Elasticlave: An Efficient Memory Model for Enclaves
This addresses the slow-down problem in TEEs for secure computing applications, offering a significant performance boost while maintaining security, though it is an incremental improvement on existing memory models.
The paper tackles the performance overhead in trusted-execution environments (TEEs) like Intel SGX by introducing Elasticlave, a memory model that allows selective and temporary memory sharing between enclaves and the OS, eliminating expensive data copies. It reports 1 to 2 orders of magnitude performance improvements over the spatial isolation model in a prototype on a RISC-V core.
Trusted-execution environments (TEE), like Intel SGX, isolate user-space applications into secure enclaves without trusting the OS. Thus, TEEs reduce the trusted computing base, but add one to two orders of magnitude slow-down. The performance cost stems from a strict memory model, which we call the spatial isolation model, where enclaves cannot share memory regions with each other. In this work, we present Elasticlave---a new TEE memory model that allows enclaves to selectively and temporarily share memory with other enclaves and the OS. Elasticlave eliminates the need for expensive data copy operations, while offering the same level of application-desired security as possible with the spatial model. We prototype Elasticlave design on an RTL-designed cycle-level RISC-V core and observe 1 to 2 orders of magnitude performance improvements over the spatial model implemented with the same processor configuration. Elasticlave has a small TCB. We find that its performance characteristics and hardware area footprint scale well with the number of shared memory regions it is configured to support.