论文标题
安全计算以隐藏输入功能
Secure Computation to Hide Functions of Inputs
论文作者
论文摘要
我们考虑了一个两用户安全的计算问题,其中爱丽丝和鲍勃进行了交流,以计算输入的一些确定性功能。隐私要求是,每个用户不应学习有关输入功能的任何其他信息,而不是从其自身输入和输出中推断出的内容。对于无分配设置,即,当协议必须正确且用于任何关节输入分布时,我们完全表征了所有可牢固计算功能的集合。当仅针对基于爱丽丝的单个传输计算函数的鲍勃需要隐私时,我们表明渐近安全的可计算性等于完全安全的可计算性。另外,我们考虑一个可以访问所有通信的窃听者,不应学习有关输入的某些功能的任何信息(可能与用户计算的功能有所不同),并表明相互作用可能是安全计算所必需的。
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.