Pattern Analytical Module for EDOS Attacker Recognition
Preeti Daffu, Amanpreet Kaur · IOSR Journal of Computer Engineering · 2016
Cloud computing has provided a platform to its users where they are charged on the basis of usage of the cloud resources; this is known as "pay-as-you-use".Today, Cloud computing is the most hyped technology arenas and it has became one of the rapidly rising sections of IT.It has permitted us to measure our servers in better and availability to provide the services to greater number of the end users. .In cloud environment it is very difficult to detect and filter the attack packets because everything is virtualized there.Issues of protecting the cloud from the attackers and hackers cannot be underestimated.EDOS attacks are the cloud specific attacks and such attack causes the financial loss to the end users.The cloud service model automatically balances the resources according to their request of the consumers.The technique used in proposed model will detect and mitigate the EDoS attack through few strategic attacker/s, group of the attackers or zombie machine network (BOTNET), it indirectly or directly decreased profits and reduce the cost for the cloud operators.In this paper, an approach have been proposed, named Pattern Attack Recognition, to detect and mitigate the Economic Denial of Sustainability (EDoS) attack in cloud computing.The model is designed to assess its response time and the outcomes show that it is a capable solution to mitigate the EDOS.