A multi-layered approach to botnet detection

Proceedings of the 2008 International Conference on Security and Management, SAM 2008

Volumn , Issue , 2008, Pages 301-308

  Erbacher, Robert F ^a   Cutler, Adele ^b   Banerjee, Pranab ^c   Marshall, Jim ^c  

^a Utah State University ^*  (United States)

^b UTAH STATE UNIVERSITY   (United States)

^c SDL   (United States)

Author keywords

Botnet Detection; Data Mining; Signature Based detection; Software Architecture

Indexed keywords

BOTNET DETECTION; BOTNETS; DATA MINING TECHNIQUES; MISUSE DETECTIONS; MULTI-LAYERED; MULTI-LAYERED APPROACHES; NEW CLASS; OPEN ARCHITECTURES; SIGNATURE-BASED DETECTION;

DATA MINING; INFORMATION MANAGEMENT;

SOFTWARE ARCHITECTURE;

EID: 62749197655     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (19)

1. Mitsuaki Akiyama, Takanori Kawamoto, Masayoshi Shimamura, Teruaki Yokoyama, Youki Kadobayashi, and Suguru Yamaguchi, "A proposal of metrics for botnet detection based on its cooperative behavior," Proceedings of the SAINT 2007 Internet Measurement Technology and its Applications to Building Next Generation Internet Workshop, January 2007.
2. James R. Binkley and Suresh Singh, "An Algorithm for Anomaly-based Botnet Detection," Computer Science, PSU, USENIX SRUTI: '06 2nd Workshop on Steps to Reducing Unwanted Traffic on the Internet, July 7 2006.
3. James R. Binkley, "Anomaly-based Botnet Server Detection," Computer Science, PSU, FLOCON CERT/SEI, Vancouver WA, October 2006.
4. L. Breiman, "Random forests," Machine Learning, 2001, 45(1), 5-32.
5. Robert J. Brown, "An Artificial Neural Network Experiment," Dr. Dobbs Journal, April 1987.
6. Evan Cooke, Farnam Jahanian, and Danny McPherson, "The Zombie Roundup: Understanding, Detecting, and Disrupting Botnets," Proceedings of the 2005 Usenix Workshop on Steps to Reducing Unwanted Traffic on the Internet (SRUTI '05), June 2005.
7. Corinna Cortes and V. Vapnik, "Support-Vector Networks," Machine Learning, 20, 1995.
8. D. Denning, "An Intrusion-Detection Model,". IEEE Transactions on Software Engineering, 13(2), Feb. 1987.
9. Jonathon W. Donaldson, "Anomaly-based Botnet Detection for High-Speed Networks," Thesis, Rochester Institute of Technology, Rochester, New York.
10. W. Frawley and G. Piatetsky-Shapiro and C. Matheus, "Knowledge Discovery in Databases: An Overview," AI Magazine, Fall 1992, pp. 213-228.
11. P. Helman and G. Liepins, "Statistical Foundations of Audit Trail Analysis for the Detection of Computer Misuse," IEEE Transactions on Software Engineering, 19(9), September, 1993.
12. Sandvine, "Dynamic Botnet Detection," Sandvine White Paper, June 2006.
13. Trend Micro, "Taxonomy of Botnet Threats," Trend Micro White Paper, November 2006.
14. Moheeb Abu Rajab, Jay Zarfoss, Fabian Monrose, Andreas Terzis. A Multifaceted Approach to Understanding the Botnet Phenomenon. In Proceedings of ACM SIGCOMM/USENIX Internet Measurement Conference (IMC), Oct., 2006. Rio de Janeiro, Brazil.
15. Open Source Security Information Management (OSSIM), http://www.ossim. net/
16. Prelude IDS, http://www.prelude-ids.org/
17. McAfee, http://www.mcafee.com/us/
18. Norton Antivirus, http://www.norton.com/
19. Know your Enemy: Tracking Botnets, http://www.honeynet.org/papers/bots/