## CryptoDB

### Guy N. Rothblum

#### Publications

Year
Venue
Title
2020
TCC
A statistical zero-knowledge proof (SZK) for a problem $\Pi$ enables a computationally unbounded prover to convince a polynomial-time verifier that $x \in \Pi$ without revealing any additional information about $x$ to the verifier, in a strong information-theoretic sense. Suppose, however, that the prover wishes to convince the verifier that $k$ separate inputs $x_1,\dots,x_k$ all belong to $\Pi$ (without revealing anything else). A naive way of doing so is to simply run the SZK protocol separately for each input. In this work we ask whether one can do better -- that is, is efficient batch verification possible for SZK? We give a partial positive answer to this question by constructing a batch verification protocol for a natural and important subclass of SZK -- all problems $\Pi$ that have a non-interactive SZK protocol (in the common random string model). More specifically, we show that, for every such problem $\Pi$, there exists an honest-verifier SZK protocol for batch verification of $k$ instances, with communication complexity $poly(n) + k \cdot poly(\log{n},\log{k})$, where $poly$ refers to a fixed polynomial that depends only on $\Pi$ (and not on $k$). This result should be contrasted with the naive solution, which has communication complexity $k \cdot poly(n)$. Our proof leverages a new NISZK-complete problem, called Approximate Injectivity, that we find to be of independent interest. The goal in this problem is to distinguish circuits that are nearly injective, from those that are non-injective on almost all inputs.
2020
TCC
Suppose Alice wants to convince Bob of the correctness of k NP statements. Alice could send k witnesses to Bob, but as k grows the communication becomes prohibitive. Is it possible to convince Bob using smaller communication (without making cryptographic assumptions or bounding the computational power of a malicious Alive)? This is the question of batch verification for NP statements. Our main result is a new interactive proof protocol for verifying the correctness of k UP statements (NP statements with a unique witness) using communication that is poly-logarithmic in k (and a fixed polynomial in the length of a single witness). This result is obtained by making progress on a different question in the study of interactive proofs. Suppose Alice wants to convince Bob that a huge dataset has some property. Can this be done if Bob can't even read the entire input? In other words, what properties can be verified in sublinear time? An Interactive Proof of Proximity guarantees that Bob accepts if the input has the property, and rejects if the input is far (say in Hamming distance) from having the property. Two central complexity measures of such a protocol are the query and communication complexities (which should both be sublinear). For every query parameter $q$, and for every language in logspace uniform NC, we construct an interactive proof of proximity with query complexity $q$ and communication complexity $(n/q) \cdot \polylog(n)$. Both results are optimal up to poly-logarithmic factors, under reasonable complexity-theoretic or cryptographic assumptions. The second result, which is our main technical contribution, builds on a distance amplification technique introduced in a beautiful recent work of Ben-Sasson, Kopparty and Saraf [CCC 2018].
2019
TCC
If I commission a long computation, how can I check that the result is correct without re-doing the computation myself? This is the question that efficient verifiable computation deals with. In this work, we address the issue of verifying the computation as it unfolds. That is, at any intermediate point in the computation, I would like to see a proof that the current state is correct. Ideally, these proofs should be short, non-interactive, and easy to verify. In addition, the proof at each step should be generated efficiently by updating the previous proof, without recomputing the entire proof from scratch. This notion, known as incrementally verifiable computation, was introduced by Valiant [TCC 08] about a decade ago. Existing solutions follow the approach of recursive proof composition and can be based on strong and non-falsifiable cryptographic assumptions (so-called “knowledge assumptions”).In this work, we present a new framework for constructing incrementally verifiable computation schemes in both the publicly verifiable and designated-verifier settings. Our designated-verifier scheme is based on somewhat homomorphic encryption (which can be based on Learning with Errors) and our publicly verifiable scheme is based on the notion of zero-testable homomorphic encryption, which can be constructed from ideal multi-linear maps [Paneth and Rothblum, TCC 17].Our framework is anchored around the new notion of a probabilistically checkable proof (PCP) with incremental local updates. An incrementally updatable PCP proves the correctness of an ongoing computation, where after each computation step, the value of every symbol can be updated locally without reading any other symbol. This update results in a new PCP for the correctness of the next step in the computation. Our primary technical contribution is constructing such an incrementally updatable PCP. We show how to combine updatable PCPs with recently suggested (ordinary) verifiable computation to obtain our results.
2017
CRYPTO
2017
TCC
2017
JOFC
2016
CRYPTO
2015
ASIACRYPT
2014
TCC
2014
JOFC
2013
CRYPTO
2012
CRYPTO
2011
ASIACRYPT
2011
JOFC
2010
TCC
2010
TCC
2010
CRYPTO
2009
TCC
2009
TCC
2008
CRYPTO
2007
TCC
2007
TCC
2006
EPRINT
Suppose you want to store a large file on a remote and unreliable server. You would like to verify that your file has not been corrupted, so you store a small private (randomized)fingerprint'' of the file on your own computer. This is the setting for the well-studied authentication problem, and the size of the required private fingerprint is well understood. We study the problem of sub-linear authentication: suppose you would like to encode and store your file in a way that allows you to verify that it has not been corrupted, but without reading all of it. If you only want to read t bits of the file, how large does the size s of the fingerprint need to be? We define this problem formally, and show a tight lower bound on the relationship between s and t when the adversary is not computationally bounded, namely: s x t= Omega(n) where n is the file size. This is an easier case of the online memory checking problem, introduced by Blum, Evans, Gemmel, Kannan and Naor in 1991, and hence the same (tight) lower bound applies also to this problem. It was previously shown that when the adversary is not computationally bounded, under the assumption that one-way functions exist, it is possible to construct much better online memory checkers and sub-linear authentication schemes. We show that the existence of one-way functions is also a necessary condition: even slightly breaking the s x t= Omega(n) lower bound in a computational setting implies the existence of one-way functions.

Eurocrypt 2019
TCC 2019
TCC 2017
TCC 2016
Crypto 2013
PKC 2011
TCC 2011