论文标题
空间隐私定价：地理市场中隐私，实用性和价格之间的相互作用
Spatial Privacy Pricing: The Interplay between Privacy, Utility and Price in Geo-Marketplaces
论文作者
论文摘要
地理市场允许为其位置数据付费用户。关注隐私的用户可能希望为准确指出其位置的数据收取更多费用，但对于更模糊的数据可能会收取更少的收费。买方希望最大程度地减少数据成本，但可能需要花费更多才能获得必要的准确性。我们称这种相互作用在隐私，实用程序和价格\ emph {空间隐私定价}之间。我们以一个示例问题的示例问题来确定是否可以通过购买位置数据来确定潜在的客户数量是否足以开放。该问题表示为一个顺序决策问题，买家首先做出一系列决定要购买哪些数据并结束有关是否开设餐厅的决定。我们提出了两种解决此问题的算法，包括表明它们比基准更好的实验。
A geo-marketplace allows users to be paid for their location data. Users concerned about privacy may want to charge more for data that pinpoints their location accurately, but may charge less for data that is more vague. A buyer would prefer to minimize data costs, but may have to spend more to get the necessary level of accuracy. We call this interplay between privacy, utility, and price \emph{spatial privacy pricing}. We formalize the issues mathematically with an example problem of a buyer deciding whether or not to open a restaurant by purchasing location data to determine if the potential number of customers is sufficient to open. The problem is expressed as a sequential decision making problem, where the buyer first makes a series of decisions about which data to buy and concludes with a decision about opening the restaurant or not. We present two algorithms to solve this problem, including experiments that show they perform better than baselines.
