Rotation Perturbation Technique for Privacy Preserving in Data Stream Mining

Kalyani Kathwadia; Aniket Patel

doi:10.32628/IJSRSET184861

Rotation Perturbation Technique for Privacy Preserving in Data Stream Mining

Authors(2) :-Kalyani Kathwadia, Aniket Patel

Datasets is very challenging task in the systems. It is real processing. Data mining technique classification is one of the most important technique, in this paper is to classify the data as improve the classification accuracy, we have used ensemble model for classification of data. Randomization process added to privacy sensitive data after next process reconstruction to the main data from the perturbed data. Principal Component Analysis (PCA) is used to preserve the variability in the data. Rotation transformation can enlarge the increase the base classifiers and improve the accuracy of the ensemble classifier. In this paper, we analyses a rotation perturbation technique for PCA find eigenvector, load line plot and Zscore-Normalization method using to dimension in stream mining.

Authors and Affiliations

Kalyani Kathwadia
Department of Information Technology Silver Oak College of Engineering And Technology Ahmedabad, Gujarat, India
Aniket Patel
Department of Information Technology Silver Oak College of Engineering And Technology Ahmedabad, Gujarat, India

Data mining, Classification, Privacy, PCA, Z score-Normalization

N P Nethravathi, Prasanth G Rao, P Deepa Shenoy, Venugopal K R, Indramma M."CBTS: correlation based transformation strategy for privacy preserving data mining" (IEEE), 2015.
Julius Adebayo, Lalana Kagal. "A Privacy Protection for Procedure for Large Scale Individual Level Data" (IEEE), 2015.
C.Gokulnath, M.K.Priyan, Vishnu Ballan." Preservation of privacy in data mining by using PCA based perturbation technique" (IEEE), 2015.
Yingpeng Sang, Hong Shan, and Hui Tian. "Effective reconstruction of data perturbed by random projections" (IEEE) 2012.
Shuheng Zhou, Katrina Liggett, Larry Wasserman." Differential privacy with compression" (IEEE) 2009.
M.Parvathy, K. Sundarakantham, S. Mercy Shalinie, and C.Dhivya. "An efficient privacy protection machism for recommendation using hybrid transformation technique" (IEEE) 2014.
R.viidya Banu, N.Nagaveni." preservation of data privacy using PCA based transformation" (IEEE) 2009.
Zhen Lin, Jig Wang, Lian Liu, Jun Zhang."Generalized random rotation perturbation for vertically partitioned data sets" (IEEE) 2009.
Liming Li, Qishan Zhang."Privacy preserving clustering technique using hybrid data transformation method" (IEEE), 2009.
Li Liu, Murat kantarcioglu, and Bhavani Thuraisingham."The application of the perturbation model based privacy preserving data mining for real-word data" (IEEE) 2006.
Kun Liu, Hillol Kargupta, senior Member, IEEE, and Jessica Ryan. “Random projection based multiplicative data perturbation for privacy preserving distribution data mining" (IEEE) 2006.
Keke Chen, Ling Liu. "Privacy preserving data classification with rotation perturbation" (IEEE), 2005.

Publication Details

Published in : Volume 4 | Issue 8 | May-June 2018
Date of Publication : 2018-06-30
License: This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 217-223
Manuscript Number : IJSRSET184861
Publisher : Technoscience Academy

Print ISSN : 2395-1990, Online ISSN : 2394-4099

Cite This Article :

Kalyani Kathwadia, Aniket Patel, " Rotation Perturbation Technique for Privacy Preserving in Data Stream Mining, International Journal of Scientific Research in Science, Engineering and Technology(IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 4, Issue 8, pp.217-223, May-June-2018.
Journal URL : http://ijsrset.com/IJSRSET184861

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Manuscript Number : IJSRSET184861

Rotation Perturbation Technique for Privacy Preserving in Data Stream Mining