K-Means+ID3: A Novel Method for Supervised Anomaly Detection by Cascading K-Means Clustering and ID3 Decision Tree Learning Methods

Balagani, Kiran S; Gaddam, Shekhar R.; Phoha, Vir V

doi:10.1109/TKDE.2007.44

Record: found
Abstract: not found
Article: not found

K-Means+ID3: A Novel Method for Supervised Anomaly Detection by Cascading K-Means Clustering and ID3 Decision Tree Learning Methods

Author(s): Shekhar R. Gaddam , Vir V. Phoha , Kiran S. Balagani

Publication date (Print): March 2007

Journal: IEEE Transactions on Knowledge and Data Engineering

Publisher: Institute of Electrical and Electronics Engineers (IEEE)

Read this article at

ScienceOpenPublisher

Bookmark

There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

Related collections

Most cited references 20

Record: found
Abstract: not found
Article: not found

On combining classifiers

J. Kittler, M. Hatef, R.P.W. Duin … (1998)

0 comments Cited 490 times – based on 0 reviews      Review now

Bookmark

Record: found
Abstract: not found
Conference Proceedings: not found

A Comparative Study of Anomaly Detection Schemes in Network Intrusion Detection

Aleksandar Lazarevic, Levent Ertöz, Vipin Kumar … (2003)

0 comments Cited 50 times – based on 0 reviews

Bookmark

Record: found
Abstract: not found
Article: not found

Anomaly detection in IP networks

M. Thottan, Chuanyi Ji (2003)

0 comments Cited 50 times – based on 0 reviews      Review now

Bookmark

All references

Author and article information

Journal

Title: IEEE Transactions on Knowledge and Data Engineering

Abbreviated Title: IEEE Trans. Knowl. Data Eng.

Publisher: Institute of Electrical and Electronics Engineers (IEEE)

ISSN (Print): 1041-4347

Publication date Created: March 2007

Publication date (Print): March 2007

Volume: 19

Issue: 3

Pages: 345-354

Article

DOI: 10.1109/TKDE.2007.44

SO-VID: e3af1182-e8a0-4f15-a5ee-0d51084b3dec

History

Data availability:

K-Means+ID3: A Novel Method for Supervised Anomaly Detection by Cascading K-Means Clustering and ID3 Decision Tree Learning Methods

Read this article at

Related collections

Cascading Disasters

Most cited references 20

On combining classifiers

A Comparative Study of Anomaly Detection Schemes in Network Intrusion Detection

Anomaly detection in IP networks

Author and article information

Journal

Article

History

Comments

Comment on this article

Similar content 1,329

Cited by 21

Most referenced authors 166