Towards a Classification of Non-interactive Computational Assumptions in Cyclic Groups

We study non-interactive computational intractability assumptions in prime-order cyclic groups. We focus on the broad class of computational assumptions which we call target assumptions where the adversary’s goal is to compute concrete group elements. Our analysis identifies two families of intractability assumptions, the q-Generalized Diffie-Hellman Exponent (q-GDHE) assumptions and the q-Simple Fractional (q-SFrac) assumptions (a natural generalization of the q-SDH assumption), that imply all other target assumptions. These two assumptions therefore serve as Uber assumptions that can underpin all the target assumptions where the adversary has to compute specific group elements. We also study the internal hierarchy among members of these two assumption families. We provide heuristic evidence that both families are necessary to cover the full class of target assumptions. We also prove that having (polynomially many times) access to an adversarial 1-GDHE oracle, which returns correct solutions with non-negligible probability, entails one to solve any instance of the Computational Diffie-Hellman (CDH) assumption. This proves equivalence between the CDH and 1-GDHE assumptions. The latter result is of independent interest. We generalize our results to the bilinear group setting. For the base groups, our results translate nicely and a similar structure of non-interactive computational assumptions emerges. We also identify Uber assumptions in the target group but this requires replacing the q-GDHE assumption with a more complicated assumption, which we call the bilinar gap assumption. Our analysis can assist both cryptanalysts and cryptographers. For cryptanalysts, we propose the q-GDHE and the q-SDH assumptions are the most natural and important targets for cryptanalysis in prime-order groups. For cryptographers, we believe our classification can aid the choice of assumptions underpinning cryptographic schemes and be used as a guide to minimize the overall attack surface that different assumptions expose

Snarky Signatures: Minimal Signatures of Knowledge from Simulation-Extractable SNARKs

We construct a pairing based simulation-extractable SNARK (SE-SNARK) that consists of only 3 group elements and has highly efficient verification. By formally linking SE-SNARKs to signatures of knowledge, we then obtain a succinct signature of knowledge consisting of only 3 group elements. SE-SNARKs enable a prover to give a proof that they know a witness to an instance in a manner which is: (1) succinct - proofs are short and verifier computation is small; (2) zero-knowledge - proofs do not reveal the witness; (3) simulation-extractable - it is only possible to prove instances to which you know a witness, even when you have already seen a number of simulated proofs. We also prove that any pairing based signature of knowledge or SE-NIZK argument must have at least 3 group elements and 2 verification equations. Since our constructions match these lower bounds, we have the smallest size signature of knowledge and the smallest size SE-SNARK possible

Practical Zero-Knowledge Arguments from Structured Reference Strings

Zero-knowledge proofs have become an important tool for addressing privacy and scalability concerns in cryptographic protocols. For zero-knowledge proofs used in blockchain applications, it is desirable to have small proof sizes and fast verification. Yet by design, existing constructions with these properties such as zk-SNARKs also have a secret trapdoor embedded in a relation dependent structured reference string (SRS). Knowledge of this trapdoor suffices to break the security of these proofs. The SRSs required by zero-knowledge proofs are usually constructed with multiparty computation protocols, but the resulting parameters are specific to each individual circuit. In this thesis, we propose a model for constructing zero-knowledge arguments (i.e. zero-knowledge proofs with computational soundness) in which the generation of the SRS is directly considered in the security analysis. In our model the same SRS can be used across multiple applications. Further, the model is updatable i.e. users can update the universal SRS and the SRS is considered secure provided at least one of these users is honest. We propose two zero-knowledge arguments with updatable and universal SRSs, as well as a third which is neither updatable nor universal, but which through similar techniques achieves simulation extractability. The proposed arguments are practical, with proof sizes never more than a constant number of group elements. Verification for two of our constructions consist of a small number of pairing operations. For our other construction, which has the desirable property of a linear sized updatable and universal SRS, we describe efficient batching techniques so that verification is fast in the amortised setting