JSM 2004 - Toronto

Abstract #301259

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Activity Number: 425
Type: Contributed
Date/Time: Thursday, August 12, 2004 : 10:30 AM to 12:20 PM
Sponsor: Section on Statistical Computing
Abstract - #301259
Title: The Development and Exploration of Online Classifiers for Backscatter from Denial of Service Attacks
Author(s): Kendall Giles*+ and David J. Marchette and Carey Priebe
Companies: Johns Hopkins University and Naval Surface Warfare Center and Johns Hopkins University
Address: 7694 Willow Point Dr., Falls Church, VA, 22042,
Keywords: classification ; backscatter ; denial of service ; network security
Abstract:

As a motivation for understanding network attacks and designing better network security systems, this paper details methods for the investigation of denial of service attacks using statistical classification techniques. In particular, we focus on classifying what appear to be different attack types based on analysis of sensed denial-of-service attack artifacts called backscatter. We also emphasize developing models and classifiers for the purpose of detecting the onset of distributed denial-of-service attacks using sensed packets. With these goals in mind, we develop and empirically evaluate classifiers and classification methodologies, with a concentration on online classifiers. These classifiers would necessarily be useful in real-time sensor network settings.

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