Paper 2013/377

An Algebraic Framework for Diffie-Hellman Assumptions

Alex Escala, Gottfried Herold, Eike Kiltz, Carla Ràfols, and Jorge Villar

Abstract

We put forward a new algebraic framework to generalize and analyze Diffie-Hellman like Decisional Assumptions which allows us to argue about security and applications by considering only algebraic properties. Our $D_{\ell,k}-MDDH$ assumption states that it is hard to decide whether a vector in $G^\ell$ is linearly dependent of the columns of some matrix in $G^{\ell\times k}$ sampled according to distribution $D_{\ell,k}$. It covers known assumptions such as $DDH$, $2-Lin$ (linear assumption), and $k-Lin$ (the $k$-linear assumption). Using our algebraic viewpoint, we can relate the generic hardness of our assumptions in $m$-linear groups to the irreducibility of certain polynomials which describe the output of $D_{\ell,k}$. We use the hardness results to find new distributions for which the $D_{\ell,k}-MDDH$-Assumption holds generically in $m$-linear groups. In particular, our new assumptions $2-SCasc$ and $2-ILin$ are generically hard in bilinear groups and, compared to $2-Lin$, have shorter description size, which is a relevant parameter for efficiency in many applications. These results support using our new assumptions as natural replacements for the $2-Lin$ Assumption which was already used in a large number of applications. To illustrate the conceptual advantages of our algebraic framework, we construct several fundamental primitives based on any $MDDH$-Assumption. In particular, we can give many instantiations of a primitive in a compact way, including public-key encryption, hash-proof systems, pseudo-random functions, and Groth-Sahai NIZK and NIWI proofs. As an independent contribution we give more efficient NIZK and NIWI proofs for membership in a subgroup of $G^\ell$, for validity of ciphertexts and for equality of plaintexts. The results imply very significant efficiency improvements for a large number of schemes, most notably Naor-Yung type of constructions.

Note: This version includes a new result on the uniqueness of any one-parameter Matrix DH Asuumption and some typographic corrections.