Too Close for Comfort? Measuring Success of Sampled-Data Leakage Attacks Against Encrypted Search
D. Dittert, Thomas H. Schneider, Amos Treiber · 2023
The well-defined information leakage of Encrypted Search Algorithms (ESAs) is predominantly analyzed by crafting so-called leakage attacks. These attacks utilize adversarially known auxiliary data and the observed leakage to attack an ESA instance built on a user's data. Known-data attacks require the auxiliary data to be a subset of the user's data. In contrast, sampled-data attacks merely rely on auxiliary data that is, in some sense, statistically close to the user's data and hence reflect a much more realistic attack scenario where the auxiliary data stems from a publicly available data source instead of the private user's data.