Continuous biometric authentication: Can it be more practical?

Proceedings - 2010 12th IEEE International Conference on High Performance Computing and Communications, HPCC 2010

Volumn , Issue , 2010, Pages 647-652

  Al Solami, Eesa ^a   Boyd, Colin ^a   Clark, Andrew ^a   Islam, Asadul K ^a  

^a QUEENSLAND UNIVERSITY OF TECHNOLOGY   (Australia)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 78149337951     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/HPCC.2010.65     Document Type: Conference Paper

References (22)

1. A.A.E. Ahmed and I. Traore. Detecting computer intrusions using behavioral biometrics. In Third Annual Conference on Privacy, Security and Trust, St. Andrews, New Brunswick, Canada, 2005.
2. E. Ahmed, A. Clark, and G. Mohay. A novel sliding window based change detection algorithm for asymmetric traffic. In Network and Parallel Computing, 2008. NPC 2008. IFIP International Conference on, pages 168-175, 2008.
3. A. Azzini and S. Marrara. Impostor Users Discovery Using a Multimodal Biometric Continuous Authentication Fuzzy System. Lecture Notes in Computer Science, 5178:371-378, 2008.
4. M. Basseville and I.V. Nikiforov. Detection of abrupt changes: theory and application. Prentice Hall, 1993.
5. D.E. Denning. An intrusion-detection model. IEEE Transactions on software engineering, pages 222-232, 1987.
6. R. Fujimaki, T. Yairi, and K. Machida. An approach to spacecraft anomaly detection problem using kernel feature space. In Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining, page 410. ACM, 2005.
7. L.A. Gordon, M.P. Loeb, W. Lucyshyn, and R. Richardson. CSI/FBI Computer crime and security survey 2006. Computer Security Institute publications, 2006.
8. D. Gunetti and C. Picardi. Keystroke analysis of free text. ACM Transactions on Information and System Security (TISSEC), 8(3):312-347, 2005.
9. F. Gustafsson. The marginalized likelihood ratio test for detecting abrupt changes. IEEE Transactions on automatic control, 41(1):66-78, 1996.
10. F. Gustafsson. Adaptive filtering and change detection. John Wiley & Sons Inc, 2000.
11. K. Hempstalk. Continuous Typist Verification using Machine Learning. PhD thesis, The University of Waikato, 2009.
12. Y. Kawahara and M. Sugiyama. Change-point detection in time-series data by direct density-ratio estimation. In Proceedings of 2009 SIAM International Conference on Data Mining (SDM2009), pages 389-400, 2009.
13. Y. Ke, R. Sukthankar, and M. Hebert. Event detection in crowded videos. In IEEE International Conference on Computer Vision, volume 23, pages 38-41. Citeseer, 2007.
14. K.S. Killourhy and R.A. Maxion. Comparing Anomaly-Detection Algorithms for Keystroke Dynamics. In IEEE/IFIP International Conference on Dependable Systems & Networks, 2009. DSN'09, pages 125-134, 2009.
15. G. Kwang, R.H. Yap, T. Sim, and R. Ramnath. An Usability Study of Continuous Biometrics Authentication. In Proceedings of the Third International Conference on Advances in Biometrics, pages 828-837. Springer-Verlag, 2009.
16. J. Liu, FR Yu, C.H. Lung, and H. Tang. A Framework of Combining Intrusion Detection and Continuous Authentication in Mobile Ad Hoc Networks. In IEEE International Conference on Communications, 2008. ICC'08, pages 1515-1519, 2008.
17. J. McHugh. Intrusion and intrusion detection. International Journal of Information Security, 1(1):14-35, 2001.
18. U. Murad and G. Pinkas. Unsupervised Profiling for Identifying Superimposed Fraud. In Proceedings of the Third European Conference on Principles of Data Mining and Knowledge Discovery, page 261. Springer-Verlag, 1999.
19. L. O'Gorman. Comparing passwords, tokens, and biometrics for user authentication. Proceedings of the IEEE, 91(12):2021-2040, 2003.
20. M. Pusara. An Examination of User Behavior for Re-authentication. PhD thesis, Center for Education and Research in Information Assurance and Security, Purdue Univeristy (August 2007).
21. M. Pusara and C.E. Brodley. User re-authentication via mouse movements. In Proceedings of the 2004 ACM workshop on Visualization and data mining for computer security, pages 1-8. ACM New York, NY, USA, 2004.
22. R.V. Yampolskiy and V. Govindaraju. Taxonomy of Behavioural Biometrics. Behavioral Biometrics for Human Identification: Intelligent Applications, page 1, 2009.