论文标题
在隐私，保密，失真和通信约束下的功能计算
Function Computation Under Privacy, Secrecy, Distortion, and Communication Constraints
论文作者
论文摘要
可靠函数计算的问题是通过对多方观察到嘈杂的测量值的远程来源的隐私，保密和存储约束来扩展的。经典函数计算问题的主要添加包括1）相对于远程源而不是传输终端观察到的序列，对窃听器的隐私泄漏进行了测量； 2）相对于远程源的融合中心的信息泄漏被视为新的隐私泄漏度量； 3）计算的函数被允许是目标函数的扭曲版本，与可靠的函数计算方案相比，它可以降低存储速率，此外还可以减少保密和隐私泄漏； 4）使用两个传输节点观察来计算函数。速率区域上的内部和外部边界通过两个传输节点得出了无损和有损的单功能计算，这些节点在文献中恢复了先前的结果。对于特殊情况，包括可逆和部分可逆函数以及退化的测量通道，建立了简化的无损和损耗率区域边界，并将一个区域评估为示例场景。
The problem of reliable function computation is extended by imposing privacy, secrecy, and storage constraints on a remote source whose noisy measurements are observed by multiple parties. The main additions to the classic function computation problem include 1) privacy leakage to an eavesdropper is measured with respect to the remote source rather than the transmitting terminals' observed sequences; 2) the information leakage to a fusion center with respect to the remote source is considered as a new privacy leakage metric; 3) the function computed is allowed to be a distorted version of the target function, which allows to reduce the storage rate as compared to a reliable function computation scenario in addition to reducing secrecy and privacy leakages; 4) two transmitting node observations are used to compute a function. Inner and outer bounds on the rate regions are derived for lossless and lossy single-function computation with two transmitting nodes, which recover previous results in the literature. For special cases, including invertible and partially invertible functions, and degraded measurement channels, simplified lossless and lossy rate region bounds are established, and one region is evaluated as an example scenario.
