CRJan 28, 2022
Perfectly-Secure Synchronous MPC with Asynchronous Fallback GuaranteesAnanya Appan, Anirudh Chandramouli, Ashish Choudhury
Secure multi-party computation (MPC) is a fundamental problem in secure distributed computing. An MPC protocol allows a set of $n$ mutually distrusting parties to carry out any joint computation of their private inputs, without disclosing any additional information about their inputs. MPC with information-theoretic security provides the strongest security guarantees and remains secure even against computationally unbounded adversaries. Perfectly-secure MPC protocols is a class of information-theoretically secure MPC protocols, which provides all the security guarantees in an error-free fashion. The focus of this work is perfectly-secure MPC. Known protocols are designed assuming either a synchronous or asynchronous communication network. It is well known that perfectly-secure synchronous MPC protocol is possible as long as adversary can corrupt any $t_s < n/3$ parties. On the other hand, perfectly-secure asynchronous MPC protocol can tolerate up to $t_a < n/4$ corrupt parties. A natural question is does there exist a single MPC protocol for the setting where the parties are not aware of the exact network type and which can tolerate up to $t_s < n/3$ corruptions in a synchronous network and up to $t_a < n/4$ corruptions in an asynchronous network. We design such a best-of-both-worlds perfectly-secure MPC protocol, provided $3t_s + t_a < n$ holds. For designing our protocol, we design two important building blocks, which are of independent interest. The first building block is a best-of-both-worlds Byzantine agreement (BA) protocol tolerating $t < n/3$ corruptions and which remains secure, both in a synchronous as well as asynchronous network. The second building block is a polynomial-based best-of-both-worlds verifiable secret-sharing (VSS) protocol, which can tolerate up to $t_s$ and $t_a$ corruptions in a synchronous and in an asynchronous network respectively.
CRDec 21, 2021
A Survey on Perfectly-Secure Verifiable Secret-SharingAnirudh Chandramouli, Ashish Choudhury, Arpita Patra
Verifiable Secret-Sharing (VSS) is a fundamental primitive in secure distributed computing. It is used as a building block in several distributed computing tasks, such as Byzantine agreement and secure multi-party computation. In this article, we consider VSS schemes with perfect security, tolerating computationally unbounded adversaries. We comprehensively survey the existing perfectly-secure VSS schemes in three different communication settings, namely synchronous, asynchronous and hybrid setting and provide full details of the existing schemes in these settings. The aim of this survey is to provide a clear knowledge and foundation to researchers who are interested in knowing and extending the state-of-the-art perfectly-secure VSS schemes.
CRDec 5, 2019
ASTRA: High Throughput 3PC over Rings with Application to Secure PredictionHarsh Chaudhari, Ashish Choudhury, Arpita Patra et al.
The concrete efficiency of secure computation has been the focus of many recent works. In this work, we present concretely-efficient protocols for secure $3$-party computation (3PC) over a ring of integers modulo $2^{\ell}$ tolerating one corruption, both with semi-honest and malicious security. Owing to the fact that computation over ring emulates computation over the real-world system architectures, secure computation over ring has gained momentum of late. Cast in the offline-online paradigm, our constructions present the most efficient online phase in concrete terms. In the semi-honest setting, our protocol requires communication of $2$ ring elements per multiplication gate during the {\it online} phase, attaining a per-party cost of {\em less than one element}. This is achieved for the first time in the regime of 3PC. In the {\it malicious} setting, our protocol requires communication of $4$ elements per multiplication gate during the online phase, beating the state-of-the-art protocol by $5$ elements. Realized with both the security notions of selective abort and fairness, the malicious protocol with fairness involves slightly more communication than its counterpart with abort security for the output gates {\em alone}. We apply our techniques from $3$PC in the regime of secure server-aided machine-learning (ML) inference for a range of prediction functions-- linear regression, linear SVM regression, logistic regression, and linear SVM classification. Our setting considers a model-owner with trained model parameters and a client with a query, with the latter willing to learn the prediction of her query based on the model parameters of the former. The inputs and computation are outsourced to a set of three non-colluding servers. Our constructions catering to both semi-honest and the malicious world, invariably perform better than the existing constructions.