments. Considering the possibility of overlapping images at the output end, we prove that a JTC-based image encryption system can avoid overlapping images at the output when the distance between the input images is 3W (W is the side length of a square image), which provides a theoretical foundation for further research. Finally, a numerical simulation demonstrates the effectiveness and feasibility of the proposed idea.Entropy 2019, 21, 850 2 of 17 Vilardy et al. analyzed JTC encryption methods and found that it is possible to significantly improve the quality of the decrypted image by introducing a simple nonlinear operation in the encrypted function that contains the joint power spectrum [13][14][15]. Moreover, the JTC system has been applied to different transformation domains, such as the fractional Fourier transform domain [16], Fresnel transform domain [17], and chaotic maps [18,19], which greatly expanded the application of JTC. As is known, cryptography and cryptanalysis are complementary to each other. Therefore, attack schemes against JTC encryption system are proposed [20][21][22][23][24][25][26]. At the same time, the researchers introduced authentication to improve the security of the system [27][28][29][30].In the JTC encryption system, the common feature is that the classified information is controlled by one user. However, in some cases, this information cannot be owned by one user alone. The classified information can be obtained only if two or more users are present simultaneously. In the current study, a multi-user encryption system is proposed based on JTC. The proposed cryptosystem is uniquely useful in practical applications such as co-signing important documents, the control of nuclear buttons, access to certain crucial information, and so on.The remainder of this paper is organized as follows. Section 2 proves the feasibility of the proposed scheme through mathematical theory and the analysis of potential risks. Multi-user double image encryption is proposed, and the position distribution of the output image is analyzed in Section 3. Simulation results are shown in Section 4. Finally, the conclusions are presented in Section 5. The Proposed CryptosystemOn he basis of JTC, the current report proposes a multi-user encryption system with fingerprint keys. Different system users utilize ...

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“…It is an optics based feature extraction technique in which the joint transform correlator is used to extract the features from the biometrics technique [4]. In this technique, a single biometrics of the enrolled person has used as the joint input.…”

Section: Joint Transform Correlatormentioning

confidence: 99%

“…Various cancellable biometric formulations known as biohashing have been proposed [3][4][5]. Biohashing is a two step process.…”

Section: Introductionmentioning

confidence: 99%

“…The specific features of the biometrics can be extracted by using different feature extraction methods such as principle component analysis, Fisher discriminant analysis [3] etc. Recently, an optics based biohashing technique has been proposed, in which the optics based joint transform correlator (JTC) has been used to extract the features of the biometrics [4]. In the present paper, a comparative study of the biohashing technique has been carried out using the principle component analysis (PCA) and the joint transform correlator (JTC) for the feature extraction from the biometrics for both the self generated data base and the standard extended Yale-B data base.…”

Section: Introductionmentioning

confidence: 99%

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Comparative study of biohashing technique using different feature extraction methods

Saini

Sinha

2010

SPIE Proceedings

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A comparative study of biohashing technique using different feature extraction methods has been carried out. A basic biohashing technique involves two steps. First is the extraction of the features from the biometrics and second is the discretization of the obtained features with the random numbers. In this paper, two different data bases and two different feature extraction techniques have been studied. The first data base consists of self generated images and images from ORL and Indian face database and the second data base is taken from the standard Yale-B data base. The two different feature extraction techniques that have been used are the optics based joint transform correlator technique and the principle component analysis technique. Hamming distance has been used to discriminate the different populations. The performance of the techniques has been analyzed by using the false rejection ratio (FRR), false acceptance ratio (FAR) and the equal error rate (EER) in order to compare the effect of the different feature extraction methods on the biohashing technique.

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Optics based biohashing using joint transform correlator

Cited by 8 publications

References 28 publications

Digital holographic-based cancellable biometric for personal authentication

Digital holographic-based cancellable biometric for personal authentication

A Multi-User Encryption and Authentication System Based on Joint Transform Correlation

Comparative study of biohashing technique using different feature extraction methods

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