CURE: A Security Architecture with CUstomizable and Resilient Enclaves
Raad Bahmani, Ferdinand Brasser, Ghada Dessouky, Patrick Jauernig,, Matthias Klimmek, Ahmad-Reza Sadeghi, Emmanuel Stapf

TL;DR
CURE introduces a flexible security architecture with customizable enclaves, supporting diverse application needs and enhanced protection against side-channel attacks, while maintaining minimal hardware overhead.
Contribution
It is the first architecture to offer multiple enclave types with resource isolation and support for emerging applications, addressing key limitations of existing TEEs.
Findings
Implements CURE on RISC-V with 15.33% performance overhead
Supports multiple enclave types for flexible security
Provides resource isolation for peripherals and cores
Abstract
Security architectures providing Trusted Execution Environments (TEEs) have been an appealing research subject for a wide range of computer systems, from low-end embedded devices to powerful cloud servers. The goal of these architectures is to protect sensitive services in isolated execution contexts, called enclaves. Unfortunately, existing TEE solutions suffer from significant design shortcomings. First, they follow a one-size-fits-all approach offering only a single enclave type, however, different services need flexible enclaves that can adjust to their demands. Second, they cannot efficiently support emerging applications (e.g., Machine Learning as a Service), which require secure channels to peripherals (e.g., accelerators), or the computational power of multiple cores. Third, their protection against cache side-channel attacks is either an afterthought or impractical, i.e., no…
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Taxonomy
TopicsSecurity and Verification in Computing · Cloud Data Security Solutions · Advanced Memory and Neural Computing
