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Two-Stage Human Verification using HandCAPTCHA and Anti-Spoofed Finger Biometrics with Feature Selection

Asish Bera, Debotosh Bhattacharjee and Hubert P. H. Shum
Expert Systems with Applications (ESWA), 2021

 Impact Factor: 8.5 Top 25% Journal in Computer Science, Artificial Intelligence# Citation: 10#

Two-Stage Human Verification using HandCAPTCHA and Anti-Spoofed Finger Biometrics with Feature Selection
# According to Google Scholar 2023"

Abstract

This paper presents a human verification scheme in two independent stages to overcome the vulnerabilities of attacks and to enhance security. At the first stage, a hand image-based CAPTCHA (HandCAPTCHA) is tested to avert automated bot-attacks on the subsequent biometric stage. In the next stage, finger biometric verification of a legitimate user is performed with presentation attack detection (PAD) using the real hand images of the person who has passed a random HandCAPTCHA challenge. The electronic screen-based PAD is tested using image quality metrics. After this spoofing detection, geometric features are extracted from the four fingers (excluding the thumb) of real users. A modified forward-backward (M-FoBa) algorithm is devised to select relevant features for biometric authentication. The experiments are performed on the Bogazici University (BU) and the IIT-Delhi (IITD) hand databases using the k-nearest neighbor and random forest classifiers. The average accuracy of the correct HandCAPTCHA solution is 98.5%, and the false accept rate of a bot is 1.23%. The PAD is tested on 255 subjects of BU, and the best average error is 0%. The finger biometric identification accuracy of 98% and an equal error rate (EER) of 6.5% have been achieved for 500 subjects of the BU. For 200 subjects of the IITD, 99.5% identification accuracy, and 5.18% EER are obtained.

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BibTeX

@article{bera21twostage,
 author={Bera, Asish and Bhattacharjee, Debotosh and Shum, Hubert P. H.},
 journal={Expert Systems with Applications},
 title={Two-Stage Human Verification using HandCAPTCHA and Anti-Spoofed Finger Biometrics with Feature Selection},
 year={2021},
 volume={171},
 pages={114583},
 numpages={18},
 doi={10.1016/j.eswa.2021.114583},
 issn={0957-4174},
 publisher={Elsevier},
}

RIS

TY  - JOUR
AU  - Bera, Asish
AU  - Bhattacharjee, Debotosh
AU  - Shum, Hubert P. H.
T2  - Expert Systems with Applications
TI  - Two-Stage Human Verification using HandCAPTCHA and Anti-Spoofed Finger Biometrics with Feature Selection
PY  - 2021
VL  - 171
SP  - 114583
EP  - 114583
DO  - 10.1016/j.eswa.2021.114583
SN  - 0957-4174
PB  - Elsevier
ER  - 

Plain Text

Asish Bera, Debotosh Bhattacharjee and Hubert P. H. Shum, "Two-Stage Human Verification using HandCAPTCHA and Anti-Spoofed Finger Biometrics with Feature Selection," Expert Systems with Applications, vol. 171, pp. 114583, Elsevier, 2021.

Supporting Grants

Similar Research

Asish Bera, Ratnadeep Dey, Debotosh Bhattacharjee, Mita Nasipuri and Hubert P. H. Shum, "Spoofing Detection on Hand Images Using Quality Assessment", Multimedia Tools and Applications (MTAP), 2021
Lining Zhang, Hubert P. H. Shum, Li Liu, Guodong Guo and Ling Shao, "Multiview Discriminative Marginal Metric Learning for Makeup Face Verification", Neurocomputing, 2019

 

 

Last updated on 22 February 2024
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