5. CONCLUSION
Cloud computing is the on-demand availability of computer system resources, especially data storage and computing power, without direct active management by the user. Therefore, there is a lot of chances for security attacks especially botnet attack to degrade the quality of cloud service influenced by botmaster. Thus the proposed robustive network traffic analyzer based on superintend ensemble-learning mechanism, has clustered the each type of botnet attack such distributed denial of service, spam botnet attack and maintain the reliability and quality of service in cloud based applications. Thus, the result obtained for the proposed system has exposed better performance when compared to existing systems. The proposed system has taken optimal precision value of0.961 and recall value of 0.986. It accomplished high F-measure value of 0.976 and high detection accuracy value of 99.04.