Delegating Computations with (almost) Minimal Time and Space Overhead

The problem of verifiable delegation of computation considers a setting in which a client wishes to outsource an expensive computation to a powerful, but untrusted, server. Since the client does not trust the server, we would like the server to certify the correctness of the result. Delegation has emerged as a central problem in cryptography, with a flurry of recent activity in both theory and practice. In all of these works, the main bottleneck is the overhead incurred by the server, both in time and in space. Assuming (sub-exponential) LWE, we construct a one-round argument-system for proving the correctness of any time $T$ and space $S$ RAM computation, in which both the verifier and prover are highly efficient. The verifier runs in time $n \cdot polylog(T)$ and space $polylog(T)$, where $n$ is the input length. Assuming $S \geq \max(n,polylog(T))$, the prover runs in time $\tilde{O}(T)$ and space $S + o(S)$, and in many natural cases even $S+polylog(T)$. Our solution uses somewhat homomorphic encryption but, surprisingly, only requires homomorphic evaluation of arithmetic circuits having multiplicative depth (which is a main bottleneck in homomorphic encryption) $\log_2\log(T)+O(1)$. Prior works based on standard assumptions had a $T^c$ time prover, where $c \geq 3$ (at the very least). As for the space usage, we are unaware of any work, even based on non-standard assumptions, that has space usage $S+polylog(T)$. Along the way to constructing our delegation scheme, we introduce several technical tools that we believe may be useful for future work

Computationally-Secure and Composable Remote State Preparation

We introduce a protocol between a classical polynomial-time verifier and a quantum polynomial-time prover that allows the verifier to securely delegate to the prover the preparation of certain single-qubit quantum states The prover is unaware of which state he received and moreover, the verifier can check with high confidence whether the preparation was successful. The delegated preparation of single-qubit states is an elementary building block in many quantum cryptographic protocols. We expect our implementation of "random remote state preparation with verification", a functionality first defined in (Dunjko and Kashefi 2014), to be useful for removing the need for quantum communication in such protocols while keeping functionality. The main application that we detail is to a protocol for blind and verifiable delegated quantum computation (DQC) that builds on the work of (Fitzsimons and Kashefi 2018), who provided such a protocol with quantum communication. Recently, both blind an verifiable DQC were shown to be possible, under computational assumptions, with a classical polynomial-time client (Mahadev 2017, Mahadev 2018). Compared to the work of Mahadev, our protocol is more modular, applies to the measurement-based model of computation (instead of the Hamiltonian model) and is composable. Our proof of security builds on ideas introduced in (Brakerski et al. 2018)

Computationally-Secure and Composable Remote State Preparation

We introduce a protocol between a classical polynomial-time verifier and a quantum polynomial-time prover that allows the verifier to securely delegate to the prover the preparation of certain single-qubit quantum states The prover is unaware of which state he received and moreover, the verifier can check with high confidence whether the preparation was successful. The delegated preparation of single-qubit states is an elementary building block in many quantum cryptographic protocols. We expect our implementation of "random remote state preparation with verification", a functionality first defined in (Dunjko and Kashefi 2014), to be useful for removing the need for quantum communication in such protocols while keeping functionality. The main application that we detail is to a protocol for blind and verifiable delegated quantum computation (DQC) that builds on the work of (Fitzsimons and Kashefi 2018), who provided such a protocol with quantum communication. Recently, both blind an verifiable DQC were shown to be possible, under computational assumptions, with a classical polynomial-time client (Mahadev 2017, Mahadev 2018). Compared to the work of Mahadev, our protocol is more modular, applies to the measurement-based model of computation (instead of the Hamiltonian model) and is composable. Our proof of security builds on ideas introduced in (Brakerski et al. 2018)

Modular Sumcheck Proofs with Applications to Machine Learning and Image Processing

Cryptographic proof systems provide integrity, fairness, and privacy in applications that outsource data processing tasks. However, general-purpose proof systems do not scale well to large inputs. At the same time, ad-hoc solutions for concrete applications - e.g., machine learning or image processing - are more efficient but lack modularity, hence they are hard to extend or to compose with other tools of a data-processing pipeline. In this paper, we combine the performance of tailored solutions with the versatility of general-purpose proof systems. We do so by introducing a modular framework for verifiable computation of sequential operations. The main tool of our framework is a new information-theoretic primitive called Verifiable Evaluation Scheme on Fingerprinted Data (VE) that captures the properties of diverse sumcheck-based interactive proofs, including the well-established GKR protocol. Thus, we show how to compose VEs for specific functions to obtain verifiability of a data-processing pipeline. We propose a novel VE for convolution operations that can handle multiple input-output channels and batching, and we use it in our framework to build proofs for (convolutional) neural networks and image processing. We realize a prototype implementation of our proof systems, and show that we achieve up to $5 \times$ faster proving time and $10 \times$ shorter proofs compared to the state-of-the-art, in addition to asymptotic improvements

On Black-Box Constructions of Time and Space Efficient Sublinear Arguments from Symmetric-Key Primitives

Zero-knowledge proofs allow a prover to convince a verifier of a statement without revealing anything besides its validity. A major bottleneck in scaling sub-linear zero-knowledge proofs is the high space requirement of the prover, even for NP relations that can be verified in a small space. In this work, we ask whether there exist complexity-preserving (i.e. overhead w.r.t time and space are minimal) succinct zero-knowledge arguments of knowledge with minimal assumptions while making only black-box access to the underlying primitives. We design the first such zero-knowledge system with sublinear communication complexity (when the underlying $\textsf{NP}$ relation uses non-trivial space) and provide evidence why existing techniques are unlikely to improve the communication complexity in this setting. Namely, for every NP relation that can be verified in time T and space S by a RAM program, we construct a public-coin zero-knowledge argument system that is black-box based on collision-resistant hash-functions (CRH) where the prover runs in time $\widetilde{O}(T)$ and space $\widetilde{O}(S)$, the verifier runs in time $\widetilde{O}(T/S+S)$ and space $\widetilde{O}(1)$ and the communication is $\widetilde{O}(T/S)$, where $\widetilde{O}()$ ignores polynomial factors in $\log T$ and $\kappa$ is the security parameter. As our construction is public-coin, we can apply the Fiat-Shamir heuristic to make it non-interactive with sample communication/computation complexities. Furthermore, we give evidence that reducing the proof length below $\widetilde{O}(T/S)$ will be hard using existing symmetric-key based techniques by arguing the space-complexity of constant-distance error correcting codes