论文标题
隐私与公用事业的经济学：投资策略
The Economics of Privacy and Utility: Investment Strategies
论文作者
论文摘要
由于个人信息不受约束的披露，不可避免地泄漏了隐私的泄漏，这激发了有关强大隐私机制的广泛研究。但是，现有的研究大部分仅限于在静态环境中解决问题，而随着时间的推移无视隐私泄漏。不幸的是，这种对隐私的处理不足，在实际情况下，用户随着时间的推移不断披露其个人信息，从而导致用户敏感信息累积泄漏。在本文中，我们考虑在有限的时间范围内考虑隐私泄漏，并研究最佳策略，以最大程度地提高公开数据的实用性，同时限制有限的Horizon隐私泄漏。我们考虑一种简单的隐私机制，该机制涉及在每次披露之前压缩用户的数据，以满足对未来隐私的所需约束。我们进一步激励了几种算法，以优化动态的隐私 - 效用折衷方案，并通过广泛的合成性能测试评估其性能。
The inevitable leakage of privacy as a result of unrestrained disclosure of personal information has motivated extensive research on robust privacy-preserving mechanisms. However, existing research is mostly limited to solving the problem in a static setting with disregard for the privacy leakage over time. Unfortunately, this treatment of privacy is insufficient in practical settings where users continuously disclose their personal information over time resulting in an accumulated leakage of the users' sensitive information. In this paper, we consider privacy leakage over a finite time horizon and investigate optimal strategies to maximize the utility of the disclosed data while limiting the finite-horizon privacy leakage. We consider a simple privacy mechanism that involves compressing the user's data before each disclosure to meet the desired constraint on future privacy. We further motivate several algorithms to optimize the dynamic privacy-utility tradeoff and evaluate their performance via extensive synthetic performance tests.
