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In previous work (arXiv:0910.5714), we introduced the Privacy Approximation Ratio (PAR) and used it to study the privacy of protocols for second-price Vickrey auctions and Yaos millionaires problem. Here, we study the PARs of multiple protocols for both the disjointness problem (in which two participants, each with a private subset of {1,...,k}, determine whether their sets are disjoint) and the intersection problem (in which the two participants, each with a private subset of {1,...,k}, determine the intersection of their private sets). We show that the privacy, as measured by the PAR, provided by any protocol for each of these problems is necessarily exponential (in k). We also consider the ratio between the subjective PARs with respect to each player in order to show that one protocol for each of these problems is significantly fairer than the others (in the sense that it has a similarly bad effect on the privacy of both players).
Set-based estimation has gained a lot of attention due to its ability to guarantee state enclosures for safety-critical systems. However, it requires computationally expensive operations, which in turn often requires outsourcing of these operations t
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