New Framework to Detect and Prevent Denial of Service Attack in Cloud Computing Environment

As a result of integration of many techniques such as grading, clustering, utilization computing and resource's sharing, cloud computing has been appeared as multi element's composition technology, it offers several computing services such as IaaS (infrastructure as service), PaaS (platform as service) and SaaS (software as service) based on pay as you use rule, but nevertheless, and because of cloud computing end users participate in computing resources (co_ tenancy) , and by which infrastructure computing can be shared by a number of users, and as a result to this feature, some security challenges has been existed and one of the most serious security threats is flooding attack, which prevent other users from using cloud infrastructure services, that kind of attack can be done by a legitimate or illegitimate cloud computing users. To overcome this problem various approaches have been proposed based on Artificial intelligence and statistical methods, but most of them concentrate on one side of problem and neglect the other aspects. In our proposed approach, the focusing will be more in overcoming the problem in all its aspects, in attack detection stage covariance matrix statistical method will be applied and to determine attack source TTl (Time_to_Life) value counting method will be used, and the attack prevention will be based on Honeypot method, and initial simulation to this approach using UML class diagram and sequence diagram showed where our proposed framework can be done in cloud environment.