Distributed Denial of Service (DDoS) is the significant hardest threats in internet security. These attacks are typically explicit attempts to disrupt legitimate user access services. So it is a necessary obsession to protect the resource and trace from the DDoS attack. But it was very tricky to discriminate normal traffic due to its identities and origins hiding. Developing a broad resistance mechanism against identified and anticipated DDoS flooding attacks is a desired goal of the intrusion detection and prevention. This paper discussed some of the mostly used predicting trace back techniques to solve the issues raised by DDoS attacks. In this paper it also asses the different trace back techniques which are provide effective, efficient detection of such attacks.
1. R. Alshammari, and A. N. Zincir-Heywood, “Can Encrypted Traffic be identified without Port Numbers, IP Addresses and Payload Inspection?” Journal of Computer Networks, Elsevier, 2011. 2. Amruta Kokate and Prof.Pramod Patil, A Survey on Different IP Traceback Techniques for finding The Location of Spoofers”, International Journal Of Engineering And Computer Science ISSN: 2319-7242, Volume 4 Issue 12 Dec 2015, Page No. 15132-15135. 3. A-Duwairi and M. Govindarasu, “Novel Hybrid Schemes Employing Packet Marking and Logging for IP Traceback,” IEEE Trans. Parallel and Distributed Systems, vol. 17, no. 5, May 2006, pp. 403- 418. 4. G.Florance, “Survey of IP Traceback Methods in Distributed Denial of Service (DDoS) Attacks”, International Journal of Innovative Research in Science, Engineering and Technology, Vol. 4, Issue 7, July 2015. 5. Hakem Beitollahi, Geert Deconinck: Analyzing Well-known Countermeasures against Distributed Denial of Service Attacks, Computer Comm., Vol. 35, 2012, pp. 1312-1332. 6. A.John and T Sivakumar, “DDoS: Survey of Traceback Methods”, International Journal of Recent Trends in Engineering, Vol. 1, No. 2, May 2009, pp. 241-245. 7. H. I. Liu, and K. C. Chang, Defending systems Against Tilt DDoS attacks, Telecommunication Systems, Services, and Applications (TSSA), October 20-21, 2011, pp. 22-27. 8. X. Liu, X. Yang, and Y. Lu, “To filter or to authorize: network-layer DoS defense against multimillion-node botnets”, in Proc. of the ACM SIGCOMM conference on Data communication (SIGCOMM ’08), NY, USA, 2008, pp. 195-206. 9. R. M. Mutebi, and I. A. Rai, “An Integrated Victim-based Approach against IP Packet Flooding Denial of Service”, International Journal of Computing and ICT Research, Special Issue Vol. 4, No. 1, October 2010, pp. 70-80. 10. M. Naveed, S. Un Nihar, and M. Inayatullah Babar, “Network Intrusion Prevention by Configuring ACLs on the Routers, based on Snort IDS Alerts,” Proc. of 6th Intl’ Conference. 11. Saman Taghavi Zargar and James Joshi et al., “A Survey of Defense Mechanisms Against Distributed Denial of Service (DDoS) Flooding Attacks”, IEEE COMMUNICATIONS SURVEYS & TUTORIALS, published online Feb. 2013, pp. 1-24. 12. Thomas Dubendorfer, Matthias Bossardt, Bernhard Plattner, “Adaptive Distributed Traffic Control Service for DDoS Attack Mitigation”, Proceedings of the 19th IEEE International Parallel and Distributed Processing Symposium (IPDPS’05) – Workshop 17 – Volume 18, 2005. 13. D. K. Yau, J. C. Lui, and F. Liang, “Defending against Distributed Denial-of-Service Attacks with Max-min Fair Server-centric Router Throttles”, In Proc. of IEEE IWQoS, May 2002.
Network Security, DDoS attacks, Trace back methods, Botnets, Flooding attack.