上下文感知隐私的基于规则的方法和评估

Lucas Teixeira, Fabiola Maffra, Kevin Lelu, Ahmed A. Al-Obaidi, A. Badii
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引用次数: 3

摘要

高分辨率监控系统对安全至关重要。然而,这些强大的工具已经被一些CCTV运营商滥用。政府和公民社会正试图在安全和隐私之间取得平衡。隐私过滤器可用于帮助保护包含个人身份信息(PH)的部分图像。本文提出了一种改进闭路电视显示屏隐私保护的新方法。我们的方法使用上下文线索来确定图像中每个人所需的隐私过滤级别。我们还提出了一种系统的方法来处理上下文线索。我们使用规则引擎来概括和促进该系统的定制,该系统在设计上应该专门用于给定环境中的操作。此外,我们提出了一个案例研究作为概念验证,其中我们创建了一个环境,提供高水平的隐私保护,同时允许所需的监视监控水平。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A rule-based methodology and assessment for context-aware privacy
High resolution surveillance systems are essential for security. However, these powerful tools have been misused by several CCTV operators. The governments and civil society are attempting to strike a balance between safety and privacy. Privacy filters can be used to help protect part of an image which included Personally Identifiable Information (PH). This paper presents a novel approach to improve the privacy protection in the CCTV displays. Our method uses context cues to determine the required privacy filtering level for each person in the image. We also present a systematic methodology to handle the context cues. We use a rules engine to generalise and facilitate the customisation of this system that by design should be specialized for operation in a given environment. In addition, we present a case study as a proof-of-concept whereby we have created an environment providing with high levels of privacy protection whilst allowing the required level of surveillance monitoring.
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