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Fast Byzantine agreement
 In PODC
, 2013
"... is paper presents the first probabilistic Byzantine Agreement algorithmwhose communication and time complexities are polylogarithmic. So far, the most effective probabilistic Byzantine Agreement algorithm had communication complexity Õ p n and time complexity O ̃ (1). Our algorithm is based on a ..."
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is paper presents the first probabilistic Byzantine Agreement algorithmwhose communication and time complexities are polylogarithmic. So far, the most effective probabilistic Byzantine Agreement algorithm had communication complexity Õ p n and time complexity O ̃ (1). Our algorithm is based on a novel, unbalanced, almost everywhere to everywhere Agreement protocol which is interesting in its own right.
Quorums Quicken Queries: Efficient Asynchronous Secure Multiparty Computation
"... We describe an asynchronous algorithm to solve secure multiparty computation (MPC) over n players, when strictly less than a 1/8 fraction of the players are controlled by a static adversary. For any function f that can be computed by a circuit with m gates, our algorithm requires each n+m player to ..."
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Cited by 4 (3 self)
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We describe an asynchronous algorithm to solve secure multiparty computation (MPC) over n players, when strictly less than a 1/8 fraction of the players are controlled by a static adversary. For any function f that can be computed by a circuit with m gates, our algorithm requires each n+m player to send a number of bits and perform an amount of computation that is Õ( n + √ n). This significantly improves over traditional algorithms, which require each player to both send a number of messages and perform computation that is Ω(nm). Contact: Varsha Dani,
Breaking the O(nm) Bit Barrier: Secure Multiparty Computation with a Static Adversary
"... We describe scalable algorithms for secure multiparty computation (SMPC). We assume a synchronous message passing communication model, but unlike most related work, we do not assume the existence of a broadcast channel. Our main result holds for the case where there are n players, of which a 1/3 − ɛ ..."
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Cited by 3 (1 self)
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We describe scalable algorithms for secure multiparty computation (SMPC). We assume a synchronous message passing communication model, but unlike most related work, we do not assume the existence of a broadcast channel. Our main result holds for the case where there are n players, of which a 1/3 − ɛ fraction are controlled by an adversary, for ɛ any positive constant. We describe a SMPC algorithm for this model that requires each player to send Õ ( n+m n + √ n+m n) messages and perform Õ( n + √ n) computations to compute any function f, where m is the size of a circuit to compute f. We also consider a model where all players are selfish but rational. In this model, we describe a Nash equilibrium protocol that solve SMPC n+m n+m
SelfHealing of Byzantine Faults
"... Recent years have seen significant interest in designing networks that are selfhealing in the sense that they can automatically recover from adversarial attack. Previous work shows that it is possible for a network to automatically recover, even when an adversary repeatedly deletes nodes in the net ..."
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Recent years have seen significant interest in designing networks that are selfhealing in the sense that they can automatically recover from adversarial attack. Previous work shows that it is possible for a network to automatically recover, even when an adversary repeatedly deletes nodes in the network. However, there have not yet been any algorithms that selfheal in the case where an adversary takes over nodes. In this paper, we address this gap. In particular, we describe a communication network over n nodes that ensures the following properties, even when an adversary controls up to t ≤ (1/4 − ɛ)n nodes, for any positive ɛ. First, the network provides pointtopoint communication with bandwidth and latency costs that are asymptotically optimal. Second, O(t(log ∗ n) 2) message corruptions occur in expectation, before the adversarially controlled nodes are effectively quarantined so that they cause no more corruptions. We present empirical results showing that our approach may be practical. “Fool me once, shame on you. Fool me twice, shame on me. ” English proverb 1
SelfHealing Computation?
"... Abstract. In the problem of reliable multiparty computation (RC), there are n parties, each with an individual input, and the parties want to jointly compute a function f over n inputs. The problem is complicated by the fact that an omniscient adversary controls a hidden fraction of the parties. We ..."
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Abstract. In the problem of reliable multiparty computation (RC), there are n parties, each with an individual input, and the parties want to jointly compute a function f over n inputs. The problem is complicated by the fact that an omniscient adversary controls a hidden fraction of the parties. We describe a selfhealing algorithm for this problem. In particular, for a fixed function f, with n parties and m gates, we describe how to perform RC repeatedly as the inputs to f change. Our algorithm maintains the following properties, even when an adversary controls up to t ≤ ( 1 4 − )n parties, for any constant > 0. First, our algorithm performs each reliable computation with the following amortized resource costs: O(m+ n logn) messages, O(m+ n logn) computational operations, and O(`) latency, where ` is the depth of the circuit that computes f. Second, the expected total number of corruptions is O(t(log∗m)2), after which the adversarially controlled parties are effectively quarantined so that they cause no more corruptions.
Secure Location Sharing
"... In the last decade, the number of locationaware mobile devices has mushroomed. Just as locationbased services grow fast, they lay out many questions and challenges when it comes to privacy. For example, who owns the location data and for what purpose is the data used? To answer these questions, we ..."
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In the last decade, the number of locationaware mobile devices has mushroomed. Just as locationbased services grow fast, they lay out many questions and challenges when it comes to privacy. For example, who owns the location data and for what purpose is the data used? To answer these questions, we need new tools for location privacy. In this paper, we focus on the problem of secure location sharing, where a group of n clients want to collaborate with each other to anonymously share their location data with a location database server and execute queries based on them. To become more realistic, we assume up to a certain fraction of the clients are controlled arbitrarily by an active and computationally unbounded adversary. A relaxed version of this problem has already been studied in the literature assuming either a trusted third party or a weaker adversarial model. We alternatively propose a scalable approach for secure location sharing that tolerates up to n/6 staticallychosen malicious clients and does not require any trusted third party. We show that, unlike most other locationbased services, our protocol is secure against trafficanalysis attacks. We also show that our protocol requires each client to send a polylogarithmic number of bits and compute a polylogarithmic number of operations (with respect to n) to query a point of interest based on its location. 1