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Blur vs. Block: Investigating the Effectiveness of Privacy-Enhancing Obfuscation for Images

机译:Blur vs.块:调查隐私的有效性 - 增强图像的图像

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Computer vision can lead to privacy issues such as unauthorized disclosure of private information and identity theft, but it may also be used to preserve user privacy. For example, using computer vision, we may be able to identify sensitive elements of an image and obfuscate those elements thereby protecting private information or identity. However, there is a lack of research investigating the effectiveness of applying obfuscation techniques to parts of images as a privacy-enhancing technology. In particular, we know very little about how well obfuscation works for human viewers or users' attitudes towards using these mechanisms. In this paper, we report results from an online experiment with 53 participants that investigates the effectiveness two exemplar obfuscation techniques: "blurring" and "blocking", and explores users' perceptions of these obfuscations in terms of image satisfaction, information sufficiency, enjoyment, and social presence. Results show that although "blocking" is more effective at de-identification compared to "blurring" or leaving the image "as is", users' attitudes towards "blocking" are the most negative, which creates a conflict between privacy protection and users' experience. Future work should explore alternative obfuscation techniques that could protect users' privacy and also provide a good viewing experience.
机译:计算机愿景可以导致隐私问题,例如未经授权披露私人信息和身份盗用,但它也可用于保护用户隐私。例如,使用计算机愿景,我们可能能够识别图像的敏感元素并使这些元素混淆,从而保护私人信息或身份。然而,缺乏研究调查将混淆技术应用于作为隐私增强技术的图像部分的有效性。特别是,我们对人类观众或用户对使用这些机制的态度的态度有多少些了解。在本文中,我们报告了一个在线实验的结果,其中53名参与者调查了两个示例性混淆技术的有效性:“模糊”和“阻止”,并在图像满足,信息充足,享受,信息充足,享受方面探讨了用户对这些混淆的看法。和社会存在。结果表明,虽然“堵”是在去标识更有效相比,“模糊”或离开图像“原样”,用户对‘堵’的态度是最消极的,它创建隐私保护和用户之间的冲突经验。未来的工作应该探索可以保护用户隐私的替代混淆技术,并提供了良好的观看体验。

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