Biometric Authentication and Identification using Behavioral Biometrics Technique of Signature Verification
Shalini Dhiman1, Munish Sabharwal2
1Shalini Dhiman, CSE Department, Chandigarh University, Chandigarh, India.
2Munish Sabharwal, CSE Department, Chandigarh University, Chandigarh, India
Manuscript received on 21 September 2019 | Revised Manuscript received on 30 September 2019 | Manuscript Published on 01 October 2019 | PP: 33-38 | Volume-8 Issue-9S4 July 2019 | Retrieval Number: I11060789S419 /19©BEIESP | DOI: 10.35940/ijitee.I1106.0789S419
Open Access | Editorial and Publishing Policies | Cite | Mendeley | Indexing and Abstracting
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open-access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Authentication using biometrics is on the rise due to various security concerns and especially in India with the advent of Digital India concept promoting the wide use of aadhar as an authentication mechanism. The authentication using a login and a password are fading away due to the various malpractices and fraudulent methods that have been developed which pose a threat to this kind of authentication and security mechanism. Signature verification is one of the important aspects of biometric authentication which is slowly finding its use in certain niche organizations. The present study uses an ensemble approach, stacking to authenticate or validate a user by his signature and proposes a hybrid model using three algorithms namely, Random Tree, Logistic Regression & Multi-Layer Perceptron for achieving better accuracy.
Keywords: Signature verification, Behavioral biometrics, Authentication, Random Tree, Logistic Regression, MLP.
Scope of the Article: Digital System and Logic Design