A rule-based methodology and assessment for context-aware privacy

Abstract

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 (PII). 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.

Minor Privacy Protection Through Real-time Video Processing at the Edge

“…Levi and his colleagues [16] use a CNN to classify primary objects in an image between gender and age. Meanwhile, a rule based method has been also proposed that divides the image into sections and implement privacy measures based on rule sets [32]. The last method we compared with is [7] which…”

“…Accuracy Otto et al [26] 81.27 % Levi et al [16] 84.7 % Teixeira et al [32] 91.14 % Du et al [7] 79.24 % MiPRE 92.1 % tries to extract facial features and accurately detect the age of each. As shown by Table 1, our MiPRE scheme achieves a better performance in terms of accuracy than of these reported efforts.…”