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A Geometric Framework for Unsupervised Anomaly Detection: Detecting Intrusions in Unlabeled Data

Eleazar Eskin; Andrew Arnold; Michael Prerau; Leonid Portnoy; Salvatore Stolfo

Title:
A Geometric Framework for Unsupervised Anomaly Detection: Detecting Intrusions in Unlabeled Data
Author(s):
Eskin, Eleazar
Arnold, Andrew
Prerau, Michael
Portnoy, Leonid
Stolfo, Salvatore
Date:
Type:
Articles
Department:
Computer Science
Permanent URL:
Notes:
Applications of data mining in computer security (Boston: Kluwer, 2002), pp. 77-101.
Subject(s):
Computer science
Item views:
307
Metadata:
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Suggested Citation:
Eleazar Eskin, Andrew Arnold, Michael Prerau, Leonid Portnoy, Salvatore Stolfo, 2002, A Geometric Framework for Unsupervised Anomaly Detection: Detecting Intrusions in Unlabeled Data, Columbia University Academic Commons, http://hdl.handle.net/10022/AC:P:8719.

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