A comprehensive taxonomy of DDoS attacks and defense mechanism applying in a smart classification

WSEAS Transactions on Computers

Volumn 7, Issue 4, 2008, Pages 281-290

  Asosheh, Abbass ^a   Ramezani, Naghmeh ^a  

^a TARBIAT MODARES UNIVERSITY   (Iran)

Author keywords

DDoS attack; Defense mechanism; Detection; Smart classification; Taxonomy

Indexed keywords

CHLORINE COMPOUNDS; CLASSIFICATION (OF INFORMATION); FEATURE EXTRACTION; HIERARCHICAL SYSTEMS; TAXONOMIES;

DDOS ATTACK; DDOS ATTACKS; DEFENSE MECHANISM; DEFENSE MECHANISMS; DETECTION; DISTRIBUTED DENIAL-OF-SERVICE ATTACKS; K-NEAREST NEIGHBORS; MULTIPLE MACHINES; POTENTIAL ATTACK; SMART CLASSIFICATION; TAXONOMY;

MECHANISMS;

EID: 48749093494     PISSN: 11092750     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

References (36)

1. S. Specht, M. and R. B. Lee., Distributed Denial of Service: Taxonomies of Attacks; Tools and Countermeasures. Proceedings of the 17th International Conference on Parallel and Distributed Computing Systems, 2004, pp.543-550.
2. J. Mirkovic, J. Martin, et al., A Taxonomy of DDoS Attacks and DDoS Defence Mechanisms, Computer Science Department, University of California, 2002.
3. U. Tariq, M. Hang, and et al., A Comprehensive Categorization of DDoS Attack and DDoS Defense Techniques., ADMA LNAI 4093, 2006 pp.1025-1036.
4. L. Chen, T. Longstaff, K. Carley, A Taxonomy of DDoS Attack and DDoS Defense Mechanisms, Computers and Security, 2004.
5. F. Kargl, J. Maier and M. Weber, Protecting web servers from distributed denial of service attacks, In Proceedings of 10th International World Wide Web Conference, 2001.
6. J. Kang, Y. Zhang, and et al., A Formalized Taxonomy of DDoS Attacks based on Similarity, ISI 3975, 2006, pp. 717-719.
7. A. Hussain, J. Heidemann, C. Papadopoulos, A Framework for Classifying Denial of Service Attacks, ACM, 2003, pp.99-110
8. B. Joao, D. Cabrera, and et al. Proactive Detection of Distributed Denial of Service Attacks Using MIB Traffic Variables - A Feasibility Study, Integrated Network Management Proceedings, 2001, pp. 609-622.
9. A. Juels and J. Brainard, Client puzzles: A cryptographic countermeasure against connection depletion attacks, In Proceedings of the 1999 Networks and distributed system security symposium (NDSS'99), 1999.
10. F. Lau, S. H. Rubin, and et al., Distributed denial of service attacks, In Proceedings of 2000 IEEE International Conference on Systems, Man, and Cybernetics, 2000.
11. A. C. Snoeren, C. Partridge, and et al., Hash-Based IP Traceback, In Proceedings of ACM SIGCOMM 2001 Conference on Applications, Technologies, Architectures, and Protocols for Computer Communication, August 2001.
12. D. X. Song and A. Perrig, Advanced and authenticated marking schemes for IP Traceback, IEEE Infocom, 2001.
13. D. Dean, M. Franklin and A. Stubblefield, An algebraic approach to IP Traceback, In Proceedings of the 2001 Network and Distributed System Security Symposium, February 2001.
14. S. M. Bellovin, ICMP traceback messages, Internet draft, http:// search.ietf.org/internetrafts/draft-ietf-itrace-01.txt, Oct. 2001.
15. S. Savage, D. Wetherall, A. Karlin, and T. Anderson, Practical network support for IP Traceback, In Proceedings of 2000 ACM SIGCOMM Conference, Aug. 2000.
16. T. M. Gil and M. Boleto, MULTOPS: a datastructure for bandwidth attack detection, In Proceedings of 10th Usenix Security Symposium, August 2001.
17. D. G. Andersen, H. Balakrishnan, M. F. Kaashoek, R. Morris, Resilient Overlay Networks,In Proceedings of 18th ACM SOSP, October 2001.
18. Distributed Denial of Service attacks and theirdefenses:http:// www.lancs.ac.uk/postgrad/pissias/netsec/DDoS/
19. D. Moore, The spread of the code red worm (crv2),http:// www.caida.org/analysis/security/codered/coderedv2_analysis.xml.
20. CERT Coordination Center, erkms and li0n worms, http:// www.cert.org/incident∉tes/IN-2001-03.html
21. CERT Coordination Center, Ramen worm, http://www.cert.org/ incident_notes/IN-2001-01.html
22. N. Weaver, Warhol Worm; http://www.cs.berkeley.edu/~nweaver/ warhol.html
23. Tripwire, Tripwire for servers, http://www.tripwire.com/products/ servers/
24. McAfee, Personal Firewall, http://www.mcafee.com/myapps/firewall/ ov_firewall.asp
25. Cisco, Strategies to protect against distributed denial of service attacks, http://www.cisco.com/warp/public/707/newsflash.html
26. Mananet, Reverse Firewall, http://www.cs3-inc.com/ps_rfw.html
27. Information Sciences Institute, Dynabone, http://www.isi.edu/ dynabone/.
28. G. Zhang, M. Parashar, Cooperative Mechanism against DDOS Attacks, the Applied Software Systems Laboratory, Department of Electrical and Computer Engineering, Rutgers University, 2005.
29. K. Mihui, K. Chae, Detection and Identification Mechanism against Spoofed, Springer-Verlag Berlin Heidelberg, 2004, pp. 673-682.
30. A. Hussain, J. Heidemann, A Framework for Classifying Denial of Service Attacks, SIGCOMM, ACM, 2003, pp.99-110.
31. V. A. Kumar, Sophistication in distributed denial-of-service attacks on the Internet, CURRENT SCIENCE, VOL. 87, NO. 7, 10 October, 2004, pp.885-888.
32. R. Jalili, F. Imani-Mehr, Detection of Distributed Denial of Service Attacks Using Statistical Pre-Prossesor and Unsupervised Neural Network", ISPEC, Springer-Verlag Berlin Heidelberg, 2005, pp. 192-203
33. M. Li, J. Liu, and D. Long, Probability Principle of Reliable Approach to detect signs of DDOS Flood Attacks, PDCAT, Springer-Verlag Berlin Heidelberg, 2004, pp.596-599.
34. J. Han, M. Kamber, Data Mining Concepts and Techniques, Elsevier Inc., 2006.
35. P. Tan, N., M. Steinbach, Introduction to Data Mining, Pearson Education, Inc., 2006.
36. G. Dimitris, T. Ioannis, and D. Evangelos, Feature Selection for Robust Detection of Distributed Denial of service Attacks using Genetic Algorithm, SETN, Springer-Valag Berlin Heidelberg, 2004, pp.276-281.