在一个充满摄像头的世界中协助用户:计算机视觉应用的隐私意识基础设施

Anupam Das, Martin Degeling, Xiaoyou Wang, Junjue Wang, N. Sadeh, M. Satyanarayanan
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引用次数: 60

摘要

近年来,基于计算机视觉的技术得到了广泛的应用。这种用途不仅限于面部识别技术的快速采用,还扩展到面部表情识别,场景识别等。这些发展引起了人们对隐私的关注,需要新的解决方案来确保充分的用户意识,并在理想情况下控制由此产生的潜在敏感数据的收集和使用。虽然摄像头已经无处不在,但大多数时候用户甚至没有意识到它们的存在。在本文中,我们为物联网介绍了一种新的分布式隐私基础设施,并特别讨论了它如何帮助增强用户对有关他们的视频数据的收集和使用的意识和控制。该基础设施已经在两个校区进行了早期部署和评估,支持物联网资源的自动发现和用户的选择性通知。这包括收集用户数据的计算机视觉应用程序的存在。特别是,我们描述了一种功能的实现,该功能可以帮助用户发现附近的摄像头,并选择他们是否希望在视频流中对自己的面部进行变性。
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Assisting Users in a World Full of Cameras: A Privacy-Aware Infrastructure for Computer Vision Applications
Computer vision based technologies have seen widespread adoption over the recent years. This use is not limited to the rapid adoption of facial recognition technology but extends to facial expression recognition, scene recognition and more. These developments raise privacy concerns and call for novel solutions to ensure adequate user awareness, and ideally, control over the resulting collection and use of potentially sensitive data. While cameras have become ubiquitous, most of the time users are not even aware of their presence. In this paper we introduce a novel distributed privacy infrastructure for the Internet-of-Things and discuss in particular how it can help enhance user's awareness of and control over the collection and use of video data about them. The infrastructure, which has undergone early deployment and evaluation on two campuses, supports the automated discovery of IoT resources and the selective notification of users. This includes the presence of computer vision applications that collect data about users. In particular, we describe an implementation of functionality that helps users discover nearby cameras and choose whether or not they want their faces to be denatured in the video streams.
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