Biometric Finger Vein Recognition Methods for Authentication

Wagh, Dnyaneshwari P.; Fadewar, H. S.; Shinde, G. N.

doi:10.1007/978-981-32-9515-5_5

Cited by 18 publications

(6 citation statements)

References 16 publications

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“…These behavioural recognition modalities are based on the actions of human beings. Secondly, the physiological biometrics are the well-known iris [38,39,40], face [41,42,43] and fingerprint [44,6,45] and some others less popular such as finger veins [46,47], ear [48,49] and footprint [50,51] which are based on physical characteristics of a human being.…”

Section: Types Of Biometricsmentioning

confidence: 99%

ELEKTRA: ELEKTRokardiomatrix application to biometric identification with convolutional neural networks

Fuster-Barceló

Peris-López²,

Cámara³

2022

Neurocomputing

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Section: Types Of Biometricsmentioning

confidence: 99%

ELEKTRA: ELEKTRokardiomatrix application to biometric identification with convolutional neural networks

Fuster-Barceló

Peris-López²,

Cámara³

2022

Neurocomputing

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“…Finger Vein authentication schemes commonly utilized in various applications for authentication purposes [1,2]. Unlike conventional authentication tools, like PIN, password always at risk of being forgotten or stolen, but the biometric authentication provides the best convenience for the user [3,4].…”

Section: Introductionmentioning

confidence: 99%

Enhanced Elman Spike Neural Network Optimized with Glowworm Swarm Optimization for Authentication of Multiple Transaction Using Finger Vein

Mary Joans,

Leena Jasmine,

Ponsudha

2022

SSRN Journal

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“…Extracting the contour means finding the maxima of the modulus of the gradient vector [2,3]. This is one of the reasons why contours remain in the image when encrypting in the RSA system since RSA encryption is based on exponentiation modulo some natural number.…”

Section: Introductionmentioning

confidence: 99%

Bit Operations With Elements of the Rsa Algorithm in Encryption-Decryption of Color Images

Kovalchuk¹,

Peleckh²,

Бубела³

2022

MEM

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An image as a stochastic signal is one of the most common forms of information. Protecting images from unauthorized access and applying is a correspondingly urgent task. This causes the use of well-known classical encryption methods in the case of image encryption. But the image is a signal that possesses, in addition to typical informativeness, also visual informativeness. Informativeness for modern image processing methods makes it possible to ensure unauthorized access. Creating an attack on an encrypted image is possible in two ways: by traditional hacking of encryption methods, or by classical methods of visual image processing (filtering, highlighting contours, etc.). In this regard, one more requirement is put forward to encryption methods in the case of their application concerning images - this is the complete noise of the encrypted image. This is necessary so that the use of visual image processing methods becomes impossible. The RSA algorithm is one of the most widely known industrial standards for encrypting signals. Unlike symmetric encryption, in an open-key encryption scheme, it is impossible to calculate the decryption procedure, knowing the encryption procedure. Namely, the working time of the algorithm for calculating the decryption procedure is so great that it cannot be implemented on any modern computers, as well as on computers of the future. Such coding schemes are called asymmetric. Therefore, the urgent task is to implement the application of the RSA algorithm so that when encrypting an image: – the cryptographic stability of the RSA algorithm has not become worse; – the full image noise was achieved to prevent the use of visual image processing techniques. The algorithm of elements of the RSA algorithm, as the most resistant to unauthorized decryption of signals, and bitwise operations for a compatible combination during encryption and decryption of images is proposed by the authors. Encryption - decryption is performed without additional noise. The proposed algorithm is applied to images in which there are strictly extracted contours. Elements of the RSA algorithm are assigned to perform bitwise operations on the intensity values of pixels of a color image. The developed algorithm has higher cryptographic stability compared to the traditional RSA algorithm. The authors described the possibilities of using elements of the RSA algorithm in bitwise transformations when encrypting and decrypting images. The results of encryption simulation for cryptographic transformations of color images of a given dimension are presented. Modified models and algorithmic procedures of key formation processes of direct and inverse cryptographic transformations have been developed. They are reduced to elemental mathematical operations.

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Biometric Finger Vein Recognition Methods for Authentication

Cited by 18 publications

References 16 publications

ELEKTRA: ELEKTRokardiomatrix application to biometric identification with convolutional neural networks

ELEKTRA: ELEKTRokardiomatrix application to biometric identification with convolutional neural networks

Enhanced Elman Spike Neural Network Optimized with Glowworm Swarm Optimization for Authentication of Multiple Transaction Using Finger Vein

Bit Operations With Elements of the Rsa Algorithm in Encryption-Decryption of Color Images

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