Abstract
Recent studies on user identification focused on behavioral aspects of biometric patterns, such as keystroke dynamics or activity cycles in on-line games. The aim of our work is to identify users through the detection and analysis of characteristic network flow patterns. The transformation of concepts from the biometric domain into the network domain leads to the concept of a cybermetric pattern — a pattern that identifies a user based on her characteristic Internet activity.
Chapter PDF
Similar content being viewed by others
References
Holmes, J.P., Wright, L.J., Maxwell, R.L.: A performance evaluation of biometric identification devices. Technical report, Sandia National Laboratories, Albuquerque, NM (1991)
Ashbourn, J.: Biometrics: advanced identity verification. Springer, London (2000)
Chen, K.-T., Hong, L.-W.: User identification based on game-play activity patterns. In: Proc. of the 6th ACM SIGCOMM Workshop on Network and System Support for Games (NetGames 2007), pp. 7–12. ACM, New York (2007)
Bergadano, F., Gunetti, D., Picardi, C.: User authentication through keystroke dynamics. ACM Transactions Information System Security 5(4), 367–397 (2002)
Ahmed, A.A.E., Traore, I.: A new biometric technology based on mouse dynamics. IEEE Transactions on Dependable and Secure Computing 4(3), 165–179 (2007)
Perényi, M., Dang, T.D., Gefferth, A., Molnár, S.: Identification and analysis of peer-to-peer traffic. JCM 1(7), 36–46 (2006)
Lakhina, A., Crovella, M., Diot, C.: Mining anomalies using traffic feature distributions. SIGCOMM Computer Communication Review 35(4), 217–228 (2005)
Stoecklin, M.P., Boudec, J.-Y.L., Kind, A.: A two-layered anomaly detection technique based on multi-modal flow behavior models. In: Claypool, M., Uhlig, S. (eds.) PAM 2008. LNCS, vol. 4979, pp. 212–221. Springer, Heidelberg (2008)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2010 IFIP International Federation for Information Processing
About this paper
Cite this paper
Melnikov, N., Schönwälder, J. (2010). Cybermetrics: User Identification through Network Flow Analysis. In: Stiller, B., De Turck, F. (eds) Mechanisms for Autonomous Management of Networks and Services. AIMS 2010. Lecture Notes in Computer Science, vol 6155. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13986-4_24
Download citation
DOI: https://doi.org/10.1007/978-3-642-13986-4_24
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-13985-7
Online ISBN: 978-3-642-13986-4
eBook Packages: Computer ScienceComputer Science (R0)