International Journal of Science and Research (IJSR)

International Journal of Science and Research (IJSR)
Call for Papers | Fully Refereed | Open Access | Double Blind Peer Reviewed

ISSN: 2319-7064


Downloads: 133

Research Paper | Computer Science & Engineering | India | Volume 3 Issue 12, December 2014


Comparative Study of DDoS Attack Detection Technique in Cloud Computing Environment

Ajay R. Sirsat | Puja Padiya


Abstract: Cloud computing provides business new working paradigm with the benefit of cost reduce and resource sharing. Tasks from different users may be performed on the same machine. Therefore, one primary security concern is whether user data is secure in cloud. On the other hand, hacker may facilitate cloud computing to launch larger range of attack, such as a request of port scan in cloud with multiple virtual machines executing such malicious action. In addition, hacker may perform a sequence of attacks in order to compromise his target system in cloud, for example, evading an easy-to-exploit machine in a cloud and then using the previous compromised to attack the target. Such attack plan may be stealthy or inside the computing environment, so intrusion detection system or firewall has difficulty to identify it. There are various type of attack such as DDoS, HX-DoS, EDoS. Detecting of all attacks some techniques are available they are Back Propagation, Cloud Filter, Learning System ENDER, Packet Marking Approach. In this paper we have studied all techniques and find a best one on his parameter.


Keywords: Denial of Service attacks, Detection Technique, Back Propogation, Cloud Filter, Learning System ENDER, Packet marking Approach, Security


Edition: Volume 3 Issue 12, December 2014,


Pages: 1911 - 1915


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How to Cite this Article?

Ajay R. Sirsat, Puja Padiya, "Comparative Study of DDoS Attack Detection Technique in Cloud Computing Environment", International Journal of Science and Research (IJSR), Volume 3 Issue 12, December 2014, pp. 1911-1915, https://www.ijsr.net/get_abstract.php?paper_id=SUB14872

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