Abstract

In recent days, technology has reached new heights. In the same way malicious programs has also touched the level of sky and the above. Secret information are nowadays stored and managed through high secure sites. However, critical problems like hacking happens due to DDOS(Distributed Denial of Service Attacks) resulting in crashing of website for certain period of time and hacking of sensitive information thereby affecting the services issued. Such problems can be sorted by the scope of MASTDP (Multiple Authenticated Scoring Technique for denial and prevention of DDOS attacks). In this technique, internet protocol address and physical address of the users are entered and stored in the history and scores will be allotted for each and every entry. Similarly, horizontal and vertical communication scoring are given for every entry based on the vulnerability of the user (using scores). At-last, by association rule, users with peak scores are denied entry from the network or site.

References

• A. Networks, Arbor, Lexington, MA, “Measurements and mitigation of peer-to-peer-based botnets: A case study on storm worm,” “Worldwide ISP security report,” Tech. Rep., 2010.
• T. Holz, M. Steiner, F. Dahl, E. Biersack, and F. Freiling, in Proc. USENIX LEET, 2008, Article no. 9.
• J. Françcois, A. El Atawy, E. Al Shaer, and R. Boutaba, “A collaborative approach for proactive detection of distributed denial of service attacks,” in Proc. IEEE MonAM, Toulouse, France, 2007, vol. 11.
• A. Feldmann, O. Maennel, Z. M. Mao, A. Berger, and B. Maggs, “Locating Internet routing instabilities,” Comput. Commun. Rev., vol. 34, no. 4, pp. 205–218, 2004.
• A. Basu and J. Riecke, “Stability issues in OSPF routing,” in Proc. ACM SIGCOMM , 2001, pp. 225–236.
• T. Peng, C. Leckie, and K. Ramamohanarao, “Protection from distributed denial of service attacks using history-based IP filtering,” in Proc. IEEE ICC, May 2003, vol. 1, pp. 482–486.
• R. Lippmann, J. W. Haines, D. J. Fried, J. Korba, and K. Das, “The 1999 DARPA off-line intrusion detection evaluation,” Comput. Netw., vol. 34, no. 4, pp. 579–595, 2000.
• J. A. Barnett, “Computational methods for a mathematical theory of evidence,” in Proc. 7th Int. Joint Conf. Artif. Intell., 1981, pp. 868–875.
• R. N. Smith and S. Bhattacharya, “A protocol and simulation for distributed communicating firewalls,” in Proc. COMPSAC, 1999, pp. 74–79.
• Y. You, M. Zulkernine, and A. Haque, “A distributed defense framework for flooding-based DDoS attacks,” in Proc. 3rd ARES, Mar. 2008, pp. 245–252.
• K. Deeter, K. Singh, S. Wilson, L. Filipozzi, and S. T. Vuong, “APHIDS: A mobile agent-based programmable hybrid intrusion detection system,” in Proc. MATA, 2004, pp. 244–253.
• Y. Kim, W. C. Lau, M. C. Chuah, and H. J. Chao, “PacketScore: A statistics-based packet filtering scheme against distributed denial-ofservice attacks,” IEEE Trans. Depend. Secure Comput., vol. 3, no. 2, pp. 141–155, Apr.–Jun. 2006.
• G. Badishi, A. Herzberg, and I. Keidar, “Keeping denial-of-service attackers in the dark,” IEEE Trans. Depend. Secure Comput., vol. 4, no. 3, pp. 191–204, Jul.–Sep. 2007.
• D. Nashat, X. Jiang, and S. Horiguchi, “Router based detection for lowrate agents of ddos attack,” in Proc. HSPR, May 2008, pp. 177–182.
• H. Wang, D. Zhang, and K. Shin, “Change-point monitoring for the detection of DoS attacks,” IEEE Trans. Depend. Secure Comput., vol. 1, no. 4, pp. 193–208, Oct.–Dec. 2004.
• P. Verkaik, O. Spatscheck, J. Van der Merwe, and A. C. Snoeren, “Primed: Community-of-interest-based DDoS mitigation,” in Proc. ACM SIGCOMM LSAD, 2006, pp. 147–154.
• G. Koutepas, F. Stamatelopoulos, and B. Maglaris, “Distributed management architecture for cooperative detection and reaction to DDoS attacks,” J. Netw. Syst. Manage., vol. 12, pp. 73–94, Mar. 2004.
• A. El-Atawy, E. Al-Shaer, T. Tran, and R. Boutaba, “Adaptive early packet filtering for defending firewalls against DoS attacks ,” in Proc. IEEE INFOCOM, Apr. 2009, pp. 2437–2445.
• A. El-Atawy, T. Samak, E. Al-Shaer, and H. Li, “Using online traffic statistical matching for optimizing packet filtering performance,” in Proc. IEEE INFOCOM, May 2007, pp. 866–874.
• D. Das, U. Sharma, and D. K. Bhattacharyya, “Detection of HTTP flooding attacks in multiple scenarios,” in Proc. ACM Int. Conf. Commun., Comput. Security, 2011, pp. 517–522.
• A. Sardana, R. Joshi, and T. hoon Kim, “Deciding optimal entropic thresholds to calibrate the detection mechanism for variable rate DDoS attacks in ISP domain,” in Proc. ISA, Apr. 2008, pp. 270–275.
• V.Priyadharshini, Dr.K. Kuppusamy,” Prevention of DDOS Attacks using New Cracking algorithm” in International Journal of Engineering Research and Applications (IJERA) ISSN: 2248-9622 www.ijera.com Vol. 2, Issue 3, May-Jun 2012, pp.2263-2267.