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

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.

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Publication Details

Published
2025-04-24
DOI
https://doi.org/10.1145/3706598.3714074
Citations
3
Primary Topic
Privacy-Preserving Technologies in Data
Type
article
Field-Weighted Citation Impact
7.44
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article

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

Jarrod Knibbe, Jorge Gonçalves, Zhanna Sarsenbayeva, Dongju Yang et al.
3 citations
Privacy-Preserving Technologies in Data
7.44
article

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

Jarrod Knibbe, Jorge Gonçalves, Zhanna Sarsenbayeva, Dongju Yang, Shiquan Zhang, Ying Ma
article en
3 citations

Abstract

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.

The University of Sydney (AU), The University of Queensland (AU), The University of Melbourne (AU)
Reduced inequalities
Openalex Percentile: Top 3%
Privacy-Preserving Technologies in Data
7.44
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