Data Randomization and Cluster-Based Partitioning for Botnet Intrusion Detection

Al-Jarrah, Omar Y.; Alhussein, Omar; Yoo, Paul D.; Muhaidat, Sami; Taha, Kamal; Kim, Kwangjo

doi:10.1109/TCYB.2015.2490802

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Data Randomization and Cluster-Based Partitioning for Botnet Intrusion Detection

Author(s): Omar Y. Al-Jarrah , Omar Alhussein , Paul D. Yoo , Sami Muhaidat , Kamal Taha , Kwangjo Kim

Publication date (Print): August 2016

Journal: IEEE Transactions on Cybernetics

Publisher: Institute of Electrical and Electronics Engineers (IEEE)

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An Intrusion-Detection Model

D.E. Denning (1987)

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Network Anomaly Detection: Methods, Systems and Tools

D Bhattacharyya, Monowar H. Bhuyan, J. Kalita (2015)

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A review of feature selection methods on synthetic data

Noelia Sánchez-Maroño, Amparo Alonso-Betanzos, Verónica Bolón-Canedo (2013)

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Journal

Title: IEEE Transactions on Cybernetics

Abbreviated Title: IEEE Trans. Cybern.

Publisher: Institute of Electrical and Electronics Engineers (IEEE)

ISSN (Print): 2168-2267

ISSN (Electronic): 2168-2275

Publication date Created: August 2016

Publication date (Print): August 2016

Volume: 46

Issue: 8

Pages: 1796-1806

Article

DOI: 10.1109/TCYB.2015.2490802

PubMed ID: 26540724

SO-VID: 4fea79c3-1f38-4442-8e1d-9b8862866a8e

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Data Randomization and Cluster-Based Partitioning for Botnet Intrusion Detection

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Recursive Rule based Visual Categorization

Most cited references 39

An Intrusion-Detection Model

Network Anomaly Detection: Methods, Systems and Tools

A review of feature selection methods on synthetic data

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