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.