Preservation of Online Users' Keyword Search Data Using Asymmetric Algorithm Method

Authors(2) :-R. Anusha, D. Sudha

Internet is the place where tons of online user behavior data are generated every day. These data are used to extract users' valuable information for research purposes or business interests. But, the data are under the risk of being exposed to third parties. Methods are implemented to perform the data aggregation in a privacy preserving manner. Most of the available methods assure strong privacy protection at the cost of very limited aggregation such as only summation, which hardly satisfies the need of behavior analysis. In this paper, proposed a model called PPSA. This model encrypts the users' sensitive data to prevent privacy from both outside analysts and the aggregation service provider. Also, completely supports selective aggregate functions for online user behavior analysis and guaranteeing differential privacy. Homomorphic RSA algorithm is used for encrypting users’ online behavior data. Implementation is done and its performances are evaluated based on a real time behavior set. Experimental results show that the proposed method effectively supports both overall aggregate queries and various selective aggregate queries with acceptable computation and communication overheads.

Authors and Affiliations

R. Anusha
Research Scholar, Department of Computer Science, A.V.C College, Mayiladuthurai, India
D. Sudha
Associate Professor, Department of Computer Science, A.V.C College, Mayiladuthurai, India

RSA, Homomorphic, Privacy Preserving, Selective Aggregation

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Publication Details

Published in : Volume 3 | Issue 7 | September-October 2018
Date of Publication : 2018-10-30
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 266-275
Manuscript Number : CSEIT183747
Publisher : Technoscience Academy

ISSN : 2456-3307

Cite This Article :

R. Anusha, D. Sudha, "Preservation of Online Users' Keyword Search Data Using Asymmetric Algorithm Method", International Journal of Scientific Research in Computer Science, Engineering and Information Technology (IJSRCSEIT), ISSN : 2456-3307, Volume 3, Issue 7, pp.266-275, September-October-2018.
Journal URL : http://ijsrcseit.com/CSEIT183747

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