David Wu (Stanford University)
Wednesday, 24.10.2018, 12:30
Pseudorandom functions (PRFs) are one of the fundamental building blocks in cryptography. Traditionally, there have been two main approaches for PRF design: the "practitioner's approach" of building concretely-efficient constructions based on known heuristics and prior experience, and the "theoretician's approach" of proposing constructions and reducing their security to a previously-studied hardness assumption. While both approaches have their merits, the resulting PRF candidates vary greatly in terms of concrete efficiency and design complexity. In this work, we depart from these traditional approaches by exploring a new space of plausible PRF candidates. Our guiding principle is to maximize simplicity while optimizing complexity measures that are relevant to cryptographic applications. Our primary focus is on weak PRFs computable by very simple circuits--specifically, depth-2 ACC^0 circuits. Concretely, our main weak PRF candidate is a "piecewise-linear" function that first applies a secret mod-2 linear mapping to the input, and then a public mod-3 linear mapping to the result. We also put forward a similar depth-3 strong PRF candidate. The advantage of our approach is twofold. On the theoretical side, the simplicity of our candidates enables us to draw many natural connections between their hardness and questions in complexity theory or learning theory. On the applied side, the piecewise-linear structure of our candidates lends itself nicely to applications in secure multiparty computation (MPC). In this talk, I will introduce our new PRF candidates and highlight some of the connections between our candidates and questions in complexity theory, learning theory, and MPC.
Joint work with Dan Boneh, Yuval Ishai, Alain Passelègue, and Amit Sahai.