论文标题
通道泄漏，混淆的信息理论限制以及流媒体数据的最佳隐私面具设计
Channel Leakage, Information-Theoretic Limitations of Obfuscation, and Optimal Privacy Mask Design for Streaming Data
论文作者
论文摘要
在本文中，我们首先将通道泄漏的概念介绍为通道输入和通道输出之间的最小共同信息。顾名思义，通道泄漏将最小信息泄漏到恶意接收器。从广义上讲，它可以看作是通道容量的双重概念，它表征了对目标接收器的最大信息传输。我们为白色高斯案件，彩色高斯案件和褪色案例获得了通道泄漏的明确公式。然后，我们利用这一概念来调查有关流媒体数据的隐私权限权衡（以及隐私功率权衡）的基本限制；特别是，我们为固定案例，非平稳案例和有限时间案例提供了分析权权衡方程。我们的结果还表明了如何以最佳方式设计隐私面具。
In this paper, we first introduce the notion of channel leakage as the minimum mutual information between the channel input and channel output. As its name indicates, channel leakage quantifies the minimum information leakage to the malicious receiver. In a broad sense, it can be viewed as a dual concept of channel capacity, which characterizes the maximum information transmission to the targeted receiver. We obtain explicit formulas of channel leakage for the white Gaussian case, the colored Gaussian case, and the fading case. We then utilize this notion to investigate the fundamental limitations of obfuscation in terms of privacy-distortion tradeoffs (as well as privacy-power tradeoffs) for streaming data; particularly, we derive analytical tradeoff equations for the stationary case, the non-stationary case, and the finite-time case. Our results also indicate explicitly how to design the privacy masks in an optimal way.
