论文标题
使用Chapman-Robbins绑定的MIMO网络物理系统中最大化隐私
Maximizing Privacy in MIMO Cyber-Physical Systems Using the Chapman-Robbins Bound
论文作者
论文摘要
网络物理系统的隐私漏洞可能会使脆弱性暴露于对手。在这里，通过加性高斯噪声来减轻线性时间不变系统的步骤输入的隐私泄漏。隐私的基本下限是基于任何试图重新创建输入的估计器的差异的。研究了完全私人输入，并与传输零有关。此后，提出了一种提高最佳步骤输入隐私的方法，并得出了隐私 - 私人权衡权衡。最后，这些结果在KTH Live-In-In-In-In-In-In-In-In-In-In-In-In-In-In-Interbed中进行了验证，显示出与理论结果的良好对应关系。
Privacy breaches of cyber-physical systems could expose vulnerabilities to an adversary. Here, privacy leaks of step inputs to linear-time-invariant systems are mitigated through additive Gaussian noise. Fundamental lower bounds on the privacy are derived, which are based on the variance of any estimator that seeks to recreate the input. Fully private inputs are investigated and related to transmission zeros. Thereafter, a method to increase the privacy of optimal step inputs is presented and a privacy-utility trade-off bound is derived. Finally, these results are verified on data from the KTH Live-In Lab Testbed, showing good correspondence with theoretical results.
