Simulation extractability is a strong security notion of zkSNARKs that guarantees that an attacker who produces a valid proof must know the corresponding witness, even if the attacker had prior access to proofs generated by other users. Notably, simulation extractability implies that proofs are non-malleable and is of fundamental importance for applications of zkSNARKs in distributed systems. In this work, we study sufficient and necessary conditions for constructing simulation-extractable universal zkSNARKs via the popular design approach based on compiling polynomial interactive oracle proofs (PIOP). Our main result is the first security proof that popular universal zkSNARKs, such as PLONK and Marlin, as deployed in the real world, are simulation-extractable. Our result fills a gap left from previous work (Faonio et al. TCC'23, and Kohlweiss et al. TCC'23) which could only prove the simulation extractability of the "textbook" versions of these schemes and does not capture their optimized variants, with all the popular optimization tricks in place, that are eventually implemented and deployed in software libraries.

We show that the most common flavors of noisy leakage can be simulated in the information-theoretic setting using a single query of bounded leakage, up to a small statistical simulation error and a slight loss in the leakage parameter. The latter holds true in particular for one of the most used noisy-leakage models, where the noisiness is measured using the conditional average min-entropy (Naor and Segev, CRYPTO’09 and SICOMP’12). Our reductions between noisy and bounded leakage are achieved in two steps. First, we put forward a new leakage model (dubbed the dense leakage model) and prove that dense leakage can be simulated in the information-theoretic setting using a single query of bounded leakage, up to small statistical distance. Second, we show that the most common noisy-leakage models fall within the class of dense leakage, with good parameters. Third, we prove lower bounds on the amount of bounded leakage required for simulation with sub-constant error, showing that our reductions are nearly optimal. In particular, our results imply that useful general simulation of noisy leakage based on statistical distance and mutual information is impossible. We also provide a complete picture of the relationships between different noisy-leakage models. Our result finds applications to leakage-resilient cryptography, where we are often able to lift security in the presence of bounded leakage to security in the presence of noisy leakage, both in the information-theoretic and in the computational setting. Remarkably, this lifting procedure makes only black-box use of the underlying schemes. Additionally, we show how to use lower bounds in communication complexity to prove that bounded-collusion protocols (Kumar, Meka, and Sahai, FOCS’19) for certain functions do not only require long transcripts, but also necessarily need to reveal enough information about the inputs.

We construct a new leakage-resilient signature scheme. Our scheme remains unforgeable in the noisy leakage model, where the only restriction on the leakage is that it does not decrease the min-entropy of the secret key by too much. The leakage information can depend on the entire state of the signer; this property is sometimes known as fully leakage resilience. An additional feature of our construction, is that it offers a graceful degradation of security in situations where standard existential unforgeability is impossible. This property was recently put forward by Nielsen et al. (PKC 2014) in the bounded leakage model, to deal with settings in which the secret key is much larger than the size of a signature. For security parameter $$\kappa $$ , our scheme tolerates leakage on the entire state of the signer until $$\omega (\log \kappa )$$ bits of min-entropy are left in the secret key, and is proven secure in the standard model. While we describe our scheme in terms of generic building blocks, we also explain how to instantiate it efficiently under fairly standard number-theoretic assumptions.