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Securing Privacy of Data in E-Marketing Against Malicious User
S. R. Jadhao1, Sampada Bhonde2
1Prof. S. R Jadhao, Department of Computer Science and Engineering, Babasaheb Naik College of Engineering, Pusad, MH, India.
2Sampada Bhonde, M.E. Student, Department of Computer Science and Engineering, Babasaheb Naik College of Engineering, Pusad, MH, India.
Manuscript received on June 27, 2015. | Revised Manuscript received on July 04, 2015. | Manuscript published on July 15, 2015. | PP: 1-5 | Volume-3 Issue-8, July 2015. | Retrieval Number: H0913073815/2015©BEIESP
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© The Authors. Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Internet is at its best for personal as well as professional use as long as it is involved in anonymous communication. There are many technologies which are evolving and growing consistently in the field of computer one of them is cloud computing. But, the security issues and threats associated with it still serve as hindrances. The focal point of this paper is privacy preserving of data in cloud. There are different approaches for preserving privacy of data. Our main concentration would be securing privacy of data in cloud by assigning ID’s (further referred as token) which are unique. The goal of unique ID’s is to eliminate the privacy risk by modifying the dataset in such a way that only owner can access the original data. Preferably, any authority, server or an adversary alone should not know any client’s personal information. This paper analyses and discusses various approaches for securing data like adopting cryptographic methods, writing access rights and policies, anonymising data, assigning unique ID’s or token .Finally, the approach is made as why anonymity technique is used. Algorithms are discussed for anonymous sharing of private data among N parties. A technique is used so that ID numbers are used ranging from 1 to N. This assignment is anonymous such that when the identities are received at other end these are unknown to the other members of the group.
Keywords: Anonymization and de-anonymization, cloud and distributed computing systems, multiparty computation, privacy preserving data mining, privacy protection.