Energy Aware Supervised Pattern Attack Recognition Technique for Mitigation of EDoS Attacks in Cloud Platform

Cloud computing is a rapidly growing technology in this new era. Cloud is a platform where users get charged on the basis of the services and resources they have used. It enables its users to access the cloud resources from the remote locations i.e. from anywhere at any time. It needs only a working internet connection to access the cloud services. Cloud users have always been victim to the security issues and attacks which leads to the data loss. The data is not saved on the hard disk of the computer so it is highly prone to security risks. Identifying the attacks on cloud platform is a difficult task because everything on cloud is in virtual form. EDoS (Economic Denial of Sustainability) attack is a form of DDoS attacks; carried out for a long span of time and intended to put a financial burden and cause economical loss to the users of cloud. Such attacks do not exhaust the bandwidth of the user; their main aim is to put a huge financial loss or burden on the user. A technique named as SPART (Supervised Pattern Attack Recognition Technique) implemented to mitigate the EDoS attacks in cloud computing which consumes lesser energy as compared to the existing models. The experimental results have shown the less energy consumption in proposed model.