Hybrid Approach for Detection of Anomaly Network Traffic using Data Mining Techniques-Reference-Cited by-同舟云学术

Hybrid Approach for Detection of Anomaly Network Traffic using Data Mining Techniques

Published:2012 Issue: Volume:6 Page:996-1003
ISSN:2212-0173
Container-title:Procedia Technology
language:en
Short-container-title:Procedia Technology

Author:

Agarwal Basant,Mittal Namita

Publisher

Elsevier BV

Subject

General Earth and Planetary Sciences,General Environmental Science

Reference18 articles.

1. Altyeb Altaher, Sureswaran Ramadass, Bhavani Thuraisingham, Mohammad Mehedy, 28-30 Oct. 2011, “On-Line anomaly Detection Based On Relative Entropy”, Broadband Network and Multimedia Technology (IC-BNMT), 2011 4th IEEE International Conference, pp 33-36.

2. C. Cortes and V. Vapnik. 1995, “Support-vector network. Machine Learning”, Kluwer Academic Publishers, Boston. pp: 273-297.

3. DARPA Intrusion Detection Evaluation Data Sets 1999, available at http://www.ll.mit.edu/IST/ideval/data/data\index.html.

4. Denning, D.E. 1987, “An Intrusion-Detection Model”, Software Engineering, IEEE Transactions., SE-13, Issue: 2 pp 222-232.

5. G. Nychis, V. Sekar, D.G. Anderson. 2008, “An Empirical Evaluation of Entropy-based Anomaly Detection” Proceedings of the 8th ACM SIGCOMM conference on Internet measurement, ACM Press,pp 151-156.

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