Isolate unauthorized authentication and block data transaction using agile IP traceback

Authors

  • R. Lalith Kumar  PG Scholar, Department of Software Development & Management, VIT University, Vellore, TamilNadu, India

Keywords:

IP Traceback, Spoofing, Agile IP Traceback, Data transactions.

Abstract

IP Traceback is a mechanism which is used to identify the origin of the packet on the internet. Since there are no authentications done for any IP address, there are many chances that IP address can be faked and used to perform harmful attacks to any host machines. There are many traceback methods implemented of which few are just used for investigation purpose and some for detection and prevention of these harmful attacks. The attacks are broadly categorized as passive in which only data is watched and active attacks in which the data is modified with purpose to corrupt or destroy the data. Passive attacks are very tough to find but it can be prevented. Active attacks are very tough to avoid but it’s easy to detect. There are two types of service attacks which are Denial of Service (DoS) and Distributed Denial of Service (DDoS) attacks. In DoS attacked only one system and one network connection is used to send packets to the system. These packets can be either TCP or UDP. By this way, it is possible to make the system inaccessible and hence all the applications available under the system is blocked. In DDoS attack it uses more number of system and many networks and hence blocks the server connections in a fast manner. Hence there is a need for a very fast processing algorithm to identify and block data transactions. This fast processing can be accomplished by Agile IP Traceback (AIT) which gives much better performance when compared to other algorithms.

References

  1. Long Chengy, Dinil Mon Divakarany, Aloysius Wooi Kiak Angz, Wee Yong Limy, Vrizlynn L. L. Thing, “FACT: A Framework for Authentication in Cloud-based IP Traceback”, IEEE 2016.
  2. S. M. Bellovin, “Security problems in the TCP/IP protocol suite,” ACM SIGCOMM Comput. Commun. Rev., vol. 19, no. 2, pp. 32?48, Apr. 1989.
  3. Stephen M. Specht, ICANN Security and Stability Advisory Committee, “Distributed denial of service (DDOS) attacks,” SSAC, Tech. Rep. SSAC Advisory SAC008, Mar. 2006.
  4. Alex C. Snoeren, “Hash-Based IP Traceback”, BBN Technologies, 2007.
  5. D. Moore, C. Shannon, D. J. Brown, G. M. Voelker, and S. Savage, “Inferring internet denial-of-service activity,” ACM Trans. Comput. Syst., vol. 24, no. 2, pp. 115?139, May 2006.
  6. D. X. Song and A. Perrig, “Advanced and authenticated marking schemes for IP traceback,” in Proc. IEEE 20th Annu. Joint Conf. IEEE Comput. Commun. Soc. (INFOCOM), vol. 2. Apr. 2001, pp. 878?886.
  7. Virandra Patil, Pritish Deshpande, Mahesh Talekar, Swapnil Tapkir, Dhanajay khade, Prof.Nitin Hambir, “Spoofer location detection using passive ip traceback”, MJRET 2016.
  8. Shweta vincent, j. Immanuel john raja, “A Survey of IP Traceback Mechanisms to overcome Denial-of-Service Attacks”.
  9. Vijayalakshmi Murugesan, Mercy Shalinie, Nithya Neethimani, “A Brief Survey of IP Traceback Methodologies”, 2014.
  10. Wikipedia, “IP_traceback” https://en.wikipedia.org/wiki/IP_traceback.

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Published

2017-09-26

Issue

Section

Research Articles

How to Cite

[1]
R. Lalith Kumar, " Isolate unauthorized authentication and block data transaction using agile IP traceback, International Journal of Scientific Research in Science and Technology(IJSRST), Online ISSN : 2395-602X, Print ISSN : 2395-6011, Volume 3, Issue 7, pp.269-274, September-October-2017.