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Semi-Automated Derivation of Personal Privacy Policies

Semi-Automated Derivation of Personal Privacy Policies
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Author(s): George Yee (National Research Council Canada, Canada) and Larry Korba (National Research Council Canada, Canada)
Copyright: 2004
Pages: 4
Source title: Innovations Through Information Technology
Source Editor(s): Mehdi Khosrow-Pour, D.B.A. (Information Resources Management Association, USA)
DOI: 10.4018/978-1-59140-261-9.ch117
ISBN13: 9781616921255
EISBN13: 9781466665347

Abstract

Growth of the Internet has been accompanied by growth of Internet e-services (e.g. e-commerce, e-health). This proliferation of e-services has in turn fueled the need to protect the personal privacy of e-service users. We advocate a privacy policy negotiation approach to protecting personal privacy [1,2]. However, it is evident that the specification of a personal privacy policy must be as easy as possible for the consumer. In this paper, we define the content of personal privacy policies using privacy principles that have been enacted into legislation. We then present two semi-automated approaches for the derivation of personal privacy policies. The first approach makes use of common privacy rules obtained through community consensus. This consensus can be obtained from research and/or surveys. The second approach makes use of existing privacy policies in a peer-to-peer community.

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