article · 2016
L.: Constant-round private function evaluation with linear complexity
Jonathan Katz, Lior Malka
Cited by 0Abstract and details only
Abstract
Abstract. We consider the problem of private function evaluation (PFE) in the two-party setting. Here, informally, one party holds an input x while the other holds a (circuit describing a) function f; the goal is for one (or both) of the parties to learn f(x) while revealing nothing more to either party. In contrast to the usual setting of secure computation, where the function being computed is known to both parties, PFE is useful in settings where the function (i.e., algorithm) itself must remain secret, e.g., because it is proprietary or classified. It is known that PFE can be reduced to standard secure computa-tion by having the parties evaluate a universal circuit, and this is the approach taken in most prior work. Using a universal circuit, however, introduces additional overhead and results in a more complex imple-mentation. We show here a completely new technique for PFE that avoids universal circuits, and results in constant-round protocols with communication/computational complexity linear in the size of the cir-cuit computing f. This gives the first constant-round protocol for PFE with linear complexity (without using fully homomorphic encryption), even restricted to semi-honest adversaries. 1
Cite this paper
Katz, J., & Malka, L. (2016). L.: Constant-round private function evaluation with linear complexity.
Katz, Jonathan, and Lior Malka. “L.: Constant-round private function evaluation with linear complexity.” 2016.
Katz, Jonathan, and Lior Malka. 2016. “L.: Constant-round private function evaluation with linear complexity.”
Katz, J. and Malka, L. (2016) ‘L.: Constant-round private function evaluation with linear complexity’.
@article{katz2016constant,
title = {{L.: Constant-round private function evaluation with linear complexity}},
author = {Katz, Jonathan and Malka, Lior},
year = {2016}
}Made from the index record. Check names, capitalisation and page numbers against the paper. Need another style? AI for Research has over 10,000.