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The great potential of data mining in a networked world cannot be realized without acceptable guarantees that private information will be protected. In theory, general cryptographic protocols for secure multiparty computation enable data mining with privacy preservation that is optimal with respect to the desired end results. However, the performance(More)
Although the semi-honest model is reasonable in some cases, it is unrealistic to assume that adversaries will al- ways follow the protocols exactly. In particular, malicious adversaries could deviate arbitrarily from their prescribed protocols. Clearly, protocols that can withstand malicious adversaries provide more security. However, there is an ob- vious(More)
Lindell and Pinkas demonstrated that it is feasible to preserve privacy in data mining by employing a combination of general-purpose and specialized securemultiparty-computation (SMC) protocol components. Yet practical obstacles of several sorts have impeded a fully practical realization of this idea. In this paper, we address the correctness and(More)
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