Differentially Private Interval Observer Design with Bounded Input Perturbation
Differentially Private Interval Observer Design with Bounded Input Perturbation
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具有有界输入扰动的差分隐私区间观测器设计
DOI：
10.23919/acc45564.2020.9147726
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发表时间：
2020
期刊：
影响因子：
--
通讯作者：
J. L. Ny
中科院分区：
文献类型：
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作者：
Kwassi H. Degue;J. L. Ny
用于诸如智能交通系统的新兴系统的实时数据处理需要基于从个人收集的隐私敏感数据来估计变量，他们的位置追踪在本文中，我们提出了一个隐私保护的区间观测器架构的多智能体系统，其中一个有界的隐私保护噪声被添加到每个参与者的数据，并随后考虑到观察员。观察者发布的估计值保证了代理数据的差异隐私，这意味着它们的统计分布对任何单个代理信号的某些变化都不太敏感。数值模拟说明了所提出的架构的行为。
Real-time data processing for emerging systems such as intelligent transportation systems requires estimating variables based on privacy-sensitive data gathered from individuals, e.g., their location traces. In this paper, we present a privacy-preserving interval observer architecture for a multiagent system, where a bounded privacy-preserving noise is added to each participant’s data and is subsequently taken into account by the observer. The estimates published by the observer guarantee differential privacy for the agents’ data, which means that their statistical distribution is not too sensitive to certain variations in any single agent’s signal. A numerical simulation illustrates the behavior of the proposed architecture.