Paper 2026/498

Bridging Programmability, Efficiency, and Bounded Trust: A Hybrid Privacy-Preserving Smart Contract Framework

Abstract

Privacy-preserving smart contracts (PPSCs) extend blockchain computation from transparent execution to confidential applications, enabling mutually distrustful parties to jointly compute contract logic on private inputs. Existing PPSC designs can be categorized into two main paradigms: trusted hardware–based systems and cryptographic systems. Trusted hardware-based systems provide general programmability and the performance is usually close to non-confidential computation, but the hardware has to be trusted. In contrast, cryptographic systems require much lower trust on the hardware but the performance is usually much lower. In this paper, we propose a hybrid PPSC framework that combines trusted hardware with cryptographic techniques, achieving both general programmability and reduced reliance on trusted hardware. Specifically, the TEE executes the smart contracts, but needs to authenticate the computation. A proof of the encrypted computational results is sent on-chain, and the blockchain authenticates the computational and aggregates the computational results using cryptographic approaches such as homomorphic encryption. In this way, the confidential smart contract via TEE is both efficient and general programmable, without being trusted. Meanwhile, the on-chain cryptographic approach does not introduce high overhead as it only authenticates and aggregates the results. We formalize the system model and security goals, and prove the correctness using the Universal Composability framework. Our implementation and evaluation on Intel SGX as the trusted hardware and Solidity as the smart contract show that our approach achieves nearly no degradation on the performance compared to non-confidential computation.