Affiliation:
1. Purdue University, USA
Abstract
Secure computation allows multiple parties to compute joint functions over private data without leaking any sensitive data, typically using powerful cryptographic techniques. Writing secure applications using these techniques directly can be challenging, resulting in the development of several programming languages and compilers that aim to make secure computation accessible. Unfortunately, many of these languages either lack or have limited support for rich recursive data structures, like trees. In this paper, we propose a novel representation of structured data types, which we call oblivious algebraic data types, and a language for writing secure computations using them. This language combines dependent types with constructs for oblivious computation, and provides a security-type system which ensures that adversaries can learn nothing more than the result of a computation. Using this language, authors can write a single function over private data, and then easily build an equivalent secure computation according to a desired public view of their data.
Funder
Intelligence Advanced Research Projects Activity
NSF
Publisher
Association for Computing Machinery (ACM)
Subject
Safety, Risk, Reliability and Quality,Software
Cited by
6 articles.
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1. Combining Classical and Probabilistic Independence Reasoning to Verify the Security of Oblivious Algorithms;Lecture Notes in Computer Science;2024-09-11
2. Language-Based Security for Low-Level MPC;Proceedings of the 26th International Symposium on Principles and Practice of Declarative Programming;2024-09-09
3. Taypsi: Static Enforcement of Privacy Policies for Policy-Agnostic Oblivious Computation;Proceedings of the ACM on Programming Languages;2024-04-29
4. General-Purpose Secure Conflict-free Replicated Data Types;2023 IEEE 36th Computer Security Foundations Symposium (CSF);2023-07
5. Taype: A Policy-Agnostic Language for Oblivious Computation;Proceedings of the ACM on Programming Languages;2023-06-06