You are here

Resource-sensitive intrusion detection models for network traffic

Download pdf | Full Screen View

Date Issued:
2003
Summary:
Network security is an important subject in today's extensively interconnected computer world. The industry, academic institutions, small and large businesses and even residences are now greatly at risk from the increasing onslaught of computer attacks. Such malicious efforts cause damage ranging from mere violation of confidentiality and issues of privacy up to actual financial loss if business operations are compromised, or even further, loss of human lives in the case of mission-critical networked computer applications. Intrusion Detection Systems (IDS) have been used along with the help of data mining modeling efforts to detect intruders, yet with the limitation of organizational resources it is unreasonable to inspect every network alarm raised by the IDS. Modified Expected Cost of Misclassification ( MECM) is a model selection measure that is resource-aware and cost-sensitive at the same time, and has proven to be effective for the identification of the best resource-based intrusion detection model.
Title: Resource-sensitive intrusion detection models for network traffic.
104 views
36 downloads
Name(s): Abushadi, Mohamed E.
Florida Atlantic University, Degree grantor
Khoshgoftaar, Taghi M., Thesis advisor
Type of Resource: text
Genre: Electronic Thesis Or Dissertation
Issuance: monographic
Date Issued: 2003
Publisher: Florida Atlantic University
Place of Publication: Boca Raton, Fla.
Physical Form: application/pdf
Extent: 159 p.
Language(s): English
Summary: Network security is an important subject in today's extensively interconnected computer world. The industry, academic institutions, small and large businesses and even residences are now greatly at risk from the increasing onslaught of computer attacks. Such malicious efforts cause damage ranging from mere violation of confidentiality and issues of privacy up to actual financial loss if business operations are compromised, or even further, loss of human lives in the case of mission-critical networked computer applications. Intrusion Detection Systems (IDS) have been used along with the help of data mining modeling efforts to detect intruders, yet with the limitation of organizational resources it is unreasonable to inspect every network alarm raised by the IDS. Modified Expected Cost of Misclassification ( MECM) is a model selection measure that is resource-aware and cost-sensitive at the same time, and has proven to be effective for the identification of the best resource-based intrusion detection model.
Identifier: 9780496218929 (isbn), 13054 (digitool), FADT13054 (IID), fau:9919 (fedora)
Collection: FAU Electronic Theses and Dissertations Collection
Note(s): College of Engineering and Computer Science
Thesis (M.S.)--Florida Atlantic University, 2003.
Subject(s): Computer networks--Security measures--Automation
Computers--Access control
Data mining
Computer security
Held by: Florida Atlantic University Libraries
Persistent Link to This Record: http://purl.flvc.org/fcla/dt/13054
Sublocation: Digital Library
Use and Reproduction: Copyright © is held by the author, with permission granted to Florida Atlantic University to digitize, archive and distribute this item for non-profit research and educational purposes. Any reuse of this item in excess of fair use or other copyright exemptions requires permission of the copyright holder.
Use and Reproduction: http://rightsstatements.org/vocab/InC/1.0/
Host Institution: FAU
Is Part of Series: Florida Atlantic University Digital Library Collections.