Most of the cloud services require users to share personal data like electronic medical record for data analysis and data mining, bringing privacy concerns. The data sets can be anonymized by using generalization method to attain such privacy requirement. At present the proportion of data in several cloud application growing greatly in congruence with the bid data trend, therefore it is a challenge for currently used software tools to capture , maintain and process such large-scale data within a suffient time. Consequently , it is difficult for achieving privacy due to their inefficiency in handling large scale data sets. In this paper, we propose a scalable two phase top down specialization(TDS) approach to anonymize large-scale data sets using map reduce technique on cloud computing. To achieve the specialization computation in a highly scalable way, we draft a group of creative map reduce jobs in both the phases of our approach. As a result, the experimental evaluation shows that the scalability and efficiency of TDS can be significantly enriched over existing approaches.

Ezhilarasi S, Indhumathy R, Helen Anitha M, Seetha

Data anonymization; top-down specialization; MapReduce; cloud;privacy preservation

'

 [1]. B.C.M. Fung, K. Wang, R. Chen, and P.S. Yu, “Privacy-Preserving Data Publishing: A Survey of Recent Devel- opments,” ACM Computing Surveys, vol. 42, no. 4, pp. 1-53, 2010.

[2]. N. Mohammed, B. Fung, P.C.K. Hung, and C.K. Lee, “Centralized and Distributed Anonymization for High-Dimensional Healthcare Data,” ACM Trans. Knowledge Discovery from Data, vol. 4, no. 4, Article 18, 2010.

[3]. B. Fung, K. Wang, L. Wang, and P.C.K. Hung, “Privacy-Preserving Data Publishing for Cluster Analysis,” Data and Knowledge Eng., vol. 68, no. 6, pp. 552-575, 2009.

[4]. N. Mohammed, B.C. Fung, and M. Debbabi, “Anonymity Meets Game Theory: Secure Data Integration with Malicious Participants,” VLDB J., vol. 20, no. 4, pp. 567-588, 2011.

[5]. H. Takabi, J.B.D. Joshi, and G. Ahn, “Security and Privacy Challenges in Cloud Computing Environments,” IEEE Security and Privacy, vol. 8, no. 6, pp. 24-31, Nov. 2010.

[6]. N. Cao, C. Wang, M. Li, K. Ren, and W. Lou, “Privacy-Preserving Multi-Keyword Ranked Search over Encrypted Cloud Data,” Proc. IEEE INFOCOM, pp. 829-837, 2011.

'

Publication Details
Published in : Volume 1 | Issue 1 | January-Febuary - 2015 Date of Publication Print ISSN Online ISSN 2015-02-25 2395-1990 2394-4099
Page(s)	Manuscript Number		Publisher
287-290	IJSRSET151163		Technoscience Academy
Cite This Article
Ezhilarasi S, Indhumathy R, Helen Anitha M, Seetha, "Preserving Privacy in Cloud Computing Environment using Map Reduce Technique", International Journal of Scientific Research in Science, Engineering and Technology(IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 1, Issue 1, pp.287-290, January-Febuary-2015. URL : http://ijsrset.com/IJSRSET151163.php