An Approach To Enhance Level Of Security To The ATM Customers By Hiding Face Biometric Data Using Steganography

K. Lavanya;  ; C. Naga Raju;

doi:10.26634/jit.1.3.1911

An Approach To Enhance Level Of Security To The ATM Customers By Hiding Face Biometric Data Using Steganography

i-manager s Journal on Information Technology ◽

10.26634/jit.1.3.1911 ◽

2012 ◽

Vol 1 (3) ◽

pp. 25-30

Author(s):

K. Lavanya ◽

◽

C. Naga Raju ◽

Keyword(s):

Biometric Data ◽

Face Biometric

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Class-Distribution Preserving Transform for Face Biometric Data Security

2007 IEEE International Conference on Acoustics, Speech and Signal Processing - ICASSP '07 ◽

10.1109/icassp.2007.366192 ◽

2007 ◽

Cited By ~ 6

Author(s):

Y C Feng ◽

Pong C Yuen

Keyword(s):

Data Security ◽

Biometric Data ◽

Class Distribution ◽

Face Biometric

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Covert exchange of face biometric data using steganography

2013 5th Computer Science and Electronic Engineering Conference (CEEC) ◽

10.1109/ceec.2013.6659460 ◽

2013 ◽

Cited By ~ 4

Author(s):

Rasher D. Rashid ◽

Sabah A. Jassim ◽

Harin Sellahewa

Keyword(s):

Biometric Data ◽

Face Biometric

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Masquerade Attack Analysis for Secured Face Biometric System

International Journal of Recent Technology and Engineering - 2 ◽

10.35940/ijrte.b6309.0710221 ◽

2021 ◽

Vol 10 (2) ◽

pp. 225-232

Author(s):

Sanjeeva Kumar M. Hatture ◽

◽

Shweta Policepatil ◽

Keyword(s):

Hybrid Approach ◽

Personal Identification ◽

Biometric System ◽

Biometric Data ◽

Left Turn ◽

Liveness Detection ◽

Identity Based ◽

Recognition Systems ◽

Biometric Trait ◽

Face Biometric

Biometrics systems are mostly used to establish an automated way for validating or recognising a living or nonliving person's identity based on physiological and behavioural features. Now a day’s biometric system has become trend in personal identification for security purpose in various fields like online banking, e-payment, organizations, institutions and so on. Face biometric is the second largest biometric trait used for unique identification while fingerprint is being the first. But face recognition systems are susceptible to spoof attacks made by nonreal faces mainly known as masquerade attack. The masquerade attack is performed using authorized users’ artifact biometric data that may be artifact facial masks, photo or iris photo or any latex finger. This type of attack in Liveness detection has become counter problem in the today's world. To prevent such spoofing attack, we proposed Liveness detection of face by considering the countermeasures and texture analysis of face and also a hybrid approach which combine both passive and active liveness detection is used. Our proposed approach achieves accuracy of 99.33 percentage for face anti-spoofing detection. Also we performed active face spoofing by providing several task (turn face left, turn face right, blink eye, etc) that performed by user on live camera for liveness detection.

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