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Sequential detection with applicatio...

Vedantam, Satish.

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Sequential detection with applications to detection of network intrusions.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Sequential detection with applications to detection of network intrusions./
Author:	Vedantam, Satish.
Description:	59 p.
Notes:	Source: Masters Abstracts International, Volume: 42-04, page: 1269.
Contained By:	Masters Abstracts International42-04.
Subject:	Mathematics. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=1417945

Sequential detection with applications to detection of network intrusions.
Vedantam, Satish.

Sequential detection with applications to detection of network intrusions. - 59 p.

Source: Masters Abstracts International, Volume: 42-04, page: 1269.

Thesis (M.S.)--University of Southern California, 2003.

Rapid response, minimal false alarm rate, and the capability to detect a wide spectrum of attacks are the crucial features of intrusion detection systems. Once the set of observables is decided upon, sequential change-point detection algorithms can be used to minimize the detection delay for a given maximum false alarm rate. In this thesis, based on the advanced change-point detection methods, we propose an efficient anomaly detection system that detects denial-of-service attacks with minimal detection delay for a given false alarm rate.Subjects--Topical Terms:

515831
Mathematics.

Sequential detection with applications to detection of network intrusions.
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035 $a (UnM)AAI1417945
035 $a AAI1417945
040 $a UnM $c UnM
100 1 $a Vedantam, Satish. $3 1020964
245 1 0 $a Sequential detection with applications to detection of network intrusions.
300 $a 59 p.
500 $a Source: Masters Abstracts International, Volume: 42-04, page: 1269.
500 $a Adviser: Boris Rozovskii.
502 $a Thesis (M.S.)--University of Southern California, 2003.
520 $a Rapid response, minimal false alarm rate, and the capability to detect a wide spectrum of attacks are the crucial features of intrusion detection systems. Once the set of observables is decided upon, sequential change-point detection algorithms can be used to minimize the detection delay for a given maximum false alarm rate. In this thesis, based on the advanced change-point detection methods, we propose an efficient anomaly detection system that detects denial-of-service attacks with minimal detection delay for a given false alarm rate.
520 $a The sequential detection algorithm is nonparametric and utilizes thresholding of a test statistic to achieve a fixed rate of false positives. The proposed constant false alarm rate detector is self-learning and adapts to various network loads and usage patterns. The results of the theoretical and experimental studies are also presented.
590 $a School code: 0208.
650 4 $a Mathematics. $3 515831
650 4 $a Computer Science. $3 626642
690 $a 0405
690 $a 0984
710 2 0 $a University of Southern California. $3 700129
773 0 $t Masters Abstracts International $g 42-04.
790 1 0 $a Rozovskii, Boris, $e advisor
790 $a 0208
791 $a M.S.
792 $a 2003
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=1417945