Secure Processors Part II: Intel SGX Security Analysis and MIT Sanctum Architecture
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This manuscript is the second in a two part survey and analysis of the state of the art in secure processor systems, with a specific focus on remote software attestation and software isolation. The first part established the taxonomy and prerequisite concepts relevant to an examination of the state of the art in trusted remote computation: attested software isolation containers (enclaves). This second part extends Part I’s description of Intel’s Software Guard Extensions (SGX), an available and documented enclave-capable system, with a rigorous security analysis of SGX as a system for trusted remote computation. This part documents the authors’ concerns over the shortcomings of SGX as a secure system and introduces the MIT Sanctum processor developed by the authors: a system designed to offer stronger security guarantees, lend itself better to analysis and formal verification, and offer a more straightforward and complete threat model than the Intel system, all with an equivalent programming model. This two part work advocates a principled, transparent, and well-scrutinized approach to system design, and argues that practical guarantees of privacy and integrity for remote computation are achievable at a reasonable design cost and performance overhead.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it