Key points are not available for this paper at this time.
Motivated by the application of private statistical analysis of large databases, we consider the problem of selective private function evaluation (SPFE). In this problem, a client inter-acts with one or more servers holding copies of a database z = zt,. . . , z, in order to compute f (z~t,. . . , z~, , , ), for some function f and indices i = it,. . . , i, ~ chosen by the client. Ideally, the client must learn nothing more about the database than f (zit,. . . , zi, , ~), and the servers should learn nothing. Generic solutions for this problem, based on standard techniques for secure function evaluation, incur communi-cation complexity that is at least linear in n, making them prohibitive for large databases even when f is relatively sim-ple and m is small. We present various approaches for con-structing sublinear-communication PFE protocols, both for the general problem and for special cases of interest. Our so-lutions not only offer sublinear communication complexity, but are also practical in many scenarios. 1.
Canetti et al. (Wed,) studied this question.