Generating additive secret shares of a shuffled dataset – such that neither party knows the order in which it is permuted – is a fundamental building block in many protocols, such as secure collaborative filtering, oblivious sorting, and secure function evaluation on set intersection. Traditional approaches to this problem either involve expensive public-key based crypto or using symmetric crypto on permutation networks. While public-key-based solutions are bandwidth efficient, they are computation-heavy. On the other hand, constructions based on permutation networks are communication-bound, especially when the dataset contains large elements, for e.g., feature vectors in an ML context.<\/p>\n","protected":false},"excerpt":{"rendered":"
Generating additive secret shares of a shuffled dataset – such that neither party knows the order in which it is permuted – is a fundamental building block in many protocols, such as secure collaborative filtering, oblivious sorting, and secure function evaluation on set intersection. Traditional approaches to this problem either involve expensive public-key based crypto 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