A Secure, Confidential, and Verifiable Decision Support System

Abstract

Decision support systems are increasingly adopted to automate decision-making processes across industries, organizations, and governments. Decision support demands data privacy, integrity, and availability while ensuring customization, security, and verifiability of the decision process. Existing solutions fail to guarantee those properties altogether. To overcome this limitation, we propose SPARTA, an approach based on Trusted Execution Environments (TEEs) that automates decision processes. To guarantee privacy, integrity, and availability, SPARTA employs efficient cryptographic techniques on notarized data with access mediated through user-defined access policies. Our solution allows users to define decision rules, which are translated to certified software objects deployed within TEEs, thereby guaranteeing customization, verifiability, and security of the process. With experiments run on public benchmarks and synthetic data, we show our approach is scalable and adds limited overhead compared to non-cryptographically secured solutions.

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