ENHANCING home security through visual CRYPTOGRAPHY

Title

ENHANCING home security through visual CRYPTOGRAPHY

Creator

Mohan J.; R D.R.

Description

Home security systems in the recent times have gained greater importance due to increasing threat in the society. Biometrics deals with automated approaches of recognizing a user or verifying the user identity based on behavioral or physiological features. Visual cryptography is a scheme of secret sharing where a secret image is encrypted into shares which disclose no data independently about the original secret image. As the template of biometric are stored in centralized database due to the threats of security the template of biometric may be changed by attacker. If the template of biometric is changed then the authorized user will not be permitted to access the resource. To manage this problem the schemes of visual cryptography can be used to secure the face recognition. Visual cryptography offers huge ways for supporting such needs of security as well as additional authentication layer. To manage this problem the visual cryptography schemes can be used to secure digital biometric information privacy. In this approach the face or private image is dithered in two varied host images that is sheets and are stored in separate servers of data so as to assure that the original image can get extracted only by accessing both sheets together at a time and a single sheet will not be capable to show any data of private image. The main aim of the study is to propose an algorithm which is a combination of CVC and Siamese network. This research implements visual cryptography for face images in a biometric application. The Siamese network is essential to solve one shot learning by representation of learning feature that are compared to verification tasks. In this research face authentication helps in accomplishing robustness by locating face image from an n input image. This research explores the availability of using visual cryptography for securing the privacy to biometric data. The results of the proposed approach provide an accuracy of 93% which is found to be superior when compared with that of the approaches that are already in practice. 2020

Source

Microprocessors and Microsystems, Vol-80

Date

2021-01-01

Publisher

Elsevier B.V.

Subject

Biometric authentication; CVC, Siamese network; Security; Visual cryptography

Coverage

Mohan J., Research Scholar, Department of Computer Science, Bharathiar University, Coimbatore, India; R D.R., Associate Professor, Department of Computer Science, CHRIST(Deemed to be University), Bengaluru, India

Rights

Restricted Access

Relation

ISSN: 1419331; CODEN: MIMID

Format

Online

Language

English

Type

Article

Identifier

https://doi.org/10.1016/j.micpro.2020.103355

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85094858951&doi=10.1016%2fj.micpro.2020.103355&partnerID=40&md5=e8237fec0cbb8129e98292c3f3f9524c