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Now a days in the cloud networks huge amounts of data are stored and transferred from one location to another location. The data that is transferred from one place to another is exposed to attacks. Although various techniques or applications are available to protect data, loopholes exist. Anomaly detection uses some data mining techniques to detect the surprising behavior hidden within data increasing the chances of being intruded or attacked. Various hybrid approaches have also been made in order to detect known and unknown attacks more accurately. Cloud computing has become one of the most projecting words in the IT world due to its design for providing computing service as a utility. The typical use of cloud computing as a resource has changed the scenery of computing. Due to the increased flexibility, better reliability, great scalability and decreased costs have captivated businesses and individuals alike because of the pay-per-use form of the cloud environment. Cloud computing is a completely internet dependent technology where client data are stored and maintained in the data center of a cloud providers. The Anomaly Detection System is one of the Intrusion Detection techniques. It’s an area in the cloud environment that is been developed in the detection of unusual activities in the cloud networks. Although, there are a variety of Intrusion Detection techniques available in the cloud environment, this survey paper exposes and focuses on different IDS in cloud networks through different categorizations and conducts comparative study on the security measures of Drop box, Google Drive and iCloud, to illuminate their strength and weakness in terms of security.

Survey: Anomaly Detection in Cloud Based Networks and Security Measures in Cloud Date Storage Applications