基于偏好的隐私交易
Preference-Based Privacy Trading
摘要：
我们通过这篇论文提出的问题是：在他们正式同意（许可）的情况下交易消费者个人信息，并作为回报向他们提供激励（金钱或其他方式），在经济上是否可行？鉴于（a）人类是“妥协”生物并有隐私偏好的行为假设，（b）隐私作为一种没有严格界限的商品，以及（c）数据发布供应链下游的数据持有者不适当泄露数据的实际必然性，我们提出了一个设计的监管有效/在一个简化的卖方-经纪人市场上，利用一种新的偏好函数投标方法，研究了寡头垄断数据交易市场的有界无效率经济机制。我们的方法保留了异构隐私保护约束（在分组消费者处，即，APP，级别）达到一定的折衷级别，并且同时满足代理（例如，广告组织）收集客户数据用于定向行为广告。
英文摘要：
The question we raise through this paper is: Is it economically feasible to trade consumer personal information with their formal consent (permission) and in return provide them incentives (monetary or otherwise)?. In view of (a) the behavioral assumption that humans are `compromising' beings and have privacy preferences, (b) privacy as a good not having strict boundaries, and (c) the practical inevitability of inappropriate data leakage by data holders downstream in the data-release supply-chain, we propose a design of regulated efficient/bounded inefficient economic mechanisms for oligopoly data trading markets using a novel preference function bidding approach on a simplified sellers-broker market. Our methodology preserves the heterogeneous privacy preservation constraints (at a grouped consumer, i.e., app, level) upto certain compromise levels, and at the same time satisfies information demand (via the broker) of agencies (e.g., advertising organizations) that collect client data for the purpose of targeted behavioral advertising.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
