Efficient Asynchronous Verifiable Secret Sharing and Multiparty Computation

Secure Multi-Party Computation (MPC) providing information theoretic security allows a set of n parties to securely compute an agreed function F over a finite field ${\mathbb F}$, even if t parties are under the control of a computationally unbounded active adversary. Asynchronous MPC (AMPC) is an important variant of MPC, which works over an asynchronous network. It is well known that perfect AMPC is possible if and only if n \geq 4t+1, while statistical AMPC is possible if and only if n \geq 3t+1. In this paper, we study the communication complexity of AMPC protocols (both statistical and perfect) designed with exactly n = 4t+1 parties. Our major contributions in this paper are as follows: 1. Asynchronous Verifiable Secret Sharing (AVSS) is one of the main building blocks for AMPC. In this paper, we design two AVSS protocols with 4t+1 parties: the first one is statistically secure and has non-optimal resilience, while the second one is perfectly secure and has optimal resilience. Both these schemes achieve a common interesting property, which was not achieved by the previous schemes. Specifically, our AVSS schemes allow to share a secret through a polynomial of degree at most d, where t \leq d \leq 2t. In contrast, the existing AVSS schemes can share a secret only through a polynomial of degree at most t. The new property of our AVSS simplifies the degree reduction step for the evaluation of multiplication gates in an AMPC protocol. 2.Using our statistical AVSS, we design a statistical AMPC protocol with n = 4t+1 which communicates O(n^2) field elements per multiplication gate. Though this protocol has non-optimal resilience, it significantly improves the communication complexity of the existing statistical AMPC protocols. 3. We then present a perfect AMPC protocol with n = 4t+1 (using our perfect AVSS scheme), which also communicates O(n^2) field elements per multiplication gate. This protocol improves on our statistical AMPC protocol as it has optimal resilience. To the best of our knowledge, this is the most communication efficient perfect AMPC protocol in the information theoretic setting

Efficient Statistical Asynchronous Verifiable Secret Sharing and Multiparty Computation with Optimal Resilience

Verifiable Secret Sharing (VSS) is a fundamental primitive used as a building block in many distributed cryptographic tasks, such as Secure Multiparty Computation (MPC) and Byzantine Agreement (BA). An important variant of VSS is Asynchronous VSS (AVSS) which is designed to work over asynchronous networks. AVSS is a two phase (Sharing, Reconstruction) protocol carried out among n parties in the presence of a computationally unbounded active adversary, who can corrupt up to t parties. We assume that every two parties in the network are directly connected by a pairwise secure channel. In this paper, we present a new statistical AVSS protocol with optimal resilience; i.e. with n = 3t+1. Our protocol privately communicates O((\ell n^3 + n^4 \log{\frac{1}{\epsilon}}) \log{\frac{1}{\epsilon}}) bits and A-casts O(n^3 \log(n)) bits to simultaneously share \ell \geq 1 elements from a finite field F, where \epsilon is the error parameter of our protocol. There are only two known statistical AVSS protocols with n = 3t+1 reported in [CR93] and [PCR09]. The AVSS protocol of [CR93] requires a private communication of O(n^9 (\log{\frac{1}{\epsilon}})^4) bits and A-cast of O(n^9 (\log{\frac{1}{\epsilon}})^2 \log(n)) bits to share a single element from F. Thus our AVSS protocol shows a significant improvement in communication complexity over the AVSS of [CR93]. The AVSS protocol of [PCR09] requires a private communication and A-cast of O((\ell n^3 + n^4) \log{\frac{1}{\epsilon}}) bits to share \ell \geq 1 elements. However, the shared element(s) may be NULL \not \in {\mathbb F}. Thus our AVSS is better than the AVSS of [PCR09] due to the following reasons: 1. The A-cast communication of our AVSS is independent of the number of secrets i.e. \ell; 2. Our AVSS makes sure that the shared value(s) always belong to F. Using our AVSS, we design a new primitive called Asynchronous Complete Secret Sharing (ACSS) which acts as an important building block of asynchronous multiparty computation (AMPC). Using our ACSS scheme, we design a statistical AMPC protocol with optimal resilience; i.e., with n = 3t+1, that privately communicates O(n^5 \log{\frac{1}{\epsilon}}) bits per multiplication gate. This significantly improves the communication complexity of only known optimally resilient statistical AMPC of [BKR93] that privately communicates \Omega(n^{11} (\log{\frac{1}{\epsilon}})^4) bits and A-cast \Omega(n^{11} (\log{\frac{1}{\epsilon}})^2 \log(n)) bits per multiplication gate. Both our ACSS and AVSS employ several new techniques, which are of independent interest

