Privacy Preserving Data Mining for Deliberative Consultations

Conference paper

DOI: 10.1007/978-3-319-32034-2_9

Part of the Lecture Notes in Computer Science book series (LNCS, volume 9648)
Cite this paper as:
Andruszkiewicz P. (2016) Privacy Preserving Data Mining for Deliberative Consultations. In: Martínez-Álvarez F., Troncoso A., Quintián H., Corchado E. (eds) Hybrid Artificial Intelligent Systems. HAIS 2016. Lecture Notes in Computer Science, vol 9648. Springer, Cham

Abstract

In deliberative consultations, which utilise electronic surveys as a tool to obtain information from residents, preserving privacy plays an important role. In this paper investigation of a possibility of privacy preserving data mining techniques application in deliberative consultations has been conducted. Three main privacy preserving techniques; namely, heuristic-based, reconstruction-based, and cryptography-based have been analysed and a setup for online surveys performed within deliberative consultations has been proposed.

This work can be useful for designers and administrators in the assessment of the privacy risks they face with a system for deliberative consultations. It can also be used in the process of privacy preserving incorporation in such a system in order to help minimise privacy risks to users.

Keywords

Privacy preserving data mining Deliberative consultations Reconstruction-based technique Cryptography-based technique Heuristic-based technique 

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.Institute of Computer ScienceWarsaw University of TechnologyWarsawPoland

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