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Amortizing Randomness in Private Multiparty Computations (2002)
| Content Provider | CiteSeerX |
|---|---|
| Author | Kushilevitz, Eyal Ostrovsky, Rafail Rosen, Adi |
| Description | We study the relationship between the number of rounds needed to repeatedly perform a private computation (i.e. where there are many sets of inputs sequentially given to the players on which the players must compute a function privately) and the overall randomness needed for this task. For the xor function, we show that for k sets of inputs, if instead of using totally fresh (i.e., independent) random bits for each of these k sets of inputs, we re-use the same ` random bits then we can significantly speedup the round-complexity of each computation compared to what is achieved by the naive strategy of partitioning the ` random bits between the k computations. |
| File Format | |
| Language | English |
| Publisher Date | 2002-01-01 |
| Publisher Institution | Proc. of 17th PODC |
| Access Restriction | Open |
| Subject Keyword | Overall Randomness Private Multiparty Computation Private Computation Many Set Xor Function Random Bit Naive Strategy |
| Content Type | Text |
| Resource Type | Article |