Asynchronous Multi-Party Quantum Computation

Multi-party quantum computation (MPQC) allows a set of parties to securely compute a quantum circuit over private quantum data. Current MPQC protocols rely on the fact that the network is synchronous, i.e., messages sent are guaranteed to be delivered within a known fixed delay upper bound, and unfortunately completely break down even when only a single message arrives late. Motivated by real-world networks, the seminal work of Ben-Or, Canetti and Goldreich (STOC\u2793) initiated the study of multi-party computation for classical circuits over asynchronous networks, where the network delay can be arbitrary. In this work, we begin the study of asynchronous multi-party quantum computation (AMPQC) protocols, where the circuit to compute is quantum. Our results completely characterize the optimal achievable corruption threshold: we present an n-party AMPQC protocol secure up to t < n/4 corruptions, and an impossibility result when t ? n/4 parties are corrupted. Remarkably, this characterization differs from the analogous classical setting, where the optimal corruption threshold is t < n/3

The Crypto-democracy and the Trustworthy

In the current architecture of the Internet, there is a strong asymmetry in terms of power between the entities that gather and process personal data (e.g., major Internet companies, telecom operators, cloud providers, ...) and the individuals from which this personal data is issued. In particular, individuals have no choice but to blindly trust that these entities will respect their privacy and protect their personal data. In this position paper, we address this issue by proposing an utopian crypto-democracy model based on existing scientific achievements from the field of cryptography. More precisely, our main objective is to show that cryptographic primitives, including in particular secure multiparty computation, offer a practical solution to protect privacy while minimizing the trust assumptions. In the crypto-democracy envisioned, individuals do not have to trust a single physical entity with their personal data but rather their data is distributed among several institutions. Together these institutions form a virtual entity called the Trustworthy that is responsible for the storage of this data but which can also compute on it (provided first that all the institutions agree on this). Finally, we also propose a realistic proof-of-concept of the Trustworthy, in which the roles of institutions are played by universities. This proof-of-concept would have an important impact in demonstrating the possibilities offered by the crypto-democracy paradigm.Comment: DPM 201

ARPA Whitepaper

We propose a secure computation solution for blockchain networks. The correctness of computation is verifiable even under malicious majority condition using information-theoretic Message Authentication Code (MAC), and the privacy is preserved using Secret-Sharing. With state-of-the-art multiparty computation protocol and a layer2 solution, our privacy-preserving computation guarantees data security on blockchain, cryptographically, while reducing the heavy-lifting computation job to a few nodes. This breakthrough has several implications on the future of decentralized networks. First, secure computation can be used to support Private Smart Contracts, where consensus is reached without exposing the information in the public contract. Second, it enables data to be shared and used in trustless network, without disclosing the raw data during data-at-use, where data ownership and data usage is safely separated. Last but not least, computation and verification processes are separated, which can be perceived as computational sharding, this effectively makes the transaction processing speed linear to the number of participating nodes. Our objective is to deploy our secure computation network as an layer2 solution to any blockchain system. Smart Contracts\cite{smartcontract} will be used as bridge to link the blockchain and computation networks. Additionally, they will be used as verifier to ensure that outsourced computation is completed correctly. In order to achieve this, we first develop a general MPC network with advanced features, such as: 1) Secure Computation, 2) Off-chain Computation, 3) Verifiable Computation, and 4)Support dApps' needs like privacy-preserving data exchange