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Information Resources Management Association
Advancing the Concepts & Practices of Information Resources Management in Modern Organizations

Legal and Technical Issues of Privacy Preservation in Data Mining

Legal and Technical Issues of Privacy Preservation in Data Mining
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Author(s): Kirsten Wahlstrom (University of South Australia, Australia), John F. Roddick (Flinders University, Australia), Rick Sarre (University of South Australia, Australia), Vladimir Estivill-Castro (Griffith University, Australia) and Denise de Vries (Flinders University, Australia)
Copyright: 2009
Pages: 6
Source title: Encyclopedia of Data Warehousing and Mining, Second Edition
Source Author(s)/Editor(s): John Wang (Montclair State University, USA)
DOI: 10.4018/978-1-60566-010-3.ch180


View Legal and Technical Issues of Privacy Preservation in Data Mining on the publisher's website for pricing and purchasing information.


To paraphrase Winograd (1992), we bring to our communities a tacit comprehension of right and wrong that makes social responsibility an intrinsic part of our culture. Our ethics are the moral principles we use to assert social responsibility and to perpetuate safe and just societies. Moreover, the introduction of new technologies can have a profound effect on our ethical principles. The emergence of very large databases, and the associated automated data analysis tools, present yet another set of ethical challenges to consider. Socio-ethical issues have been identified as pertinent to data mining and there is a growing concern regarding the (ab)use of sensitive information (Clarke, 1999; Clifton et al., 2002; Clifton and Estivill-Castro, 2002; Gehrke, 2002). Estivill-Castro et al., discuss surveys regarding public opinion on personal privacy that show a raised level of concern about the use of private information (Estivill-Castro et al., 1999). There is some justification for this concern; a 2001 survey in InfoWeek found that over 20% of companies store customer data with information about medical profile and/or customer demographics with salary and credit information, and over 15% store information about customers’ legal histories.

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