Abstract
AbstractCloud computing is our present and future. Most of us knowingly and unknowingly depend on cloud for everyday life for storing, retrieving, and accessing. As the cloud is vulnerable to attacks, we do not know what kind of attacks is encountering which might collapse our security. Unknown attacks are the one that has not perceived yet; hence, we focused on detecting unknown attacks in the cloud. We proposed a novel approach for detecting attacks based on correlation coefficients which will give casual relationships between pair of attributes, calculated Euclidean distance, and applied hierarchical agglomerative clustering algorithm for building clusters which separate clusters of normal and abnormal users. Our approach has shown better results compared with other approaches.KeywordsCloudMachine learningCorrelation coefficientsUnknown attackHierarchical clustering
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