论文标题

隐私和完整性保留清晰的计算

Privacy and Integrity Preserving Computations with CRISP

论文作者

Chatel, Sylvain, Pyrgelis, Apostolos, Troncoso-Pastoriza, Juan R., Hubaux, Jean-Pierre

论文摘要

在数字时代,用户与服务提供商共享他们的个人数据,以获得一些实用程序,例如获得高质量服务。然而,诱导的信息流引起了隐私和完整性的关注。因此,谨慎的用户可能希望通过最大程度地减少向好奇的服务提供商披露的信息来保护其隐私。服务提供商有兴趣验证用户数据的完整性以改善其服务并为其业务获得有用的知识。在这项工作中,我们通过实现已加密为服务提供商加密的数据的真实性验证,为隐私,完整性和实用程序之间的权衡提供了一个通用的解决方案。基于基于晶格的同型加密和承诺以及零知识证明,我们的构建使服务提供商能够以隐私友好的方式处理和重复使用第三方签署的数据,并提供完整性的保证。我们评估了有关不同用例的解决方案,例如智能计量,疾病敏感性和基于位置的活动跟踪,从而显示出其多功能性。我们的解决方案实现了广泛的一般性,量子的抗性,并放松了最先进的解决方案的一些假设,而不会影响性能。

In the digital era, users share their personal data with service providers to obtain some utility, e.g., access to high-quality services. Yet, the induced information flows raise privacy and integrity concerns. Consequently, cautious users may want to protect their privacy by minimizing the amount of information they disclose to curious service providers. Service providers are interested in verifying the integrity of the users' data to improve their services and obtain useful knowledge for their business. In this work, we present a generic solution to the trade-off between privacy, integrity, and utility, by achieving authenticity verification of data that has been encrypted for offloading to service providers. Based on lattice-based homomorphic encryption and commitments, as well as zero-knowledge proofs, our construction enables a service provider to process and reuse third-party signed data in a privacy-friendly manner with integrity guarantees. We evaluate our solution on different use cases such as smart-metering, disease susceptibility, and location-based activity tracking, thus showing its versatility. Our solution achieves broad generality, quantum-resistance, and relaxes some assumptions of state-of-the-art solutions without affecting performance.

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