Cryptography based on retina information

Abstract

The security of message information has drawn more attention nowadays, so; cryptography has been used extensively. This research aims to generate secured cipher keys from retina information to increase the level of security. The proposed technique utilizes cryptography based on retina information. The main contribution is the original procedure used to generate three types of keys in one system from the retina vessel's end position and improve the technique of three systems, each with one key. The distances between the center of the diagonals of the retina image and the retina vessel's end (diagonal center-end (DCE)) represent the first key. The distances between the center of the radius of the retina and the retina vessel's end (radius center-end (RCE)) represent the second key. While the diagonal-radius center and the retina vessel's end (diagonal-radius center-end (DRCE)) represent the third key. The results illustrate the process's validity and applicability. Also, improve the time required to decrypt the cipher-text by a brute force attack (BFA) from (4.358e+139) year in the compared technique to (1.3074e+140) year for retina3. The BFA time will increase with increasing the number of retina vessels, as in retina1, 2, and 3, which have 24, 53, and 103 retina vessels.

Using Crossover Area of the Retinal Eye to Generate a Secret Key Based on Deep Learning- YOLO-v5 Object Detection Algorithm

“…Weaknesses in key creation and utilization Standard RC4 algorithm vulnerabilities. Alrifaee and Ismaeel [18] Three types of keys generated from retina vessel's Keys based on DCE, RCE, and DRCE distances in retina.…”

“…Retinal biometric features offer high precision due to their stability over a lifetime [20]. Previous work, such as Tajuddin and Nandini [15], Mazher and Waleed [16], Salih and Mahdawi [17], Alrifaee and Ismaeel [18], has demonstrated the use of retinal biometric data for cryptographic key generation and key management, leveraging the uniqueness and stability of the retinal blood vessel patterns. The proposed algorithms and techniques aim to enhance the security and reliability of cryptographic systems by utilizing the retinal biometric modality.…”

Adaptation issues of machine learning in safety digitization

“…This interest could yield a torrent of unintellectual data utilizing amorphous stylistic communication commonly available to the public. The security investigators may be ethical white hat hackers assembling Internet communities to harmonize discovery schemes [3]- [5]. Here, in this scheme, specialists find vulnerabilities presented in the security applications and information to the manufacturer.…”