用不精确的隐私偏好推理

Inah Omoronyia
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引用次数: 10

摘要

信息披露过程中的用户不情愿和情境依赖因素意味着人们并不总是能够表明他们适当的隐私偏好。这种现象就是众所周知的“隐私悖论”,这表明现代技术的用户不断关注他们的隐私,但并没有将这些担忧应用到他们的使用行为中。问题是,在对隐私要求的满足进行推理时,没有考虑到隐私问题与软件中所指示的隐私偏好之间的不匹配。本文的研究愿景是将用户隐私偏好的不精确性与隐私需求满足的推理联系起来。我们概述了隐私与用户信念和不确定性之间的密切关系。然后,我们提出了一个多代理框架,在推理隐私需求的满足时利用这种关系。我们预计这一愿景将有助于缩小日益复杂的信息时代与保护用户隐私所需的软件技术之间的差距。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Reasoning with imprecise privacy preferences
User reluctance and context-dependent factors during information disclosure imply that people cannot always be counted on to indicate their appropriate privacy preference. This phenomenon is the well-known 'privacy paradox', which shows that users of modern technologies are constantly concerned about their privacy, but do not apply these concerns to their usage behaviour accordingly. The problem is that this mismatch between privacy concerns and the indicated privacy preference in software, is not considered when reasoning about the satisfaction of privacy requirements. This paper is a research vision that draws connections between the imprecisions in user privacy preferences, and reasoning about the satisfaction of privacy requirements. We outline the close relationship between privacy and user beliefs and uncertainties. We then propose a multi-agent framework that leverage on this relationship when reasoning about the satisfaction of privacy requirements. We anticipate that this vision will help reduce the gap between an increasingly complex information age and the software techniques needed to protect user privacy.
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