Abstract: Security of software system and network resources, data and information communications based on cloud computing environment has turn into a foremost problem for the improvement of cloud computing. based on the description and model of introduction of intrusion detection system(IDS), collective with characteristics of cloud computing, this paper use subspace partition and outline coefficient with intersect K-means algorithm, consequently it is probable to predict dissimilar types of attacks effectively. In the case lacking prior knowledge, it clusters events with the similar or comparable characteristics to determine unknown attacks, which has enhanced self-learning capability. Precise giving of this paper is as follow. Primary, it summarize cloud computing intrusion detection approach and proposes an enhanced intersect fuzzy intrusion detection technique and The proposed methodologies include fuzzy clustering, fuzzy clustering by local approximation of memberships based on ANN. The accessible anomaly-based approach is assessing by simulation experiments and comparison of the obtained results.
Keywords: Hybrid intrusion detection; Cloud computing, Distributed event correlation, security; complex event processing.