论文标题
测量非策略蛮力猜测中的信息泄漏
Measuring Information Leakage in Non-stochastic Brute-Force Guessing
论文作者
论文摘要
我们建议在非策略环境中进行信息泄漏的操作度量，以使野蛮的猜测对手形式化隐私。我们使用不确定的变量，随机变量的非稳态对应物来构建一个猜测框架，其中对手有兴趣根据不确定的报告确定私人信息。我们考虑蛮力反复试验猜测，在这种猜测中，对手可以可能检查与可用输出兼容的私人信息的所有可能性，以找到实际的私人实现。在产出的情况下，在不存在的情况下，对手的最坏情况猜测的比率捕获了对手的猜测复杂性的降低，因此被用作衡量私人信息泄漏的量度。我们研究了新开发的信息泄漏的度量与现有的非传统最大值信息和随机最大泄漏之间的关系，这些信息显示出一声猜测。
We propose an operational measure of information leakage in a non-stochastic setting to formalize privacy against a brute-force guessing adversary. We use uncertain variables, non-probabilistic counterparts of random variables, to construct a guessing framework in which an adversary is interested in determining private information based on uncertain reports. We consider brute-force trial-and-error guessing in which an adversary can potentially check all the possibilities of the private information that are compatible with the available outputs to find the actual private realization. The ratio of the worst-case number of guesses for the adversary in the presence of the output and in the absence of it captures the reduction in the adversary's guessing complexity and is thus used as a measure of private information leakage. We investigate the relationship between the newly-developed measure of information leakage with the existing non-stochastic maximin information and stochastic maximal leakage that are shown arise in one-shot guessing.
