Data modeling of network dynamics

Holger M. Jaenisch; James W. Handley; Jeffery P. Faucheux; Brad Harris

doi:10.1117/12.502472

30 December 2003 Data modeling of network dynamics

Holger M. Jaenisch, James W. Handley, Jeffery P. Faucheux, Brad Harris

Proceedings Volume 5200, Applications and Science of Neural Networks, Fuzzy Systems, and Evolutionary Computation VI; (2003) https://doi.org/10.1117/12.502472
Event: Optical Science and Technology, SPIE's 48th Annual Meeting, 2003, San Diego, California, United States

Abstract

This paper highlights Data Modeling theory and its use for text data mining as a graphical network search engine. Data Modeling is then used to create a real-time filter capable of monitoring network traffic down to the port level for unusual dynamics and changes in business as usual. This is accomplished in an unsupervised fashion without a priori knowledge of abnormal characteristics. Two novel methods for converting streaming binary data into a form amenable to graphics based search and change detection are introduced. These techniques are then successfully applied to 1999 KDD Cup network attack data log-on sessions to demonstrate that Data Modeling can detect attacks without prior training on any form of attack behavior. Finally, two new methods for data encryption using these ideas are proposed.

Citation Download Citation

Holger M. Jaenisch, James W. Handley, Jeffery P. Faucheux, and Brad Harris "Data modeling of network dynamics", Proc. SPIE 5200, Applications and Science of Neural Networks, Fuzzy Systems, and Evolutionary Computation VI, (30 December 2003); https://doi.org/10.1117/12.502472

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