Decaying Photos for Enhanced Privacy: User Perceptions Towards Temporal Redactions and 'Trusted' Platforms

被引:2
作者
Pias S.B.H. [1 ]
Ahmad I. [1 ]
Akter T. [1 ]
Kapadia A. [1 ]
Lee A.J. [2 ]
机构
[1] Department of Computer Science, Indiana University, Bloomington
[2] Department of Computer Science, University of Pittsburgh, Pittsburgh
来源
Proceedings of the ACM on Human-Computer Interaction | 2022年 / 6卷 / CSCW2期
关键词
image obfuscation; photo sharing; privacy; trusted hardware;
D O I
10.1145/3555538
中图分类号
学科分类号
摘要
With the rising popularity of photo sharing in online social media, interpersonal privacy violations, where one person violates the privacy of another, have become an increasing concern. Although applying image obfuscations can be a useful tool for improving privacy when sharing photos, prior studies have found these obfuscation techniques adversely affect viewers' satisfaction. On the other hand, ephemeral photos, popularized by apps such as Snapchat, allow viewers to see the entire photo, which then disappears shortly thereafter to protect privacy. However, people often use workarounds to save these photos before deletion. In this work, we study people's sharing preferences with two proposed 'temporal redactions', which combines ephemerality with redactions to allow viewers to see the entire image, yet make these images safe for longer storage through a gradual or delayed application of redaction on the sensitive portions of the photo. We conducted an online experiment (N=385) to study people's sharing behaviors in different contexts and under different levels of assurance provided by the viewer's platform (e.g., guaranteeing temporal redactions are applied through the use of 'trusted hardware'). Our findings suggest that the proposed temporal redaction mechanisms are often preferred over existing methods. On the other hand, more efforts are needed to convey the benefits of trusted hardware to users, as no significant differences were observed in attitudes towards 'trusted hardware' on viewers' devices. © 2022 ACM.
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