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User Authentication from Mouse Movement Data Using SVM Classifier

  • Bashira Akter Anima
  • Mahmood Jasim
  • Khandaker Abir RahmanEmail author
  • Adam Rulapaugh
  • Md Hasanuzzaman
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10052)

Abstract

This paper presents a robust user authentication system by gleaning raw mouse movement data. The data was collected using a publicly available tool called Recording User Input (RUI) from 23 subjects analyzed for three types of mouse actions - Mouse Move, Point-and-Click on Left or Right mouse button, and Drag-and-Drop. Samples are broken down to unit blocks comprising a certain number of actions and from each block seventy-four features are extracted to construct feature vectors. The proposed system was rigorously tested against public benchmark data. Experiment results generated by using the Support Vector Machine (SVM) classifier shows a False Rejection Rate (FRR) of 1.1594 % and a False Acceptance Rate (FAR) of 1.9053 % when the block size was set for 600 actions. After reducing dimensions using Principle Component Analysis (PCA), SVM classifier shows FRR of 1.2081 % and FAR of 2.3604 %. Compared with the existing methods based on mouse movements, our method shows significantly lower error rates, which we opine are viable enough to become an alternate to conventional authentication systems.

Keywords

Biometric Cyber behavioral biometrics Mouse dynamics Person identification SVM 

Notes

Acknowledgements

This work was done under the assistance of Ministry of Posts, Telecommunications and Information Technology Fellowship given by the Information and Communication Technology division of Ministry of Posts, Telecommunications and Information Technology, Government of the People’s Republic of Bangladesh.

References

  1. 1.
    Jain, A.K., Pankanti, S.: Biometric identification. Commun. ACM 43, 91–98 (2000)CrossRefGoogle Scholar
  2. 2.
    Kukreja, U., Stevenson, W.E., Ritter, F.E.: RUI: recording user input from interfaces under Windows and Mac OS X. Behav. Res. Methods 38(4), 656–659 (2011)CrossRefGoogle Scholar
  3. 3.
    Cristianini, N., Shawe-Taylor, J.: An Introduction to Support Vector Machines: And Other Kernel-based Learning Methods. Cambridge University Press, New York (2000)CrossRefzbMATHGoogle Scholar
  4. 4.
    Jolliffe, I.: Principal Component Analysis. Springer, New York (1986)CrossRefzbMATHGoogle Scholar
  5. 5.
    Chang, C.C., Lin, C.J.: LIBSVM: a library for support vector machines. ACM Trans. Intell. Syst. Technol. 2, 1–27 (2011). Article No. 27CrossRefGoogle Scholar
  6. 6.
    Nakkabi, Y., Traoré, I., Ahmed, A.A.E.: Improving mouse dynamics biometric performance using variance reduction via extractors with separate features. Trans. Sys. Man Cyber. Part A 40(6), 1345–1353 (2010)CrossRefGoogle Scholar
  7. 7.
    Ahmed, A.A.E., Traoré, I.: A new biometric technology based on mouse dynamics. IEEE Trans. Dependable Sec. Comput. 4(3), 165–179 (2007)CrossRefGoogle Scholar
  8. 8.
    Pusara, M., Brodley, C.E.: User re-authentication via mouse movements. In: ACM Workshop on Visualization and Data Mining for Computer Security. ACM Press (2004)Google Scholar
  9. 9.
    Muthumari, R.S., Pepsi, M.B.B.: Mouse gesture based authentication using machine learning algorithm. In: International Conference on Advanced Communication Control and Computing Technologies (2014)Google Scholar
  10. 10.
    Muthumari, G., Shenbagaraj, R., Pepsi, M.B.B.: Authentication of user based on mouse-behavior data using classification. In: IEEE International Conference on Innovations in Engineering and Technology (ICIETŠ) (2014)Google Scholar
  11. 11.
    Lakshmipriya, D., Balakrishnan, J.R.: Holistic and procedural features for authenticating users 16, 98–101 (2014)Google Scholar
  12. 12.
    Rahman, K.A., Moormann, R., Dierich, D., Hossain, M.: Continuous user verification via mouse activities. In: Dziech, A., et al. (eds.) MCSS 2015. CCIS, vol. 566, pp. 170–181. Springer, Heidelberg (2015). doi: 10.1007/978-3-319-26404-2_14 CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG 2016

Authors and Affiliations

  • Bashira Akter Anima
    • 1
  • Mahmood Jasim
    • 1
  • Khandaker Abir Rahman
    • 2
    Email author
  • Adam Rulapaugh
    • 2
  • Md Hasanuzzaman
    • 1
  1. 1.University of DhakaDhakaBangladesh
  2. 2.Saginaw Valley State UniversityUniversity CenterUSA

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