4,472 research outputs found

    Peer-to-Peer Secure Multi-Party Numerical Computation Facing Malicious Adversaries

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    We propose an efficient framework for enabling secure multi-party numerical computations in a Peer-to-Peer network. This problem arises in a range of applications such as collaborative filtering, distributed computation of trust and reputation, monitoring and other tasks, where the computing nodes is expected to preserve the privacy of their inputs while performing a joint computation of a certain function. Although there is a rich literature in the field of distributed systems security concerning secure multi-party computation, in practice it is hard to deploy those methods in very large scale Peer-to-Peer networks. In this work, we try to bridge the gap between theoretical algorithms in the security domain, and a practical Peer-to-Peer deployment. We consider two security models. The first is the semi-honest model where peers correctly follow the protocol, but try to reveal private information. We provide three possible schemes for secure multi-party numerical computation for this model and identify a single light-weight scheme which outperforms the others. Using extensive simulation results over real Internet topologies, we demonstrate that our scheme is scalable to very large networks, with up to millions of nodes. The second model we consider is the malicious peers model, where peers can behave arbitrarily, deliberately trying to affect the results of the computation as well as compromising the privacy of other peers. For this model we provide a fourth scheme to defend the execution of the computation against the malicious peers. The proposed scheme has a higher complexity relative to the semi-honest model. Overall, we provide the Peer-to-Peer network designer a set of tools to choose from, based on the desired level of security.Comment: Submitted to Peer-to-Peer Networking and Applications Journal (PPNA) 200

    On the Round Complexity of Randomized Byzantine Agreement

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    We prove lower bounds on the round complexity of randomized Byzantine agreement (BA) protocols, bounding the halting probability of such protocols after one and two rounds. In particular, we prove that: 1) BA protocols resilient against n/3 [resp., n/4] corruptions terminate (under attack) at the end of the first round with probability at most o(1) [resp., 1/2+ o(1)]. 2) BA protocols resilient against n/4 corruptions terminate at the end of the second round with probability at most 1-Theta(1). 3) For a large class of protocols (including all BA protocols used in practice) and under a plausible combinatorial conjecture, BA protocols resilient against n/3 [resp., n/4] corruptions terminate at the end of the second round with probability at most o(1) [resp., 1/2 + o(1)]. The above bounds hold even when the parties use a trusted setup phase, e.g., a public-key infrastructure (PKI). The third bound essentially matches the recent protocol of Micali (ITCS\u2717) that tolerates up to n/3 corruptions and terminates at the end of the third round with constant probability

    Self-Healing Computation

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    In the problem of reliable multiparty computation (RC), there are nn parties, each with an individual input, and the parties want to jointly compute a function ff over nn inputs. The problem is complicated by the fact that an omniscient adversary controls a hidden fraction of the parties. We describe a self-healing algorithm for this problem. In particular, for a fixed function ff, with nn parties and mm gates, we describe how to perform RC repeatedly as the inputs to ff change. Our algorithm maintains the following properties, even when an adversary controls up to t(14ϵ)nt \leq (\frac{1}{4} - \epsilon) n parties, for any constant ϵ>0\epsilon >0. First, our algorithm performs each reliable computation with the following amortized resource costs: O(m+nlogn)O(m + n \log n) messages, O(m+nlogn)O(m + n \log n) computational operations, and O()O(\ell) latency, where \ell is the depth of the circuit that computes ff. Second, the expected total number of corruptions is O(t(logm)2)O(t (\log^{*} m)^2), after which the adversarially controlled parties are effectively quarantined so that they cause no more corruptions.Comment: 17 pages and 1 figure. It is submitted to SSS'1
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