为大学环境量身定制具有隐私意识、值得信赖的协作智能空间

N. Liampotis, E. Papadopoulou, N. Kalatzis, I. Roussaki, Pavlos Kosmides, E. Sykas, D. Bental, N. Taylor
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引用次数: 1

摘要

用户向普及系统或社交媒体披露的信息越多,他们享受的个性化服务质量就越高,体验也就越丰富。然而,使用这些系统的个人的隐私问题在过去几年急剧上升,特别是在各种计算或通信系统的大规模安全漏洞事件已经成为新闻之后。本章介绍了society项目所采用的方法,以保护敏感用户数据的隐私,并确保通过社会和普适计算系统提供的服务的可信度。这个框架已经被设计、实施,并通过实际的用户试验进行了评估。除了讨论各自的需求、架构和功能外,本章还详细介绍了在大学环境中进行的用户试用,重点是获得的隐私和信任评估结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Tailoring Privacy-Aware Trustworthy Cooperating Smart Spaces for University Environments
The more information users disclose to pervasive systems or social media, the better quality and enhanced experience they enjoy for a wider variety of personalised services. However, the privacy concerns of individuals that use such systems have dramatically risen the last years, especially after several events of massive security breaches in various computing or communication systems that have reached the news. This chapter presents the approach being employed by the SOCIETIES project to protect the privacy of sensitive user data and ensure the trustworthiness of delivered services via social and pervasive computing systems. This framework has already been designed, implemented and evaluated via real user trials engaging wide and heterogeneous user populations. In addition to the respective requirements, architecture and features discussed herewith, this chapter elaborates on the user trial that has been conducted in university settings to validate this system focusing on the privacy and trust evaluation results obtained.
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