Applications of Secure Computation

当涉及到个人信息时，社会需要提供高效和有效的服务与个人隐私权之间存在紧张关系。在分配有限的资源时，许多服务都受益于访问有关个人的详细数据。例如，对患者信息的更大访问使医学研究人员能够开发新的和更个性化的治疗方法。与此同时，一系列政策和法律已经出台，通过限制分享敏感的个人信息来保护个人隐私。因此，任何既能满足服务提供者的分析需要，又能保护个人隐私的方法对社会都是有益的。**安全多方计算面临的问题是，两方或多方如何通过通信来回答相互重要的问题，而参与者相互透露的信息不超过结果本身所透露的信息。使用加密技术，这种方法允许个人和组织将他们的个人和私人信息的分析能力结合起来，而无需直接共享它。这为回答依赖于个人数据访问的重要问题打开了一扇全新可能性的大门。**我们提出了一个研究计划，探索安全计算在现实世界中重要问题的新应用。主要的重点领域将是在医疗保健领域开发安全的计算技术。其他重点领域将包括安全的在线投票和数字货币。我们之前在这些重点领域的研究经验使我们采用以下方法：(1)咨询这些应用领域的服务利益相关者，以确定涉及个人和私人数据的分析重要性问题；(2)定义一套安全需求，并开发安全的多方计算协议来实现这些需求；(3)分析协议的安全特性以确保其满足要求；(4)在软件中对协议进行原型化以评估其计算效率，从而评估其可行性。

When it comes to personal information, a tension exists between society's need to provide efficient and effective services, and an individual's right to privacy. Many services benefit from access to detailed data about individuals when allocating their limited resources. For example, greater access to patient information allows medical researchers to develop new and more personalized treatments. At the same time, a range of policies and laws have emerged to protect individual privacy by restricting the sharing of sensitive personal information. Any methodology that could simultaneously meet the analytical needs of service providers while protecting individual privacy, therefore, would be useful to a society.**Secure multi-party computation confronts the problem of how two or more parties can communicate to answer questions of mutual importance, without the participants revealing more to each other than what is revealed by the result itself. Using cryptographic techniques, this approach allows individuals and organizations to combine the analytical power of their personal and private information without ever sharing it directly. This opens the door to fundamentally new possibilities for answering important questions that rely on access to personal data.**We propose a research program exploring new applications of secure computation to questions of practical, real-world importance. The primary area of focus will be to develop secure computation techniques in the field of healthcare. Other key areas of focus will include secure online voting and digital currency. Our previous research experience in these focus areas leads us to the following methodology: (1) consult with stakeholders of services in these application areas to identify questions of analytical importance involving personal and private data; (2) define a set of security requirements and develop a secure multi-party computation protocol to realize them; (3) analyze the security properties of the protocol to ensure it meets the requirements, and (4) prototype the protocol in software to evaluate its computational efficiency, and hence its feasibility.