论文标题
本地私人准摩尔的一位提交：其渐近正常性和限制
One-bit Submission for Locally Private Quasi-MLE: Its Asymptotic Normality and Limitation
论文作者
论文摘要
局部差异隐私〜（LDP）是一种信息理论隐私定义，适用于涉及不受信任数据策展人的统计调查。已经开发了一种Quasi-Maximim可能性估计值〜（QMLE）的LDP版本，但是由于长期等待时间，昂贵的沟通成本以及对日志 - 流行期函数的衍生性假设，在现实世界中，在现实世界中建立LDP QMLE的现有方法很难实现。我们提供了一个没有这些问题的替代自然保护协议，这很容易在大规模调查中部署。我们还提供了足够的条件，以达到一致性和渐近正态性和协议的局限性。对于用户而言，我们的协议不那么繁重，理论保证涵盖的案例比现有方法更现实。
Local differential privacy~(LDP) is an information-theoretic privacy definition suitable for statistical surveys that involve an untrusted data curator. An LDP version of quasi-maximum likelihood estimator~(QMLE) has been developed, but the existing method to build LDP QMLE is difficult to implement for a large-scale survey system in the real world due to long waiting time, expensive communication cost, and the boundedness assumption of derivative of a log-likelihood function. We provided an alternative LDP protocol without those issues, which is potentially much easily deployable to a large-scale survey. We also provided sufficient conditions for the consistency and asymptotic normality and limitations of our protocol. Our protocol is less burdensome for the users, and the theoretical guarantees cover more realistic cases than those for the existing method.
