Kumari P and Thangaraj P
Optimized DeLBPA Algorithm for Binary Pattern Biometric Key Authentication in Cloud Data Production
Dynamic Systems and Applications 30 (2021) No. 10, 1545 – 1559

https://doi.org/10.46719/dsa202130.10.01

ABSTRACT.
The global enterprise cloud computing services development and security need an organization to maintain and maintain critical digital data. It is the job of researchers who constantly challenge the security dimension of companies and cloud security solutions. Biometric systems provide automatic identification based on a single unique function and characteristic. Personal identities are established with the help of biometrics. Various biological features, such as irises, fingerprints, and faces, are recognized as false people identification. The uniqueness of the biometric information held by each individual is unique. Today, security is information, business, e-commerce, military, and other important factors. In the paper, to propose Deep Local Binary Pattern Recognition (DeLBPA) by analyzing the user’s face shape and providing a face pattern-based key to user authentication protection. In the face, the image removed the noise and preprocessed using a bilateral filter algorithm. It uses the deep LBP algorithm to convert the user’s face into a grayscale histogram image and divide it into binary value rows and columns to detect facial features. The training image set is converted to gray levels. The crossover operator is applied to multiple samples per person to produce a larger number of images. The biometric face system includes image capture, feature extraction, face pattern key generation, and verification process. In this work, a person can be certified to provide a calculated weight above a threshold. This overcomes the authentication problem when the relevant trait lacks real users or a poor-quality biometric input.

Keywords: Deep LBP, biometric key generation, encryption, bilateral filter, biometric authentication.