Privacy Leakage from a Thousand Words: Millipixel Location Recovery from Dot Maps
Dot maps, which visualize individual data points as dots over a geographic region, are widely used across diverse domains to represent spatial patterns in sensitive data. However, the understanding of the privacy risks associated with dot maps remains limited, particularly for maps covering large geographic areas. In this paper, we systematically analyze these risks and present AutoLocate, an automated framework for high-precision location recovery. At its core, AutoLocate exploits anti-aliasing artifacts introduced during map rendering, which inadvertently encode sub-pixel information about dot locations. AutoLocate formulates location recovery as a black-box optimization problem, iterat...
| Authors | Yuntao Du, Tanishq Pauskar, Hao Wang et al. |
|---|---|
| Primary category | cs.CR |
| Published | 7 September 2026 |
| Last updated at source | 7 September 2026 |
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