On Securing the Software Development Lifecycle in IoT RISC-V Trusted Execution Environments

TL;DR

This paper introduces a toolkit that enhances RISC-V Trusted Execution Environments by enabling secure enclave updates, migrations, and state management, with minimal performance impact, supporting IoT and automotive applications.

Contribution

It presents a modular toolkit extending RISC-V TEEs to support secure enclave lifecycle management, compatible with existing implementations like Keystone and CURE.

Findings

Negligible performance overhead (<1.5%)

Enclave downtime as low as 0.8%

Supports secure updates and migrations

Abstract

RISC-V-based Trusted Execution Environments (TEEs) are gaining traction in the automotive and IoT sectors as a foundation for protecting sensitive computations. However, the supporting infrastructure around these TEEs remains immature. In particular, mechanisms for secure enclave updates and migrations - essential for complete enclave lifecycle management - are largely absent from the evolving RISC-V ecosystem. In this paper, we address this limitation by introducing a novel toolkit that enables RISC-V TEEs to support critical aspects of the software development lifecycle. Our toolkit provides broad compatibility with existing and emerging RISC-V TEE implementations (e.g., Keystone and CURE), which are particularly promising for integration in the automotive industry. It extends the Security Monitor (SM) - the trusted firmware layer of RISC-V TEEs - with three modular extensions that enable secure enclave update, secure migration, state continuity, and trusted time. Our implementation demonstrates that the toolkit requires only minimal interface adaptation to accommodate TEE-specific naming conventions. Our evaluation results confirm that our proposal introduces negligible performance overhead: our state continuity solution incurs less than 1.5% overhead, and enclave downtime remains as low as 0.8% for realistic applications with a 1 KB state, which conforms with the requirements of most IoT and automotive applications.