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Secure Computation to Hide Functions of Inputs

机译:安全计算以隐藏输入功能

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We consider a two-user secure computation problem in which Alice and Bob communicate interactively in order to compute some deterministic functions of the inputs. The privacy requirement is that each user should not learn any additional information about a function of the inputs other than what can be inferred from its own input and output. For the distribution-free setting, i.e., when the protocol must be correct and private for any joint input distribution, we completely characterize the set of all securely computable functions. When privacy is required only against Bob who computes a function based on a single transmission from Alice, we show that asymptotically secure computability is equivalent to perfectly secure computability. Separately, we consider an eavesdropper who has access to all the communication and should not learn any information about some function of the inputs (possibly different from the functions to be computed by the users) and show that interaction may be necessary for secure computation.
机译:我们考虑一个两用户安全的计算问题,其中Alice和Bob进行交互通信以计算输入的某些确定性函数。隐私要求是,除了可以从其自己的输入和输出中推断出的内容之外,每个用户都不应学习与输入功能有关的任何其他信息。对于无分发设置,即,当协议对于任何联合输入分发必须正确且私有时,我们将完全表征所有安全可计算函数的集合。当仅对基于Alice的一次传输来计算函数的Bob要求隐私时,我们证明渐近安全的可计算性等同于完全安全的可计算性。另外,我们考虑了一个窃听者,该窃听者可以访问所有通信,并且不应该学习有关输入某些功能的任何信息(可能与用户要计算的功能不同),并表明交互对于安全计算可能是必需的。

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