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Title: A hybrid automatic intrusion detection system using machine learning technique to detect anomalous traffic for network security
Researcher: Dhanabal L
Guide(s): Hantharajah S P
Keywords: Arts and Humanities,Arts and Recreation,Architecture
University: Anna University
Completed Date: 2018
Abstract: Secured provision of computer network in the fields of electronic newlinecommerce, government other critical service organizations are becoming newlinechallenging with every passing day. Security threats in the Internet are posing newlinea huge challenge in the recent day, world-wide. Hence, in the present era of newlineinformation technology computer / cyber security has become a high-priority newlineglobal issue that needs to be addressed. Networked computing which is an newlineinevitable part information system has made it vulnerable to security threats. newlineIntrusions compromise Confidentiality, Integrity and Availability (CIA) of newlinecomputing resources and data available in a networked environment, resulting newlinein heavy loss both in terms of money and trust to commercial or government newlineorganizations Thus it has become both mandatory and urgent for all the computer newlinenetworks to be guarded with multilevel security systems. Multilevel security newlinecan be provided with sophisticated software and equipments such as firewall, newlineVirtual Private Network (VPN), web and email filtering, antivirus protection, newlineevent management and vulnerability scanning tools. Most of the prevention newlinemethods just discussed is inadequate; there is a demanding need for a security newlinecompromise monitoring system. One such security breach monitoring system newlineis the Intrusion Detection System (IDS). Early and effective detection of newlineintrusions continues to be a big challenge to the automated IDS. Accurate newlinedetection of intrusion with less false positives (alarm without a security newlineincident) has been elusive as always.. newline newline
Pagination: xxvi, 160p.
Appears in Departments:Faculty of Science and Humanities

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01_title.pdfAttached File24.96 kBAdobe PDFView/Open
02_certificates.pdf500.82 kBAdobe PDFView/Open
03_abstract.pdf9.51 kBAdobe PDFView/Open
04_acknowledgment.pdf4.94 kBAdobe PDFView/Open
05_contents.pdf406.82 kBAdobe PDFView/Open
06_chapter1.pdf308.84 kBAdobe PDFView/Open
07_chapter2.pdf221.04 kBAdobe PDFView/Open
08_chapter3.pdf193.5 kBAdobe PDFView/Open
09_chapter4.pdf772.47 kBAdobe PDFView/Open
10_chapter5.pdf635 kBAdobe PDFView/Open
11_chapter6.pdf491.71 kBAdobe PDFView/Open
12_chapter7.pdf100.33 kBAdobe PDFView/Open
13_conclusion.pdf107.53 kBAdobe PDFView/Open
14_references.pdf129.27 kBAdobe PDFView/Open
15_publications.pdf88.36 kBAdobe PDFView/Open

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