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Using User Preferences to Enhance Privacy in Pervasive Systems

机译:使用用户偏好来增强普及系统中的隐私

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With the increasing interest in developing pervasive computing technologies there is growing recognition of the problems of maintaining user privacy. In the Daidalos pervasive system this is achieved primarily through the use of virtual identities, which are used to conceal the real identity of the user. One problem with this lies in determining to what extent the user should be engaged in the decisions relating to the selection of virtual identities, and what can be done automatically. The solution lies in creating a set of user preferences to assist in taking these decisions, refining them through the use of machine learning techniques. This paper outlines the approach being investigated and describes how this will be achieved when the processes involved in building up user preferences are not trusted.
机译:随着对发展普遍计算技术的兴趣日益越来越彰显识别维护用户隐私的问题。在DAIDALOS普遍系统中,这主要是通过使用虚拟身份来实现的,用于隐藏用户的真实身份。其中一个问题在于确定用户应该在多大程度上参与与选择虚拟身份的决策,以及可以自动完成的。解决方案在于创建一组用户偏好,以帮助采取这些决策,通过使用机器学习技术来改进它们。本文概述了所调查的方法,并描述如何在构建用户偏好的进程不信任时,这将如何实现。

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