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Preserving Privacy in Cloud Computing Environment using Map Reduce Technique


Ezhilarasi S, Indhumathy R, Helen Anitha M, Seetha
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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


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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.
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