## CryptoDB

### Ittai Abraham

#### Publications

**Year**

**Venue**

**Title**

2023

EUROCRYPT

Detect, Pack and Batch: Perfectly-Secure MPC with Linear Communication and Constant Expected Time
Abstract

We prove that perfectly-secure optimally-resilient secure Multi-Party Computation (MPC) for a circuit with $C$ gates and depth $D$ can be obtained in $O((Cn+n^4 + Dn^2)\log n)$ communication complexity and $O(D)$ expected time. For $D \ll n$ and $C\geq n^3$, this is the \textbf{first} perfectly-secure optimal-resilient MPC protocol with \textbf{linear} communication complexity per gate and \textbf{constant} expected time complexity per layer.
Compared to state-of-the-art MPC protocols in the player elimination framework [Beerliova and Hirt TCC'08, and Goyal, Liu, and Song CRYPTO'19], for $C>n^3$ and $D \ll n$, our results significantly improve the run time from $\Theta(n+D)$ to expected $O(D)$ while keeping communication complexity at $O(Cn\log n)$.
Compared to state-of-the-art MPC protocols that obtain an expected $O(D)$ time complexity [Abraham, Asharov, and Yanai TCC'21], for $C>n^3$, our results significantly improve the communication complexity from $O(Cn^4\log n)$ to $O(Cn\log n)$ while keeping the expected run time at $O(D)$.
One salient part of our technical contribution is centered around a new primitive we call \textit{detectable secret sharing}. It is perfectly-hiding, weakly-binding, and has the property that either reconstruction succeeds, or $O(n)$ parties are (privately) detected. On the one hand, we show that detectable secret sharing is sufficiently powerful to generate multiplication triplets needed for MPC. On the other hand, we show how to share $p$ secrets via detectable secret sharing with communication complexity of just $O(n^4\log n+p \log n)$. When sharing $p\geq n^4$ secrets, the communication cost is amortized to just $O(1)$ per secret.
Our second technical contribution is a new Verifiable Secret Sharing protocol that can share $p$ secrets at just $O(n^4\log n+pn\log n)$ word complexity. When sharing $p\geq n^3$ secrets, the communication cost is amortized to just $O(n)$ per secret. The best prior required $O(n^3)$ communication per secret.

2022

TCC

Asymptotically Free Broadcast in Constant Expected Time via Packed VSS
Abstract

Broadcast is an essential primitive for secure computation. We focus in this paper on optimal resilience (i.e., when the number of corrupted parties $t$ is less than a third of the computing parties $n$), and with no setup or cryptographic assumptions.
While broadcast with worst case $t$ rounds is impossible, it has been shown [Feldman and Micali STOC'88, Katz and Koo CRYPTO'06] how to construct protocols with expected constant number of rounds in the private channel model. However, those constructions have large communication complexity, specifically $\bigO(n^2L+n^6\log n)$ expected number of bits transmitted for broadcasting a message of length $L$. This leads to a significant communication blowup in secure computation protocols in this setting.
In this paper, we substantially improve the communication complexity of broadcast in constant expected time. Specifically, the expected communication complexity of our protocol is $\bigO(nL+n^4\log n)$. For messages of length $L=\Omega(n^3 \log n)$, our broadcast has no asymptotic overhead (up to expectation), as each party has to send or receive $\bigO(n^3 \log n)$ bits. We also consider parallel broadcast, where $n$ parties wish to broadcast $L$ bit messages in parallel. Our protocol has no asymptotic overhead for $L=\Omega(n^2\log n)$, which is a common communication pattern in perfectly secure MPC protocols. For instance, it is common that all parties share their inputs simultaneously at the same round, and verifiable secret sharing protocols require the dealer to broadcast a total of $\bigO(n^2\log n)$ bits.
As an independent interest, our broadcast is achieved by a \emph{packed verifiable secret sharing}, a new notion that we introduce. We show a protocol that verifies $\bigO(n)$ secrets simultaneously with the same cost of verifying just a single secret. This improves by a factor of $n$ the state-of-the-art.

2022

JOFC

Efficient Perfectly Secure Computation with Optimal Resilience
Abstract

Secure computation enables n mutually distrustful parties to compute a function over their private inputs jointly. In 1988, Ben-Or, Goldwasser, and Wigderson (BGW) proved that any function can be computed with perfect security in the presence of a malicious adversary corrupting at most $$t< n/3$$ t < n / 3 parties. After more than 30 years, protocols with perfect malicious security, and round complexity proportional to the circuit’s depth, still require (verifiably) sharing a total of $$O(n^2)$$ O ( n 2 ) values per multiplication. In contrast, only O ( n ) values need to be shared per multiplication to achieve semi-honest security. Sharing $$\Omega (n)$$ Ω ( n ) values for a single multiplication seems to be the natural barrier for polynomial secret-sharing-based multiplication. In this paper, we construct a new secure computation protocol with perfect, optimal resilience and malicious security that incurs (verifiably) sharing O ( n ) values per multiplication. Our protocol requires a constant number of rounds per multiplication. Like BGW, it has an overall round complexity that is proportional only to the multiplicative depth of the circuit. Our improvement is obtained by a novel construction for weak VSS for polynomials of degree 2t , which incurs the same communication and round complexities as the state-of-the-art constructions for VSS for polynomials of degree t . Our second contribution is a method for reducing the communication complexity for any depth 1 sub-circuit to be proportional only to the size of the input and output (rather than the size of the circuit). This implies protocols with sub-linear communication complexity (in the size of the circuit) for perfectly secure computation for important functions like matrix multiplication.

2021

TCC

Efficient Perfectly Secure Computation with Optimal Resilience
📺
Abstract

Secure computation enables $n$ mutually distrustful parties to compute a function over their private inputs jointly. In 1988 Ben-Or, Goldwasser, and Wigderson (BGW) demonstrated that any function can be computed with perfect security in the presence of a malicious adversary corrupting at most $t< n/3$ parties.
After more than 30 years, protocols with perfect malicious security, with round complexity proportional to the circuit's depth, still require sharing a total of $O(n^2)$ values per multiplication.
In contrast, only $O(n)$ values need to be shared per multiplication to achieve semi-honest security. Indeed sharing $\Omega(n)$ values for a single multiplication seems to be the natural barrier for polynomial secret sharing-based multiplication.
In this paper, we close this gap by constructing a new secure computation protocol with perfect, optimal resilience and malicious security that incurs sharing of only $O(n)$ values per multiplication, thus, matching the semi-honest setting for protocols with round complexity that is proportional to the circuit depth. Our protocol requires a constant number of rounds per multiplication. Like BGW, it has an overall round complexity that is proportional only to the multiplicative depth of the circuit.
Our improvement is obtained by a novel construction for {\em weak VSS for polynomials of degree-$2t$}, which incurs the same communication and round complexities as the state-of-the-art constructions for {\em VSS for polynomials of degree-$t$}.
Our second contribution is a method for reducing the communication complexity for any depth-1 sub-circuit to be proportional only to the size of the input and output (rather than the size of the circuit). This implies protocols with \emph{sublinear communication complexity} (in the size of the circuit) for perfectly secure computation for important functions like matrix multiplication.

#### Program Committees

- TCC 2021

#### Coauthors

- Gilad Asharov (4)
- Danny Dolev (1)
- Christopher W. Fletcher (1)
- Joseph Y. Halpern (1)
- Kartik Nayak (1)
- Shravani Patil (2)
- Arpita Patra (2)
- Benny Pinkas (1)
- Ling Ren (1)
- Avishay Yanai (2)