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INTERNATIONAL JOURNAL OF ENGINEERING DEVELOPMENT AND RESEARCH
(International Peer Reviewed,Refereed, Indexed, Citation Open Access Journal)
ISSN: 2321-9939 | ESTD Year: 2013

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Paper Details
Paper Title
Implementation of Privacy Preserving Data Classification System Using Machine Learning Technique
Authors
  Miss. Sayali B. Desale,  Prof. S.B. Javheri

Abstract
a decision support system is a computerised process which can help to make decision and action with users and help users to gain the extra knowledge. In this system server has rich dataset for particular application. In this scenario, data arranged in outside servers through the web by data owners for analysing user’s results. But these servers are outsider servers which are not completely trusted, so here comes a privacy concern. The main purpose of this system is to design a novel privacy-preserving data classification system by using the machine learning technique Artificial Neural Network for the purpose of classification. To provide a security we use Paillier homomorphic encryption technique where all the computations can be done in encrypted form. Neither the server involved in the process nor the user ready to realize any additional learning about the server side parameters and results. So, user’s data as well as categorization parameters from server side will secure and the security of user’s information is not bargained.

Keywords- Artificial Neural Network, back-propagation Homomorphic encryption, privacy preservation.
Publication Details
Unique Identification Number - IJEDR1603065
Page Number(s) - 397-403
Pubished in - Volume 4 | Issue 3 | August 2016
DOI (Digital Object Identifier) -   
Publisher - IJEDR (ISSN - 2321-9939)
Cite this Article
  Miss. Sayali B. Desale,  Prof. S.B. Javheri,   "Implementation of Privacy Preserving Data Classification System Using Machine Learning Technique", International Journal of Engineering Development and Research (IJEDR), ISSN:2321-9939, Volume.4, Issue 3, pp.397-403, August 2016, Available at :http://www.ijedr.org/papers/IJEDR1603065.pdf
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