Please Forget Where I Was Last Summer: The Privacy Risks of Public Location (Meta)Data
Kostas Drakonakis, Panagiotis Ilia, Sotiris Ioannidis, Jason Polakis
Abstract
The exposure of location data constitutes a significant privacy risk to users as it can lead to de-anonymization, the inference of sensitive information, and even physical threats. In this paper we present LPAuditor, a tool that conducts a comprehensive evaluation of the privacy loss caused by publicly available location metadata. First, we demonstrate how our system can pinpoint users' key locations at an unprecedented granularity by identifying their actual postal addresses. Our experimental evaluation on Twitter data highlights the effectiveness of our techniques which outperform prior approaches by 18.9%-91.6% for homes and 8.7%-21.8% for workplaces. Next we present a novel exploration of automated private information inference that uncovers "sensitive" locations that users have visited (pertaining to health, religion, and sex/nightlife). We find that location metadata can provide additional context to tweets and thus lead to the exposure of private information that might not match the users' intentions. We further explore the mismatch between user actions and information exposure and find that older versions of the official Twitter apps follow a privacy-invasive policy of including precise GPS coordinates in the metadata of tweets that users have geotagged at a coarse-grained level (e.g., city). The implications of this exposure are further exacerbated by our finding that users are considerably privacy-cautious in regards to exposing precise location data. When users can explicitly select what location data is published, there is a 94.6% reduction in tweets with GPS coordinates. As part of current efforts to give users more control over their data, LPAuditor can be adopted by major services and offered as an auditing tool that informs users about sensitive information they (indirectly) expose through location metadata.
Ask about this paper
Your agent reads all of it.
Lune indexed this paper to the last equation, along with the top-tier papers that cite it. Ask a question and the answer quotes them.
Your agent calls
Luneget_paper_fulltext
Free to start. No credit card required.
Terminal
Install the CLIlune papers fulltext 9cdc7f0a-73d0-4a0a-a319-6acdf8b638b7Cited by top-tier papers5
- On (The Lack Of) Location Privacy in Crowdsourcing ApplicationsSpyros Boukoros, Mathias Humbert, Stefan Katzenbeisser, Carmela TroncosoUSENIX Security 2019 · 28 citations
- Swipe Left for Identity Theft: An Analysis of User Data Privacy Risks on Location-based Dating AppsKarel Dhondt, Victor Le Pochat, Yana Dimova, Wouter Joosen et al.USENIX Security 2024 · 4 citations
- Everyone's Privacy Matters! An Analysis of Privacy Leakage from Real-World Facial Images on Twitter and Associated User BehaviorsYuqi Niu, Weidong Qiu, Peng Tang, Lifan Wang et al.CSCW 2025 · 3 citations
- Health Hazard, Handle with Care: Investigating the Privacy Risks of Android's Health ConnectKonstantinos Spyridakis, Ioannis Arkalakis, Michalis Diamantaris, Sotiris Ioannidis et al.USENIX Security 2026
- Carnus: Exploring the Privacy Threats of Browser Extension FingerprintingSoroush Karami, Panagiotis Ilia, Konstantinos Solomos, Jason PolakisNDSS 2020
Builds on3
- Membership Inference Attacks Against Machine Learning ModelsReza Shokri, Marco Stronati, Congzheng Song, Vitaly ShmatikovS&P 2017 · 5,137 citations
- Knock Knock, Who's There? Membership Inference on Aggregate Location DataApostolos Pyrgelis, Carmela Troncoso, Emiliano De CristofaroNDSS 2018 · 293 citations
- walk2friends: Inferring Social Links from Mobility ProfilesMichael Backes, Mathias Humbert, Jun Pang, Yang ZhangCCS 2017 · 123 citations
Related papers
- How does misconfiguration of analytic services compromise mobile privacy?Xueling Zhang, Xiaoyin Wang, Rocky Slavin, Travis D. Breaux et al.ICSE 2020 · 21 citations
- Privacy Leakage from a Thousand Words: Millipixel Location Recovery from Dot MapsYuntao Du, Tanishq Pauskar, Hao Wang, Jing Su et al.CCS 2026
- Raising Awareness of Location Information Vulnerabilities in Social Media Photos using LLMsYing Ma, Shiquan Zhang, Dongju Yang, Zhanna Sarsenbayeva et al.CHI 2025 · 11 citations
- A Run a Day Won't Keep the Hacker Away: Inference Attacks on Endpoint Privacy Zones in Fitness Tracking Social NetworksKarel Dhondt, Victor Le Pochat, Alexios Voulimeneas, Wouter Joosen et al.CCS 2022 · 11 citations
- Doxing via the Lens: Revealing Location-related Privacy Leakage on Multi-modal Large Reasoning ModelsWeidi Luo, Tianyu Lu, Qiming Zhang, Xiaogeng Liu et al.ICLR 2026 · 13 citations
