Security Ensured Big Data Mining with Public Cloud Services
نویسنده
چکیده
Big data applications are constructed under the cloud environment to process the big data values. Public cloud provides easily scaled up and scaled down computing power and storage to everyone. Private cloud services are provided to group of people only. Big data can be used in disaster management, high energy physics, genomics, connectomics, automobile simulations and medical imaging applications. Public cloud service components and private cloud data resources are integrated to form cross cloud services. Cross cloud service composition provides a concrete approach capable for large scale big data processing. Private clouds refuse to disclose all details of their service transaction records. History record based Service optimization method (HireSome-II) is privacy aware cross cloud service composition method. QoS history records are used to estimate the cross cloud service composition plan. k-means algorithm is used as a data filtering tool to select representative history records. HireSome-II reduces the time complexity of cross cloud service composition plan for big data processing. Big data mining operations are integrated with the History record based Service optimization method (HireSome-II). Security and privacy is provided for cross cloud service composition based big data processing environment. Privacy preserved map reduce methods are adapted to support high scalability. The HireSome-II scheme is upgraded to support mining operations on big data.
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تاریخ انتشار 2016