Komodo: Using verification to disentangle secure-enclave hardware from software

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How researchers see this paper

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DISCO: Dynamic and Invariant Sensitive Channel Obfuscation for deep neural networks (2020, background): “For the former, distributed learning techniques such as federated learning [6, 7] and split learning [8, 9] are used, where clients communicate with a centralized server using weights and activations and the latter relies on homomorphic encryption [10, 11] and secure enclaves [12, 13].”
Efficient Deep Learning on Multi-Source Private Data (2018, background): “, encryption) , a secure random number generator, and a trusted monitor which manages the enclave’s interaction with the untrusted world [11].”
Keystone: an open framework for architecting trusted execution environments (2020, methodology): “Keystone uses a standard scheme to bind the attestation with a secure channel construction [41, 58] by including limited arbitrary data (e.g., Diffie-Hellman key parameters) in the signed attestation report.”
This Paper Is Included in the Proceedings of the 12th Usenix Symposium on Operating Systems Design and Implementation (osdi '16). Ryoan: a Distributed Sandbox for Untrusted Computation on Secret Data Ryoan: a Distributed Sandbox for Untrusted Computation on Secret Data (unknown): “Komodo [27] uses formally verified software to provide an enclave abstraction on top of TrustZone.”