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arXiv 2201.03948cs.ITcs.CRcs.DCcs.IRmath.IT
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隐私、保密、失真与通信约束下的函数计算

Function Computation Under Privacy, Secrecy, Distortion, and Communication Constraints

Onur Günlü

AI总结:

本文针对带噪声测量的远程信源,扩展了带隐私、保密、存储约束的函数计算问题,提出新的泄露度量与失真计算方案,推导了双节点无损/有损计算的速率区域界并简化特殊情形下的结果。

摘要:

本文对可靠函数计算问题进行了扩展,对其噪声测量值被多方观测的远程信源施加了隐私、保密和存储约束。相较于经典函数计算问题,本文的主要新增内容包括:1)针对窃听者的隐私泄露以远程信源而非发送端观测序列为基准进行度量;2)针对融合中心的、以远程信源为基准的信息泄露被视为一种新的隐私泄露度量指标;3)允许计算得到的函数是目标函数的失真版本,与可靠函数计算场景相比,这除了能降低保密和隐私泄露量外,还能降低存储速率;4)采用两个发送节点的观测值来计算函数。本文推导了双发送节点无损和有损单函数计算速率区域的内界与外界,这些界可复现现有文献中的已有结果。针对可逆函数、部分可逆函数以及退化测量信道等特殊情况,本文建立了简化的无损和有损速率区域界,并以一个区域为例进行了数值评估。

英文摘要:

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.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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