Year: 2016 to Present | Clemson University | Co-authors: Dr. Kelly Caine, Dr. Bart Knijnenburg, Dr. Hongxin Hu, Nishant Vishwamitra | Skill: Experimental Design, Quantitative Data Analysis | Role: PhD Leader
Online social networks (OSNs) such as Facebook have become a prevalent way for individuals to present themselves, and remain connections with others. However, the huge amount of data sharing may lead to privacy issues.
Current collaborative photo privacy protection solutions can be categorized into two approaches: controlling the recipient, which restricts certain viewers’ access to the photo, and controlling the content, which protects all or part of the photo from being viewed. Focusing on the latter approach, we introduce privacy-enhancing obfuscations for photos and conduct an online experiment with 271 participants to evaluate their effectiveness against human recognition and how they affect the viewing experience.
Results indicate the two most common obfuscations, blurring and pixelating, are ineffective. On the other hand, inpainting, which removes an object or person entirely, and avatar, which replaces content with a graphical representation are effective. From a viewer experience perspective, blurring, pixelating, inpainting, and avatar are preferable. Based on these results, we suggest inpainting and avatar may be useful as privacy-enhancing technologies for photos, because they are both effective at increasing privacy for elements of a photo and provide a good viewer experience.