ObliVM: A Programming Framework for Secure Computation

作者：Chang Liu, Xiao Shaun Wang, Kartik Nayak, Yan Huang, Elaine Shi · 年份：2015 · DOI：10.1109/sp.2015.29 · 被引用次数：313 · 研究领域：Cryptography and Data Security、Complexity and Algorithms in Graphs、Privacy-Preserving Technologies in Data

We design and develop ObliVM, a programming framework for secure computation. ObliVM offers a domain specific language designed for compilation of programs into efficient oblivious representations suitable for secure computation. ObliVM offers a powerful, expressive programming language and user-friendly oblivious programming abstractions. We develop various showcase applications such as data mining, streaming algorithms, graph algorithms, genomic data analysis, and data structures, and demonstrate the scalability of ObliVM to bigger data sizes. We also show how ObliVM significantly reduces development effort while retaining competitive performance for a wide range of applications in comparison with hand-crafted solutions. We are in the process of open-sourcing ObliVM and our rich libraries to the community (www.oblivm.com), offering a reusable framework to implement and distribute new cryptographic algorithms.