Graphene-SGX: A Practical Library OS for Unmodified Applications on SGX

By Chia-che Tsai, Donald E. Porter, Mona Vij. USENIX Annual Technical Conference, 2017

635 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/e2d0bf45ac63944a2fd8d3174b366dd08968a710

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Citations in the corpus

Keystone: an open framework for architecting trusted execution environments (2020, methodology): “Thus, to execute arbitrary applications, the systems built on SGXv1 have inflated the Trusted Computing Base (TCB) and are forced to implement complex workarounds [18, 22, 31].”
Plundervolt: Software-based Fault Injection Attacks against Intel SGX (2020, methodology): “For comparison, the trusted runtime part of Microsoft’s OpenEn-clave SDK [48] contains 203 multiplications, while Graphene-SGX’s [67] libpal-Linux-SGX.so features 71 mul / imul instructions.”
Chiron: Privacy-preserving Machine Learning as a Service (2018, background): “Haven [24], SCONE [22], and GrapheneSGX [29] provide an environment to support unmodified legacy applications.”
SGX-LKL: Securing the Host OS Interface for Trusted Execution (2019, methodology): “Similar to other TEE runtime systems [8, 95], SGX-LKL includes a libc implementation to support unmodified binaries that are dynamically linked against libc.”
EnclaveDB: A Secure Database Using SGX (2018, methodology): “Haven [14] and Graphene [24] use Intel SGX for isolation and run unmodified applications by bundling them with an inenclave library OS.”
SgxPectre: Stealing Intel Secrets from SGX Enclaves Via Speculative Execution (2018, methodology): “In particular, we have developed an automated program analysis tool that symbolically executes the enclave code to examine code patterns in SGX runtimes, and have identified those code patterns in every runtime library we have examined, including Intel’s SGX SDK [36], Rust-SGX [14], GrapheneSGX [77]”
Telling Your Secrets without Page Faults: Stealthy Page Table-Based Attacks on Enclaved Execution (2017, methodology): “Graphene-SGX [45] – like other recently proposed SGX-based shielding systems including Haven [3], Panoply [41], and SCONE [2] – improves over this situation by not only protecting libOS instances from each other, but also from a malicious host operating system.”
Graviton: Trusted Execution Environments on GPUs (2018, methodology): “Our implementation does not yet use SGX for hosting the user application and GPU runtime—porting the stack to SGX can be achieved using SGX-specific containers [5, 39, 44], and is outside the scope of this work.”