On Privacy of Quantized Sensor Measurements through Additive Noise
On Privacy of Quantized Sensor Measurements through Additive Noise
复制标题
关于通过加性噪声进行量化传感器测量的保密性
DOI：
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发表时间：
2018
期刊：
影响因子：
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通讯作者：
D. Nešić
中科院分区：
文献类型：
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作者：
C. Murguia;I. Shames;F. Farokhi;D. Nešić
研究了通过添加随机变量来最大化量化传感器测量的隐私性问题。特别地，我们考虑使用噪声传感器测量来获得关于进程状态的信息的设置。该信息被量化并通过不安全的通信网络发送到远程站。希望将进程的状态保密；但是，由于网络不安全，攻击者可能会访问传感器信息，这些信息可用于估计进程状态。为了避免精确的状态估计，我们将随机数添加到量化的传感器测量中，并将和发送到远程站。这些随机变量的分布旨在最小化期望失真级别的总和和量化传感器测量之间的互信息-允许总和和量化传感器测量有多大不同。仿真结果验证了我们的结果。
We study the problem of maximizing privacy of quantized sensor measurements by adding random variables. In particular, we consider the setting where information about the state of a process is obtained using noisy sensor measurements. This information is quantized and sent to a remote station through an unsecured communication network. It is desired to keep the state of the process private; however, because the network is not secure, adversaries might have access to sensor information, which could be used to estimate the process state. To avoid an accurate state estimation, we add random numbers to the quantized sensor measurements and send the sum to the remote station instead. The distribution of these random variables is designed to minimize the mutual information between the sum and the quantized sensor measurements for a desired level of distortion - how different the sum and the quantized sensor measurements are allowed to be. Simulations are presented to illustrate our results.