Title

Intrusion detection using fuzzy logic and evolutionary algorithm techniques

Author

Monu Bambroo

Keywords and Phrases

Bucket brigade algorithm; C4.5 rule

Abstract

"An Intrusion Detection System should optimally be capable of detecting both known attacks (misuse detection) and unknown attacks (anomaly detection combined with non-self classification). This thesis research studies the problem of automating the generation of a high-fidelity 'detection model' that can recognize both known and variations on known attacks through the use of a Fuzzy Learning Classifier System"--Abstract, leaf iii.

Department(s)

Computer Science

Degree Name

M.S. in Computer Science

Publisher

University of Missouri--Rolla

Publication Date

Spring 2005

Pagination

x, 62 leaves

Note about bibliography

Includes bibliographical references (pages 85-87).

Rights

© 2005 Monu Bambroo, All rights reserved.

Document Type

Thesis - Citation

File Type

text

Language

English

Library of Congress Subject Headings

Fuzzy logic
Computer security
Genetic algorithms

Thesis Number

T 8785

Print OCLC #

62775537

Link to Catalog Record

Full-text not available: Request this publication directly from Missouri S&T Library or contact your local library.

http://laurel.lso.missouri.edu/record=b5451585~S5

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