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Secure MultiParty Computation (MPC) allows joint privacy-preserving computations on data of multiple parties. Although MPC has been studied substantially, building solutions that are practical in terms of computation and communication cost is still a major challenge. In this paper, the authors investigate the practical usefulness of MPC for multi-domain network security and monitoring. They first optimize MPC comparison operations for processing high volume data in near real-time. The authors then design privacy-preserving protocols for event correlation and aggregation of network traffic statistics, such as addition of volume metrics, computation of feature entropy, and distinct item count.
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