1,579 research outputs found
From Fairness to Full Security in Multiparty Computation
In the setting of secure multiparty computation (MPC), a set of mutually distrusting parties wish to jointly compute a function, while guaranteeing the privacy of their inputs and the correctness of the output. An MPC protocol is called fully secure if no adversary can prevent the honest parties from obtaining their outputs. A protocol is called fair if an adversary can prematurely abort the computation, however, only before learning any new information.
We present highly efficient transformations from fair computations to fully secure computations, assuming the fraction of honest parties is constant (e.g., 1% of the parties are honest). Compared to previous transformations that require linear invocations (in the number of parties) of the fair computation, our transformations require super-logarithmic, and sometimes even super-constant, such invocations. The main idea is to delegate the computation to chosen random committees that invoke the fair computation. Apart from the benefit of uplifting security, the reduction in the number of parties is also useful, since only committee members are required to work, whereas the remaining parties simply listen to the computation over a broadcast channel.
One application of these transformations is a new -bias coin-flipping protocol, whose round complexity has a super-logarithmic dependency on the number of parties, improving over the protocol of Beimel, Omri, and Orlov (Crypto 2010) that has a linear dependency. A second application is a new fully secure protocol for computing the Boolean OR function, with a super-constant round complexity, improving over the protocol of Gordon and Katz (TCC 2009) whose round complexity is linear in the number of parties.
Finally, we show that our positive results are in a sense optimal, by proving that for some functionalities, a super-constant number of (sequential) invocations of the fair computation is necessary for computing the functionality in a fully secure manner
Secure Multiparty Computation with Partial Fairness
A protocol for computing a functionality is secure if an adversary in this
protocol cannot cause more harm than in an ideal computation where parties give
their inputs to a trusted party which returns the output of the functionality
to all parties. In particular, in the ideal model such computation is fair --
all parties get the output. Cleve (STOC 1986) proved that, in general, fairness
is not possible without an honest majority. To overcome this impossibility,
Gordon and Katz (Eurocrypt 2010) suggested a relaxed definition -- 1/p-secure
computation -- which guarantees partial fairness. For two parties, they
construct 1/p-secure protocols for functionalities for which the size of either
their domain or their range is polynomial (in the security parameter). Gordon
and Katz ask whether their results can be extended to multiparty protocols.
We study 1/p-secure protocols in the multiparty setting for general
functionalities. Our main result is constructions of 1/p-secure protocols when
the number of parties is constant provided that less than 2/3 of the parties
are corrupt. Our protocols require that either (1) the functionality is
deterministic and the size of the domain is polynomial (in the security
parameter), or (2) the functionality can be randomized and the size of the
range is polynomial. If the size of the domain is constant and the
functionality is deterministic, then our protocol is efficient even when the
number of parties is O(log log n) (where n is the security parameter). On the
negative side, we show that when the number of parties is super-constant,
1/p-secure protocols are not possible when the size of the domain is
polynomial
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
Privacy-Preserving Trust Management Mechanisms from Private Matching Schemes
Cryptographic primitives are essential for constructing privacy-preserving
communication mechanisms. There are situations in which two parties that do not
know each other need to exchange sensitive information on the Internet. Trust
management mechanisms make use of digital credentials and certificates in order
to establish trust among these strangers. We address the problem of choosing
which credentials are exchanged. During this process, each party should learn
no information about the preferences of the other party other than strictly
required for trust establishment. We present a method to reach an agreement on
the credentials to be exchanged that preserves the privacy of the parties. Our
method is based on secure two-party computation protocols for set intersection.
Namely, it is constructed from private matching schemes.Comment: The material in this paper will be presented in part at the 8th DPM
International Workshop on Data Privacy Management (DPM 2013
Instantaneous Decentralized Poker
We present efficient protocols for amortized secure multiparty computation
with penalties and secure cash distribution, of which poker is a prime example.
Our protocols have an initial phase where the parties interact with a
cryptocurrency network, that then enables them to interact only among
themselves over the course of playing many poker games in which money changes
hands.
The high efficiency of our protocols is achieved by harnessing the power of
stateful contracts. Compared to the limited expressive power of Bitcoin
scripts, stateful contracts enable richer forms of interaction between standard
secure computation and a cryptocurrency.
We formalize the stateful contract model and the security notions that our
protocols accomplish, and provide proofs using the simulation paradigm.
Moreover, we provide a reference implementation in Ethereum/Solidity for the
stateful contracts that our protocols are based on.
We also adopt our off-chain cash distribution protocols to the special case
of stateful duplex micropayment channels, which are of independent interest. In
comparison to Bitcoin based payment channels, our duplex channel implementation
is more efficient and has additional features
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