Raising Awareness of Location Information Vulnerabilities in Social Media Photos using LLMs
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arXiv
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| Autori principali: | , , , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2025
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| _version_ | 1866908284963782656 |
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| author | Ma, Ying Zhang, Shiquan Yang, Dongju Sarsenbayeva, Zhanna Knibbe, Jarrod Goncalves, Jorge |
| author_facet | Ma, Ying Zhang, Shiquan Yang, Dongju Sarsenbayeva, Zhanna Knibbe, Jarrod Goncalves, Jorge |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2503_20226 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Raising Awareness of Location Information Vulnerabilities in Social Media Photos using LLMs Ma, Ying Zhang, Shiquan Yang, Dongju Sarsenbayeva, Zhanna Knibbe, Jarrod Goncalves, Jorge Human-Computer Interaction 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. |
| title | Raising Awareness of Location Information Vulnerabilities in Social Media Photos using LLMs |
| topic | Human-Computer Interaction |
| url | https://arxiv.org/abs/2503.20226 |