CAREER: Privacy Preserving Transactions with Accountability Extensions

以电子方式收集和处理的数字数据量不断增加，对用户隐私构成严重威胁。虽然文献中存在许多增强数据隐私的加密机制，但它们具有令人望而却步的计算和通信成本，并且不提供问责机制。如果不提高效率和增加问责机制，就不可能大规模采用如此迫切需要的隐私保护系统。为了实现使隐私增强技术更接近采用的目标，该项目定义并构建了一些新的密码构建块，例如新型数字签名，密码验证和零知识证明，这些都是用于增强隐私的机制的核心。为了构建实用的协议，该项目在遵循可证明安全协议设计原则的同时，引入了新的安全放松和安全模型（例如用户-设备分离），并为不同的系统参与者设计了问责机制，而不依赖于可信第三方和秘密陷门。该研究是根据三个主要的推力，侧重于不同的应用领域。也就是说，该项目研究了匿名分散支付（基于区块链），匿名身份验证（通过使用匿名凭据）和特定功能的可审计多方计算（MPC）。所进行的研究包括与政策和经济学研究人员的合作，以设计有意义的问责机制并利用区块链激励措施。该项目为不同背景的学生提供密码学和隐私保护技术的基础和实践教育，从K-12学生到工程和CS学生，以及政策学生和MBA级别的高级管理人员。该奖项反映了NSF的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估而被认为值得支持。

The amount of digital data collected and handled electronically is constantly increasing and poses serious threats to user privacy. While a number of cryptographic mechanisms that enhance data privacy exist in the literature, they suffer from prohibitive computational and communication costs and do not offer accountability mechanisms. Without improvements in efficiency and addition of accountability mechanisms, it is unlikely that the so much needed privacy-preserving systems will be massively adopted. Towards the goal of bringing privacy-enhancing technologies closer to adoption, this project defines and constructs a number of new cryptographic building blocks such as new types of digital signatures, cryptographic accumulators and zero-knowledge proofs which are at the core of mechanisms used to enhance privacy. In order to build practical protocols, the project introduces new security relaxations and security models (such as user-device separation) while adhering to the principles of provable secure protocol design, and designs accountability mechanisms for different system participants without relying on trusted third parties and secret trapdoors. The research is organized under three main thrusts which focus on different application areas. Namely, the project investigates anonymous decentralized payments (blockchain based), anonymous authentication (via the use of anonymous credentials), and auditable multi-party computation (MPC) for specific functions. The performed research includes collaborations with Policy and Economics researchers in order to design meaningful accountability mechanisms and leverage blockchain incentives. The project provides education on fundamentals and practices of cryptography and privacy-preserving techniques to students with various backgrounds: from K-12 students to engineering and CS students, as well as policy students and senior executives studying at the MBA level.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.