| Summary: | Abstract Many applications are built upon private algorithms, and executing them in untrusted, remote environments poses confidentiality issues. To some extent, these problems can be addressed by ensuring the use of secure hardware in the execution environment; however, an insecure software-stack can only provide limited algorithm secrecy. This paper aims to address this problem, by exploring the components of the Trusted Computing Base (TCB) in hardware-supported enclaves. First, we provide a taxonomy and give an extensive understanding of trade-offs during secure enclave development. Next, we present a case study on existing secret-code execution frameworks; which have bad TCB design due to processing secrets with commodity software in enclaves. This increased attack surface introduces additional footprints on memory that breaks the confidentiality guarantees; as a result, the private algorithms are leaked. Finally, we propose an alternative approach for remote secret-code execution of private algorithms. Our solution removes the potentially untrusted commodity software from the TCB and provides a minimal loader for secret-code execution. Based on our new enclave development paradigm, we demonstrate three industrial templates for cloud applications: ① computational power as a service, ② algorithm querying as a service, and ③ data querying as a service.
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