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Accuracy Comparison of Classification Techniques for Mouse Dynamics-Based Biometric CaRP

  • Sushama KulkarniEmail author
  • Hanmant Fadewar
Conference paper
  • 11 Downloads
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1090)

Abstract

Combining more than one authentication schemes enhances the robustness of a system against cyber-attacks. In this paper, we introduce a novel mouse dynamics-based biometric CaRP (CAPTCHA as gRaphical Password). It combines mouse dynamics-based biometric authentication scheme with knowledge-based authentication scheme. This study primarily focuses on the comparison of classification accuracy of binary decision tree, SVM, and ANN for proposed mouse dynamics-based authentication scheme of CaRP.

Keywords

Completely Automated Public Turing Test to Tell Computers and Humans Apart (CAPTCHA) Web security Binary decision tree Support Vector Machines (SVM) Artificial Neural Network (ANN) Mouse dynamics CAPTCHA as gRaphical passwords (CaRP) 

Notes

Acknowledgements

We wish to acknowledge volunteer participants of this study who took time to handle the proposed system and provided their permission to collect mouse dynamics data.

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Copyright information

© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  1. 1.School of Computational SciencesS. R. T. M. UniversityNandedIndia

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