Hybrid Privacy Preservation Technique Using Neural Networks

View Sample PDF

Author(s): R. VidyaBanu (Sri Krishna College of Engineering and Technology, India)and N. Nagaveni (Coimbatore Institute of Technology, India)
Copyright: 2019
Pages: 20
Source title: Cyber Law, Privacy, and Security: Concepts, Methodologies, Tools, and Applications
Source Author(s)/Editor(s): Information Resources Management Association (USA)
DOI: 10.4018/978-1-5225-8897-9.ch026

Keywords: Business & Management / Cyber Ethics / Information Science Reference / IT Security and Ethics

Purchase

View Hybrid Privacy Preservation Technique Using Neural Networks on the publisher's website for pricing and purchasing information.

Abstract

A novel Artificial Neural Network (ANN) dimension expansion-based framework that addresses the demand for privacy preservation of low dimensional data in clustering analysis is discussed. A hybrid approach that combines ANN with Linear Discriminant Analysis (LDA) is proposed to preserve the privacy of data in mining. This chapter describes a feasible technique for privacy preserving clustering with the objective of providing superior level of privacy protection without compromising the data utility and mining outcome. The suitability of these techniques for mining has been evaluated by performing clustering on transformed data and the performance of the proposed method is measured in terms of misclassification and privacy level percentage. The methods are further validated by comparing the results with traditional Geometrical Data Transformation Methods (GDTMs). The results arrived at are significant and promising.

The IRMA Community

Research IRM

Hybrid Privacy Preservation Technique Using Neural Networks

Purchase

Abstract

Related Content

IRMA Sponsors