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Virtual Fingerprint - Image-Based Authentication Increases Privacy for Users of Mouse-Replacement Interfaces

  • Viktoria Grindle
  • Syed Kamran Haider
  • John MageeEmail author
  • Marten van Dijk
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9178)

Abstract

Current secondary user authentication methods are imperfect. They either rely heavily on a user’s ability to remember key preferences and phrases or they involve providing authentication on multiple devices. However, malicious attacks that compromise a user’s device or discover personal information about the user are becoming more sophisticated and increasing in number. Users who rely on mouse-replacement interfaces face additional privacy concerns when monitored or assisted by caregivers. Our authentication method proposes a way of quantifying a user’s personality traits by observing his selection of images. This method would not be as vulnerable to malicious attacks as current methods are because the method is based on psychological observations that can not be replicated by anyone other than the correct user. As a preliminary evaluation, we created a survey consisting of slides of images and asked participants to click through them. The results indicated our proposed authentication method has clear potential to address these issues.

Keywords

Human-Computer Interaction Mouse-replacement interfaces Security Privacy Behavioral biometric Authentication Camera Mouse Virtual Fingerprint 

Notes

Acknowledgments

The authors would like to thank their participants. We would also like to thank John Chandy for his extensive guidance and the University of Connecticut for hosting the Research Experience for Undergraduates where much of the study discussed in this paper was conducted. Lastly we would like to thank the NSF for providing funding through the CNS-1359329 grant.

References

  1. 1.
    Ahmed, A.A.E., Traore, I.: Detecting computer intrusions using behavioral biometrics. In: PST (2005)Google Scholar
  2. 2.
    Ballin, L., Baladin, S.: An exploration of loneliness: communication and the social networks of older people with cerebral palsy. J. Intellect. Dev. Disabil. 32(4), 315–327 (2007)CrossRefGoogle Scholar
  3. 3.
    Barbosa, N.: Strategies: an inclusive authentication framework. In: Proceedings of the 16th International ACM SIGACCESS Conference on Computers & Accessibility (ASSETS 2014), pp. 335–336. ACM (2014)Google Scholar
  4. 4.
    Betke, M., Gips, J., Fleming, P.: The camera mouse: visual tracking of body features to provide computer access for people with severe disabilities. IEEE Trans. Neural Syst. Rehabil. Eng. 10(1), 1–10 (2002). IEEECrossRefGoogle Scholar
  5. 5.
    Cooper, L., Baladin, S., Trembath, D.: The loneliness experiences of young adults with cerebral palsy who use alternative and augmentative communication. Augment. Altern. Commun. 25(3), 154–164 (2009)CrossRefGoogle Scholar
  6. 6.
    Denning, T., Bowers, K., van Dijk, M., Juels, A.: Exploring implicit memory for painless password recovery. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI 2011), pp. 2615–2618. ACM (2011)Google Scholar
  7. 7.
    Dhamija, R. Perrig, A.: Deja vu: a user study using images for authentication. In: Proceedings of the 9th Conference on USENIX Security Symposium, SSYM 2000, vol. 9. USENIX Association (2000)Google Scholar
  8. 8.
    Jermyn, I., Mayer, A.J., Monrose, F., Reiter, M.K., Rubin, A.D.: The design and analysis of graphical passwords. In: Usenix Security (1999)Google Scholar
  9. 9.
    Lewis, M.: Cerebral palsy and online social networks. In: The 12th International ACM SIGACCESS Conference on Computers and Accessibility (ASSETS 2010). ACM, October 2010Google Scholar
  10. 10.
    Magee, J.J., Betke, M.: Automatically generating online social network messages to combat social isolation of people with disabilities. In: Stephanidis, C., Antona, M. (eds.) UAHCI 2013, Part II. LNCS, vol. 8010, pp. 684–693. Springer, Heidelberg (2013) Google Scholar
  11. 11.
    Perrig, A., Song, D.: Hash visualization: a new technique to improve real-world security. In: International Workshop on Cryptographic Techniques and E-Commerce, pp. 131–138 (1999)Google Scholar
  12. 12.
    Schmidt, A-D., Bye, R, Schmidt, H-G., Clausenm J., Kiraz, O., Yuksel, K.A., Camtepe, S.A., Albayrak, S.: Static analysis of executables for collaborative malware detection on android. In: IEEE International Conference on Communications, ICC 2009, pp. 1–5. IEEE (2009)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Viktoria Grindle
    • 1
  • Syed Kamran Haider
    • 2
  • John Magee
    • 1
    Email author
  • Marten van Dijk
    • 2
  1. 1.Math and Computer Science DepartmentClark UniversityWorcesterUSA
  2. 2.Department of Electrical Engineering and Computer ScienceUniversity of ConnecticutStorrsUSA

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