Identity leakage mitigation on asymmetric secure sketch

We consider secure sketch construction in an asymmetric setting, that is, multiple samples are acquired during enrollment, but only a single sample is obtained during verification. Known protection methods apply secure sketch constructions on the average of the samples, while publishing the auxiliary information extracted from the set of samples, such as variances or weights of the features, in clear. Since the auxiliary information is revealed, an adversary can potentially use it to determine the relationship among multiple sketches, and gather information on the identity of the sketches. In this paper, we give a formal formulation of secure sketch under the asymmetric setting, and propose two schemes that mix the identity-dependent auxiliary information within the sketch. Our analysis shows that while our schemes maintain similar bounds of information loss compared to schemes that reveal the auxiliary information, they offer better privacy protection by limiting the linkages among sketches.