Cloud computing provides storage capacity without any infrastructure investment. Fair resource allocation among applications and dynamically adopts the load changes that means the resource allocation must be scalable both in number of machines and in number of sites. Preserving of privacy is still challenging problem in cloud. To overcome that, all the data are encrypted in existing system. But encrypting all data is neither efficient nor cost effective because it is very time consuming when the data are frequently accessed or processed. In this paper we propose one constraint based approach to identify which data need to be encrypted and which do not. It automatically reduces the time to access the data in cloud. Evaluation results demonstrate that the privacy-preserving cost of data can be reduced with our approach over existing ones where all data sets are encrypted.
 M. Armbrust, A. Fox, R. Griffith, A.D. Joseph, R. Katz, A. Konwinski, G. Lee, D. Patterson, A. Rabkin, I. Stoica, and M. Zaharia, ―A View of Cloud Computing,‖ Comm. ACM, vol. 53, no. 4, pp. 50-58, 2010. R. Buyya, C.S. Yeo, S. Venugopal, J. Broberg, and I. Brandic, ―Cloud Computing and Emerging It Platforms: Vision, Hype, and Reality for Delivering Computing as the Fifth Utility,‖ Future Generation Computer Systems, vol. 25, no. 6, pp. 599-616, 2009.  L. Wang, J. Zhan, W. Shi, and Y. Liang, ―In Cloud, Can Scientific Communities Benefit from the Economies of Scale?,‖ IEEE Trans. Parallel and Distributed Systems, vol. 23, no. 2, pp. 296-303, Feb. 2012.  H. Takabi, J.B.D.. joshi, and G. Ahn, ―Security and Privacy Challenges in Cloud Computing Environments,‖ IEEE Security & privacy, vol. 8, no. 6, pp. 24-31, Nov. /Dec. 2010.