Abstract
Nowadays there is rapid growth in large-scale databases and cloud computing is becoming tempting key to host data query services due to its advantages in scalability and cost-economy. So organizations are moving towards cloud computing infrastructure. In the commercial areas use of cloud computing has increased due to its features like pay per use, fault tolerance, scalability, elasticity. Despite of these advantages some data owner hesitates to put their data on cloud which is confidential. Unless confidentiality of data and privacy in query processing are not guaranteed, some data owner does not want to move to the cloud. A secured query service should provide efficiency in query processing as well as it needs to reduce the workload of in-house infrastructure to gain the benefits of cloud computing infrastructure. RASP data perturbation is proposed to provide balance between security and efficiency of protected data. RASP method stands for Random Space Perturbation which combines injection of noise, preserving order of encryption. For enhancing performance indexing techniques are also used.
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Dipali Darpe, Jyoti Nighot (2017). Data Perturbation: An Approach to Protect Confidential Data in Cloud Environment. In: Satapathy, S., Bhateja, V., Joshi, A. (eds) Proceedings of the International Conference on Data Engineering and Communication Technology. Advances in Intelligent Systems and Computing, vol 469. Springer, Singapore. https://doi.org/10.1007/978-981-10-1678-3_33
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DOI: https://doi.org/10.1007/978-981-10-1678-3_33
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