A method for preservation of privacy in data mining processes

Danyan Liang, Peter Busch, Winnie Picoto

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contribution

Abstract

Most ethical issues in data mining have paid more attention to government excesses, while ignoring the critical issue of national security and how data mining can be used to improve it. This paper illustrates how technology can be used to ensure personal privacy is preserved while security agencies use data mining tools to identify behavior patterns of individuals, which may form a security threat to the country. We show that Anonymized data (ANNA) software can be integrated with Non-Obvious Relationship Awareness (NORA) to encrypt data before mining. Understanding the types of users in the process of data mining can help determine privacy concerns of every user and thus develop appropriate measures to ensure privacy is preserved. We also demonstrate how process models can be designed for standardizing the data mining process to track individuals or organizations with access to metadata, retrieve personal profiles and also keep such profiles private.

Original languageEnglish
Title of host publicationProceedings of the 32nd International Business Information Management Association Conference, IBIMA 2018
Subtitle of host publicationVision 2020: Sustainable Economic Development and Application of Innovation Management from Regional expansion to Global Growth
EditorsKhalid S. Soliman
Place of PublicationSeville Spain
PublisherInternational Business Information Management Association (IBIMA)
Pages203-223
Number of pages21
ISBN (Electronic)9780999855119
Publication statusPublished - 2018
Event32nd International Business Information Management Association Conference, IBIMA 2018 - Seville, Spain
Duration: 15 Nov 201816 Nov 2018

Conference

Conference32nd International Business Information Management Association Conference, IBIMA 2018
CountrySpain
CitySeville
Period15/11/1816/11/18

Keywords

  • Business Process Modelling
  • Data Mining
  • Privacy
  • Visio

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