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A new variant of the DDoS attack, called Economic Denial of Sustainabilityattack has emerged. Since the cloud service is based on the pay-per-use model,the EDoS attack endeavors to scale up the resource usage over time to the pointthe purveyor of the server is financially incapable of sustaining the servicedue to the incurred unaffordable usage charges. The implication of the EDoSattack is a major security implication as more elastic cloud services are beingdeployed. Existing techniques to detect and mitigate such attacks are eitherhave low accuracy or ineffective and, in some cases, aggravate the attack evenfurther. Therefore, an Enhanced Mitigation Mechanism is proposed to addressthese shortcomings using OpenFlow and statistical techniques, i.e. HellingerDistance and Entropy. The experiments clearly depicted that EMM is able todetect and mitigate EDoS attacks with high accuracy and it is effective interms of resource utilization compared to existing mitigation techniques. Thus,can be deployed in the cloud environment without the need for additionalresource requirements.

Comparative Analysis of State-of-the-Art EDoS Mitigation Techniques in Cloud Computing Environment