Paper 2024/1213

Bounded-Collusion Streaming Functional Encryption from Minimal Assumptions

Abstract

Streaming functional encryption (sFE), recently introduced by Guan, Korb, and Sahai [Crypto 2023], is an extension of functional encryption (FE) tailored for iterative computation on dynamic data streams. Unlike in regular FE, in an sFE scheme, users can encrypt and compute on the data as soon as it becomes available and in time proportional to just the size of the newly arrived data. As sFE implies regular FE, all known constructions of sFE and FE for $$ require strong cryptographic assumptions which are powerful enough to build indistinguishability obfuscation. In contrast, bounded-collusion FE, in which the adversary is restricted to making at most $$ function queries for some polynomial $$ determined at setup, can be built from the minimal assumptions of public-key encryption (for public-key FE) [Sahai and Seyalioglu, CCS 2010; Gorbunov, Vaikuntanathan, and Wee, CRYPTO 2012] and secret-key encryption (for secret-key FE)[Ananth, Vaikuntanathan, TCC 2019]. In this paper, we introduce and build bounded-collusion streaming FE for any polynomial bound $$ from the same minimal assumptions of public-key encryption (for public-key sFE) and secret-key encryption (for secret-key sFE). Similarly to the original sFE paper of Guan, Korb, and Sahai, our scheme satisfies semi-adaptive-function-selective security which is similar to standard adaptive indistinguishability-based security except that we require all functions to be queried before any of the challenge messages. Along the way, our work also replaces a key ingredient (called $$) from the original work of Guan, Korb, and Sahai with a much simpler construction based on garbled circuits.