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Title: Data mining approach for hybrid intrusion detection system
Researcher: Kola Sujatha, P
Guide(s): Kannan, A
Keywords: Data mining
Eccentric classifier
Hybrid intrusion detection system
Information and communication engineering
Intrusion detection system
Malicious behavior
Network attacks
Upload Date: 8-Sep-2014
University: Anna University
Completed Date: 01/09/2012
Abstract: An intrusion detection system is used to detect several types of malicious behaviors that can compromise the security and trust of a computer system The intrusion detection system detects network attacks against vulnerable services data driven attacks on applications host based attacks such as privilege escalation unauthorized logins and access to sensitive files and malware It operates either at the host level or at the network level using either misuse or signature based detection or anomaly detection Normally attacks that cannot be detected by network based intrusion detection system can be detected by a host based intrusion detection system and vice versa In each level the attacks can be detected by intrusion detection technique namely misuse detection or anomaly detection Misuse detection can detect only known attacks with high detection accuracy whereas anomaly detection can detect both known and unknown attacks with high false positive rate To resolve the shortcomings of these individual intrusion detection systems this research work proposes a novel data mining based hybrid intrusion detection system In this research work an intelligent hybrid architecture is proposed to integrate detection techniques as well as levels of intrusion detection system For this purpose data mining approaches such as classification and clustering algorithms have been proposed and implemented for feature selection misuse detection and anomaly detection
Pagination: xix, 169p.
Appears in Departments:Faculty of Information and Communication Engineering

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01_title.pdfAttached File127.81 kBAdobe PDFView/Open
02_certificates.pdf2.05 MBAdobe PDFView/Open
03_abstract.pdf9.2 kBAdobe PDFView/Open
04_acknowledgement.pdf6.47 kBAdobe PDFView/Open
05_contents.pdf23.21 kBAdobe PDFView/Open
06_chapter1.pdf59.95 kBAdobe PDFView/Open
07_chapter2.pdf72.14 kBAdobe PDFView/Open
08_chapter3.pdf24.19 kBAdobe PDFView/Open
09_chapter4.pdf983.1 kBAdobe PDFView/Open
10_chapter5.pdf1.88 MBAdobe PDFView/Open
11_chapter6.pdf614.52 kBAdobe PDFView/Open
12_chapter7.pdf1.58 MBAdobe PDFView/Open
13_chapter8.pdf1.59 MBAdobe PDFView/Open
14_chapter9.pdf12.59 kBAdobe PDFView/Open
15_references.pdf51.28 kBAdobe PDFView/Open
16_publications.pdf5.92 kBAdobe PDFView/Open
17_vitae.pdf5.32 kBAdobe PDFView/Open

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