Raising Awareness of Location Information Vulnerabilities in Social Media Photos using LLMs

要旨

Location privacy leaks can lead to unauthorised tracking, identity theft, and targeted attacks, compromising personal security and privacy. This study explores LLM-powered location privacy leaks associated with photo sharing on social media, focusing on user awareness, attitudes, and opinions. We developed and introduced an LLM-powered location privacy intervention app to 19 participants, who used it over a two-week period. The app prompted users to reflect on potential privacy leaks that a widely available LLM could easily detect, such as visual landmarks & cues that could reveal their location, and provided ways to conceal this information. Through in-depth interviews, we found that our intervention effectively increased users’ awareness of location privacy and the risks posed by LLMs. It also encouraged users to consider the importance of maintaining control over their privacy data and sparked discussions about the future of location privacy-preserving technologies. Based on these insights, we offer design implications to support the development of future user-centred, location privacy-preserving technologies for social media photos.

著者
Ying Ma
The University of Melbourne, Melbourne, Australia
Shiquan Zhang
University of Melbourne, Melbourne, Victoria, Australia
Dongju Yang
University of Melbourne, Melbourne, Victoria, Australia
Zhanna Sarsenbayeva
University of Sydney, Sydney, Australia
Jarrod Knibbe
The University of Queensland, St Lucia, QLD, Australia
Jorge Goncalves
University of Melbourne, Melbourne, Australia
DOI

10.1145/3706598.3714074

論文URL

https://dl.acm.org/doi/10.1145/3706598.3714074

動画

会議: CHI 2025

The ACM CHI Conference on Human Factors in Computing Systems (https://chi2025.acm.org/)

セッション: Data Privacy and Ethics

G304
7 件の発表
2025-04-30 20:10:00
2025-04-30 21:40:00
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