Privacy and coordination: computing on databases with endogenous participation
Privacy and coordination: computing on databases with endogenous participation
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隐私与协调：内生参与的数据库计算
DOI：
10.1145/2482540.2482585
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发表时间：
2013
影响因子：
6.8
通讯作者：
Katrina Ligett
中科院分区：
文献类型：
--
作者：
Arpita Ghosh;Katrina Ligett
我们提出了一个简单的模型，在一个隐私敏感的人口中的个人决定是否参与预先宣布的嘈杂的计算分析师，使数据库本身是内生的个人的参与选择。代理接收的隐私既取决于所宣布的噪声水平，也取决于有多少代理选择参与数据库。每个代理都有一些最低的隐私要求，并根据她的隐私要求与她参与计算时将获得的隐私期望的比较来决定是否参与。这就产生了代理之间的博弈，每个人的隐私，如果她参与，因此她的参与选择，取决于其余人口的选择。
我们研究对称贝叶斯-纳什均衡，在这个游戏中包括阈值策略，所有代理的隐私要求弱于一定的阈值参与，其余的代理没有。我们描述这些平衡，这取决于分析师和人口规模宣布的噪音;存在性，唯一性和多重性的目前结果;并讨论了一些令人惊讶的性能，他们显示。
We propose a simple model where individuals in a privacy-sensitive population decide whether or not to participate in a pre-announced noisy computation by an analyst, so that the database itself is endogenously determined by individuals' participation choices. The privacy an agent receives depends both on the announced noise level, as well as how many agents choose to participate in the database. Each agent has some minimum privacy requirement, and decides whether or not to participate based on how her privacy requirement compares against her expectation of the privacy she will receive if she participates in the computation. This gives rise to a game amongst the agents, where each individual's privacy if she participates, and therefore her participation choice, depends on the choices of the rest of the population.
We investigate symmetric Bayes-Nash equilibria, which in this game consist of threshold strategies, where all agents whose privacy requirements are weaker than a certain threshold participate and the remaining agents do not. We characterize these equilibria, which depend both on the noise announced by the analyst and the population size; present results on existence, uniqueness, and multiplicity; and discuss a number of surprising properties they display.