CryptoDB
Surya Mathialagan
Publications and invited talks
Year
Venue
Title
2025
CRYPTO
Simple and General Counterexamples to Private-Coin Evasive LWE
Abstract
We present a simple counterexample to all known variants of the private-coin evasive learning with errors (LWE) assumption. Unlike prior works, our counterexample is direct, it does not use heavy cryptographic machinery (such as obfuscation or witness encryption), and it applies to \emph{all variants} of the assumption. Our counterexample can be seen as a "zeroizing" attack against evasive LWE, calling into question the soundness of the underlying design philosophy.
2025
CRYPTO
Pseudorandom Obfuscation and Applications
Abstract
We introduce the notion of \emph{pseudorandom obfuscation}, a way to obfuscate (keyed) pseudorandom functions $f_K$ in an average-case sense. We study several variants of pseudorandom obfuscation and show a number of applications.
\begin{enumerate}
\item \textbf{Applications in the iO World:} Our weakest variant of pseudorandom obfuscation, named obfuscation for identical pseudorandom functions (iPRO), is weaker than indistinguishability obfuscation (iO): rather than obfuscating arbitrary circuits as in iO, iPRO only obfuscates circuits computing pseudorandom functions. We show that iPRO already enables several applications of iO, such as unleveled fully homomorphic encryption (without assuming circular security) and succinct randomized encodings.
\item \textbf{From iPRO to iO:} Despite being a weaker notion than iO, we show two transformations from iPRO to iO. Our first (and main) construction builds iO from iPRO plus standard assumptions on cryptographic bilinear maps. Our second construction builds iO, and even ideal obfuscation, from iPRO alone in the pseudorandom oracle model (Jain, Lin, Luo and Wichs, CRYPTO 2023).
\end{enumerate}
We also formulate stronger variants of pseudorandom obfuscation that help us go beyond the applications of indistinguishability obfuscation.
\begin{enumerate}
\setItemnumber{3}
\item \textbf{Applications outside the iO World:} We show how to construct a succinct witness encryption scheme from a strong version of PRO, where the size of the ciphertext is independent of the witness size. Such a witness encryption scheme is not known to exist even assuming iO.
\item \textbf{Construction:} We show a {\em heuristic} construction of the strongest version of PRO, secure under the sub-exponential hardness of the learning with errors (LWE) problem, and the private-coin evasive LWE heuristic (Wee, EUROCRYPT 2022; Tsabary, CRYPTO 2022).
\end{enumerate}
\noindent
Finally, we highlight some barriers in achieving the strongest version of pseudorandom obfuscation.
2025
CRYPTO
Incrementally Verifiable Computation for NP from Standard Assumptions
Abstract
Incrementally verifiable computation (IVC) [Valiant, TCC'08] allows one to iteratively prove that a configuration $x_0$ reaches another configuration $x_T$ after repeated applications of a (possibly non-deterministic) transition function $\mathcal{M}$. The key requirement is that the size of the proof and the time to update the proof is sublinear in the number of steps $T$. IVC has numerous applications such as proving correctness of virtual machine executions in blockchains.
Currently, IVC for $\mathsf{NP}$ is only known to exist in idealized models, or based on knowledge assumptions. No constructions are known from standard assumptions, or even in the random oracle model. Furthermore, as observed in prior works, since IVC for $\mathsf{NP}$ implies adaptive succinct non-interactive arguments for $\mathsf{NP}$, the work of Gentry-Wichs [STOC `11] seemingly poses barriers to constructing IVC for $\mathsf{NP}$ from falsifiable assumptions.
In this work, we observe that the Gentry-Wichs barrier can be overcome for IVC for NP. We show the following two results:
* Assuming subexponential $i\mathcal{O}$ and LWE (or bilinear maps), we construct IVC for all $\mathsf{NP}$ with proof size $\mathsf{poly}(|x_i|,\log T)$.
* Assuming subexponential $i\mathcal{O}$ and injective PRGs, we construct IVC for \emph{trapdoor IVC languages} where the proof-size is $\mathsf{poly}(\log T)$. Informally, an IVC language has a trapdoor if there {\em exists} a (not necessarily easy to find) polynomial-sized circuit that determines if a configuration $x_i$ is reachable from $x_0$ in $i$ steps.
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
- Pedro Branco (1)
- Pratish Datta (1)
- Nico Döttling (2)
- Abhishek Jain (3)
- Zhengzhong Jin (1)
- Alexis Korb (1)
- Giulio Malavolta (2)
- Surya Mathialagan (6)
- Spencer Peters (2)
- Amit Sahai (1)
- Neekon Vafa (1)
- Vinod Vaikuntanathan (3)