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Activity Number: 54
Type: Topic Contributed
Date/Time: Sunday, August 3, 2008 : 4:00 PM to 5:50 PM
Sponsor: Section on Statistical Computing
Abstract - #301628
Title: Statistical Methods for Detecting Computer Attacks from Streaming Internet Data
Author(s): Ginger Davis*+ and Karen Kafadar and David Marchette
Companies: University of Virginia and University of Colorado at Denver and Health Sciences Center and Naval Surface Warfare Center
Address: P.O. Box 400747, Charlottesville, VA, 22904,
Keywords:
Abstract:

Successful strategies for network security depend upon collating massive data features into usable variables, high-performance and computationally efficient methods for anomaly detection, and ability to predict typical behavior so atypical and abnormal events can be better identified. We define data variables (packets, sessions, activities) from network data and how they can be used in models for user profiles, workload management, application verification, etc. New techniques to process these data will be discussed, including visualization of data sets, leading to methods for clustering images. We provide examples of these methods on motivating internet packet data streams.

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Revised September, 2008