HomeHome

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(s):
Computer Science
Persistent URL:
Notes:
Applications of data mining in computer security (Boston: Kluwer, 2002), pp. 77-101.
Subject(s):
Computer science
Item views
444
Metadata:
text | xml
Suggested Citation:
Eleazar Eskin, Andrew Arnold, Michael Prerau, Leonid Portnoy, Salvatore Stolfo, , A Geometric Framework for Unsupervised Anomaly Detection: Detecting Intrusions in Unlabeled Data, Columbia University Academic Commons, .

Columbia University Libraries | Policies | FAQ