scholarly journals A Comparative study of Multi Agent Based and High-Performance Privacy Preserving Data Mining

2010 ◽  
Vol 4 (12) ◽  
pp. 23-26
Author(s):  
Md Faizan Farooqui ◽  
Md Muqeem ◽  
Dr. Md Rizwan Beg
Keyword(s):  
Data Mining ◽  
Comparative Study ◽  
High Performance ◽  
Privacy Preserving ◽  
Privacy Preserving Data Mining ◽  
Agent Based ◽  
Multi Agent

A Perturbation Method Based on Singular Value Decomposition and Feature Selection for Privacy Preserving Data Mining

2014 ◽  
Vol 10 (1) ◽  
pp. 55-76 ◽  
Author(s):  
Mohammad Reza Keyvanpour ◽  
Somayyeh Seifi Moradi
Keyword(s):  
Data Mining ◽  
Feature Selection ◽  
Singular Value Decomposition ◽  
Perturbation Method ◽  
Privacy Preserving ◽  
Singular Value ◽  
Privacy Preserving Data Mining ◽  
Selection For ◽  
Value Decomposition ◽  
Different Levels

In this study, a new model is provided for customized privacy in privacy preserving data mining in which the data owners define different levels for privacy for different features. Additionally, in order to improve perturbation methods, a method combined of singular value decomposition (SVD) and feature selection methods is defined so as to benefit from the advantages of both domains. Also, to assess the amount of distortion created by the proposed perturbation method, new distortion criteria are defined in which the amount of created distortion in the process of feature selection is considered based on the value of privacy in each feature. Different tests and results analysis show that offered method based on this model compared to previous approaches, caused the improved privacy, accuracy of mining results and efficiency of privacy preserving data mining systems.

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