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Correlating intrusion detection even...

Johnson, Michael C.

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Correlating intrusion detection events: A data mining and profiling approach.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Correlating intrusion detection events: A data mining and profiling approach./
Author:	Johnson, Michael C.
Description:	195 p.
Notes:	Source: Dissertation Abstracts International, Volume: 66-05, Section: B, page: 2676.
Contained By:	Dissertation Abstracts International66-05B.
Subject:	Computer Science. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3175613
ISBN:	0542142414

Correlating intrusion detection events: A data mining and profiling approach.
Johnson, Michael C.

Correlating intrusion detection events: A data mining and profiling approach. - 195 p.

Source: Dissertation Abstracts International, Volume: 66-05, Section: B, page: 2676.

Thesis (Ph.D.)--George Mason University, 2005.

In an increasingly connected and networked world, the need to secure computers, networks, and the information that they contain, maintain and transport is growing rapidly. Information security professionals attempt to meet this need by implementing protective systems to keep unauthorized personnel and organizations out, monitoring systems to detect unauthorized activity that gets by the protective systems, and reactive systems to help recover gracefully as well as to continuously improve all the systems in the Protect - Detect - React cycle. This dissertation focuses on the detection phase and discusses a novel approach to intrusion detection involving correlation of low level events from multiple sources into higher-level events and scenarios followed by analysis of the scenarios using profiling and data mining approaches. A prototype using events from a network sensor and events from a host sensor was implemented to test the feasibility of the proposed approach.

ISBN: 0542142414Subjects--Topical Terms:

626642
Computer Science.

Correlating intrusion detection events: A data mining and profiling approach.
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100 1 $a Johnson, Michael C. $3 1903627
245 1 0 $a Correlating intrusion detection events: A data mining and profiling approach.
300 $a 195 p.
500 $a Source: Dissertation Abstracts International, Volume: 66-05, Section: B, page: 2676.
500 $a Director: Daniel C. Barbara.
502 $a Thesis (Ph.D.)--George Mason University, 2005.
520 $a In an increasingly connected and networked world, the need to secure computers, networks, and the information that they contain, maintain and transport is growing rapidly. Information security professionals attempt to meet this need by implementing protective systems to keep unauthorized personnel and organizations out, monitoring systems to detect unauthorized activity that gets by the protective systems, and reactive systems to help recover gracefully as well as to continuously improve all the systems in the Protect - Detect - React cycle. This dissertation focuses on the detection phase and discusses a novel approach to intrusion detection involving correlation of low level events from multiple sources into higher-level events and scenarios followed by analysis of the scenarios using profiling and data mining approaches. A prototype using events from a network sensor and events from a host sensor was implemented to test the feasibility of the proposed approach.
590 $a School code: 0883.
650 4 $a Computer Science. $3 626642
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710 2 0 $a George Mason University. $3 1019450
773 0 $t Dissertation Abstracts International $g 66-05B.
790 1 0 $a Barbara, Daniel C., $e advisor
790 $a 0883
791 $a Ph.D.
792 $a 2005
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3175613