Pattern Analytical Module for EDOS Attacker Recognition
Journal Title: IOSR Journals (IOSR Journal of Computer Engineering) - Year 2016, Vol 18, Issue 5
Abstract
Abstract: 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 modelautomatically 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 attackersor 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 detectand 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
Authors and Affiliations
Preeti Daffu , Amanpreet Kaur
Keywords
Related Articles
- EP ID EP90940
- DOI -
- Views 105
- Downloads 0
Securing Cloud Data Storage
Innovations are necessary to ride the inevitable tide of change. Most of enterprises are striving to reduce their computing cost through the means of virtualization. This demand of reducing the computing cost has...
A Survey on Different Levels of Risks during Different Phases in Data Warehouse
Abstract: The term Data Warehouse represents huge collection of historical data which are subject-oriented, non-volatile, integrated, and time-variant and such data is required for the business needs [1]. Data warehouses...
Big Data Mining using Map Reduce: A Survey Paper
Abstract: Big data is large volume, heterogeneous, distributed data. Big data applications where datacollection has grown continuously, it is expensive to manage, capture or extract and process data using existings...
Design of Smart Universal Remote using Mobile for Home Automation
Abstract: Controlling Home Appliances remotely is à main part of automation. There is a great deal of inconvenience in controlling each digital home appliance with its own separate remote. In this paper we present...
Collaborative data sharing in online social network resolving privacy risk and sharing loss
Abstract : Nowadays, Online Social Networks (OSNs) is popular all over the world. Millions of people join such networks to share their personal and public information and also to make new friends and relations. But...