Adaptive Pattern Attack Recognition technique (APART) against EDoS attacks in Cloud Computing

Cloud Computing is now one of the most hyped information technology arenas and it has becoming one of the fastest rising sections of IT. Cloud computing permits us to scale our servers in greatness and availability in order to provide services to a greater number of end users. Furthermore, adopters of the cloud service model are charged based on a pay-per-use basis of the cloud's server and network resources. Resources can easily be scaled up or down dynamically without much interaction between client and service provider. The function of this model is to reduce the effect of EDoS attack by some tactical enemy/s, set of enemies or zombie machine system (BOTNET) to curtail the accessibility of the target resources, which declines the profits and increases the cost of the different cloud workers in a direct or indirect way. In this paper, we proposed an approach, named Pattern Attack Recognition, to detect the Economical-Denial-Of-Sustainability (EDoS) attack from cloud platforms. We sketch a proposed model to assess Outcome of the results in terms of its response time and resource usage.