## CryptoDB

### Surya Mathialagan

#### Publications

**Year**

**Venue**

**Title**

2024

CRYPTO

Adaptively Sound Zero Knowledge SNARKs for UP
Abstract

We study succinct non-interactive arguments (SNARGs) and succinct non-interactive arguments of knowledge (SNARKs) for the class $\mathsf{UP}$ in the reusable designated verifier model. $\mathsf{UP}$ is an expressive subclass of $\mathsf{NP}$ consisting of all $\mathsf{NP}$ languages where each instance has at most one witness; a designated verifier SNARG (dvSNARG) is one where verification of the SNARG proof requires a private verification key; and such a dvSNARG is reusable if soundness holds even against a malicious prover with oracle access to the (private) verification algorithm.
Our main results are as follows.
(1) A reusably and adaptively sound zero-knowledge (zk) dvSNARG for $\mathsf{UP}$, from subexponential LWE and evasive LWE (a relatively new but popular variant of LWE). Our SNARGs achieve very short proofs of length $(1 + o(1)) \cdot \lambda$ bits for $2^{-\lambda}$ soundness error.
(2) A generic transformation that lifts any ``Sahai-Waters-like'' (zk) SNARG to an adaptively sound (zk) SNARG, in the \emph{designated-verifier} setting. In particular, this shows that the Sahai-Waters SNARG for $\mathsf{NP}$ is adaptively sound in the designated verifier setting, assuming subexponential hardness of the underlying assumptions. The resulting SNARG proofs have length $(1 + o(1)) \cdot \lambda$ bits for $2^{-\lambda}$ soundness error. Our result sidesteps the Gentry-Wichs barrier for adaptive soundness by employing an exponential-time security reduction.
(3) A generic transformation that lifts any adaptively sound (zk) SNARG for $\mathsf{UP}$ to an adaptively sound (zk) SNARK for $\mathsf{UP}$, while preserving zero-knowledge. The resulting SNARK achieves the strong notion of black-box extraction. There are barriers to achieving such SNARKs for all of $\mathsf{NP}$ from falsifiable assumptions, so our restriction to $\mathsf{UP}$ is, in a sense, necessary.
Applying (3) to our SNARG for $\mathsf{UP}$ from evasive LWE (1), we obtain a reusably and adaptively sound designated-verifier zero-knowledge SNARK for $\mathsf{UP}$ from subexponential LWE and evasive LWE. Moreover, applying both (2) and (3) to the Sahai-Waters SNARG, we obtain the same result from LWE, subexponentially secure one-way functions, and subexponentially secure indistinguishability obfuscation. Both constructions have succinct proofs of size $\mathsf{poly}(\secp).$ These are the first SNARK constructions (even in the designated-verifier setting) for a non-trivial subset of $\mathsf{NP}$ from (sub-exponentially) falsifiable assumptions.

2023

CRYPTO

MacORAMa: Optimal Oblivious RAM with Integrity
Abstract

Oblivious RAM (ORAM), introduced by Goldreich and Ostrovsky (J. ACM `96), is a primitive that allows a client to perform RAM computations on an external database without revealing any information through the access pattern. For a database of size $N$, well-known lower bounds show that a multiplicative overhead of $\Omega(\log N)$ in the number of RAM queries is necessary assuming $O(1)$ client storage. A long sequence of works culminated in the asymptotically optimal construction of Asharov, Komargodski, Lin, and Shi (CRYPTO `21) with $O(\log N)$ worst-case overhead and $O(1)$ client storage. However, this optimal ORAM is known to be secure only in the \emph{honest-but-curious} setting, where an adversary is allowed to observe the access patterns but not modify the contents of the database. In the \emph{malicious} setting, where an adversary is additionally allowed to tamper with the database, this construction and many others in fact become insecure.
In this work, we construct the first maliciously secure ORAM with worst-case $O(\log N)$ overhead and $O(1)$ client storage assuming one-way functions, which are also necessary. By the $\Omega(\log N)$ lower bound, our construction is asymptotically optimal. To attain this overhead, we develop techniques to intricately interleave online and offline memory checking for malicious security. Furthermore, we complement our positive result by showing the impossibility of a \emph{generic} overhead-preserving compiler from honest-but-curious to malicious security, barring a breakthrough in memory checking.

2023

TCC

Memory Checking for Parallel RAMs
★
Abstract

When outsourcing a database to an untrusted remote server, one might want to verify the integrity of contents while accessing it. To solve this, Blum et al. [FOCS `91] propose the notion of \emph{memory checking}. Memory checking allows a user to run a RAM program on a remote server, with the ability to verify integrity of the storage with small private storage.
In this work, we define and initiate the formal study of memory checking for \emph{Parallel RAMs} (PRAMs). The parallel RAM model is very expressive and captures many modern architectures such as multi-core architectures and cloud clusters. When multiple clients run a PRAM algorithm on a shared remote server, it is possible that there are concurrency issues that cause inconsistencies. Therefore, integrity verification is also a desirable property in this setting.
We construct an online memory checker (one that reports faults as soon as they occur) for PRAMs with $O(\log N)$ simulation overhead in both work and depth. Moreover, we construct an offline memory checker (one that reports faults only after a long sequence of operations) with amortized $O(1)$ simulation overhead in both work and depth. As an application of our parallel memory checking constructions, we construct a \emph{maliciously secure oblivious parallel RAM} (OPRAM) with polylogarithmic overhead.

#### Coauthors

- Surya Mathialagan (3)
- Spencer Peters (1)
- Neekon Vafa (1)
- Vinod Vaikuntanathan (1)