d8921bcf-f609-4f80-bf90-35be6de8088e20211127090217944naun:naunmdt@crossref.orgMDT DepositInternational Journal of Mathematics and Computers in Simulation1998-015910.46300/9102http://www.naun.org/cms.action?id=2826329202132920211510.46300/9102.2021.15https://www.naun.org/cms.action?id=23312An New Efficient Cluster Based Detection Mechanisms for Distributed Denial of Services (DDoS) AttacksK.SaravananFaculty of Computer Science and Engg., Erode Sengunthar Engineering College, Thudupathi, IndiaR.AsokanPrincipal, Kongunadu College of Engineering and Technology, Thottiam, IndiaCluster aggregation of statistical anomaly detection is a mechanism for defending against denial of service attack (dos) and distributed denial-of-service (DDoS) attacks. DDoS attacks are treated as a congestioncontrol problem; because most of the congestion is occurred in the malicious hosts not follow the normal endto- end congestion control. Upstream routers are also notified to drop such packets in order that the router’s resources are used to route legitimate traffic hence term cluster aggregation. If the victim suspects that the cluster aggregations are solved by most of the clients, it increases the complexity of the cluster aggregation. This aggregation solving technique allows the traversal of the attack traffic throughout the intermediate routers before reaching the destination. In this proposal, the aggregation solving mechanism is cluster aggregation to the core routers rather than having at the victim. The router based cluster aggregation mechanism checks the host system whether it is legitimate or not by providing a aggregation to be solved by the suspected host.112720211127202114715227https://www.naun.org/main/NAUN/mcs/2021/a542002-027(2021).pdf10.46300/9102.2021.15.27https://www.naun.org/main/NAUN/mcs/2021/a542002-027(2021).pdf10.1109/tnet.2004.842221David K. Y. Yau, Member, IEEE and John C. S. Lui, Feng Liang, and Yeung Yam, (2005) ‘Defending Against Distributed Denial-of-Service Attacks With Max-Min Fair Server-Centric Router Throttles’, IEEE/ACM TRANSACTIONS ON NETWORKING, VOL. 13, NO. 1, Pages 29-42. John Ioannidis and Steven M. Bellovin, ‘Implementing Pushback: Router-Based Defense Against DDoS Attacks’, AT&T Labs Research, ji@research.att.com, smb@research.att.com. 10.1145/1030083.1030118Michael K. Reiter and XiaoFeng Wang, (2004), ‘Mitigating Bandwidth-Exhaustion Attacks using Congestion Puzzles’, CCS’04, October 25-29, 2004, Washington, DC, USA., Copyright ACM 1-58113-961- 6/04/0010. 10.1145/347057.347560Stefan Savage, David Wetherall, Anna Karlin and Tom Anderson, (2000), ‘Practical Network Support for IP Traceback’, ACM SIGCOMM Computer Communication Review, Volume 30, Issue 4, Pages 295-306. 10.1145/1216370.1216373Tao Peng, Christopher Leckie, and Kotagiri Ramamohanarao, (2007), ‘Survey of Network-Based Defense Mechanisms Countering the DoS and DDoS Problems’, Department of Computer Science and Software Engineering, The University of Melbourne, Australia, ACM Comput. Surv., Volume 39, Issue 1, Article no.3. 10.1007/s10207-007-0042-xXiaoFeng Wang and Michel K. Reiter, (2008), ‘A multilayer frame work for puzzle-based denial-ofservice defense’, ACM, International Journal of Information Security, ISSN:1615-5262, Page 243-263. 10.1504/ijcis.2010.029577Saravanan Kumarasamy (2011), ‘An Effective Defence Mechanism For Distributed Denial-Of-Service (Ddos) Attacks Using Router-Based Techniques’, Int. J. Critical Infrastructures, Vol. 6, No. 1, 2010,Page No. 73-80 10.5121/ijcseit.2011.1504Saravanan kumarasamy, Dr.R.Asokan ,’ Distributed Denial Of Service (Ddos) Attacks Detection Mechanism’ International Journal of Computer Science, Engineering and Information Technology (IJCSEIT), Vol.1, No.5, December 2011,Page no:39- 49.