Secure Multi-Function Computation with Private Remote Sources
Secure Multi-Function Computation with Private Remote Sources
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DOI：
10.1109/isit45174.2021.9518019
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发表时间：
2021-06
期刊：
影响因子：
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通讯作者：
O. Günlü;M. Bloch;Rafael F. Schaefer
中科院分区：
文献类型：
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作者：
O. Günlü;M. Bloch;Rafael F. Schaefer
我们考虑一个分布式函数计算问题，在该问题中，各方观察嘈杂的版本的远程源方便计算的功能，他们的意见，在融合中心通过公共通信。分布式函数计算受到约束，不仅包括可靠性和存储，而且还包括隐私和保密。具体地，1）根据关于远程源泄露的信息来测量，远程源应该对窃听者和融合中心保持私密; 2）根据关于函数的自变量泄露的信息来测量，计算的函数应该对窃听者保持秘密，以确保保密性，而不管使用的确切函数。我们推导出准确的速率区域的无损和有损单函数计算和说明的信息瓶颈的例子，其中最佳辅助随机变量的特点是二进制输入对称输出通道的有损单函数计算速率区域。我们扩展的方法，无损和有损的异步多功能计算与联合保密和隐私的限制，在这种情况下，内部和外部边界的速率区域不同，只在马尔可夫链条件的特点。
We consider a distributed function computation problem in which parties observing noisy versions of a remote source facilitate the computation of a function of their observations at a fusion center through public communication. The distributed function computation is subject to constraints, including not only reliability and storage but also privacy and secrecy. Specifically, 1) the remote source should remain private from an eavesdropper and the fusion center, measured in terms of the information leaked about the remote source; 2) the function computed should remain secret from the eavesdropper, measured in terms of the information leaked about the arguments of the function, to ensure secrecy regardless of the exact function used. We derive the exact rate regions for lossless and lossy single-function computation and illustrate the lossy single-function computation rate region for an information bottleneck example, in which the optimal auxiliary random variables are characterized for binary input symmetric output channels. We extend the approach to lossless and lossy asynchronous multiple-function computations with joint secrecy and privacy constraints, in which case inner and outer bounds for the rate regions differing only in the Markov chain conditions imposed are characterized.