Masters Theses
Abstract
"Intrusion detection systems (IDS) attempt to address the vulnerability of computer-based systems for abuse by insiders and to penetration by outsiders. An IDS is often required to examine an enormous amount of data generated by computer networks to assist in the abuse detection process. It is therefore required to develop automated tools that address these requirements to assist system operators in the detection of violations of existing security policies. In this research, an automated IDS is proposed for insider threats in a distributed system. The proposed IDS functions as an anomaly detector for insider system operations based on the analysis of the system's log files. The approach integrates dynamic programming and adaptive resonance theory (ARTI) clustering. The integrated approach aligns sequences of log events with prototypical sequences of events for performing tasks and classifies the aligned sequences for anomaly detection and task discrimination. The system examined for this research is a Boots System for controlling the movement of boots from one place to another under specific security restrictions related to the boot orders. The integrated pattern recognition technique, experiments performed using the data from the Boots system and experimental results are presented and discussed" -- Abstract, p. iii
Advisor(s)
Stanley, R. Joe
Committee Member(s)
McMillin, Bruce M.
Miller, Ann K.
Department(s)
Electrical and Computer Engineering
Degree Name
M.S. in Computer Engineering
Publisher
University of Missouri--Rolla
Publication Date
Spring 2003
Pagination
viii, 52 pages
Note about bibliography
Includes bibliographical references (pages 50-51)
Rights
© 2003 Amod Pandit, All rights reserved.
Document Type
Thesis - Restricted Access
File Type
text
Language
English
Subject Headings
Computer securityComputer networks -- Security measuresPattern recognition systems -- Design
Thesis Number
T 8216
Print OCLC #
54017063
Recommended Citation
Pandit, Amod, "An integrated pattern recognition approach for anomaly detection in a distributed system" (2003). Masters Theses. 2351.
https://scholarsmine.mst.edu/masters_theses/2351
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