Bibliographic record
Abstract
For users in possession of password-protected encrypted data in persistent storage (i.e., “data at rest”), an obvious problem is that the password may be extracted by an adversary through dictionary attacks, or by coercing the user. Traditional full disk encryption (FDE) or plausibly deniable encryption cannot adequately address such situations. Therefore, making data verifiably inaccessible in a stealthy and quick fashion may be the preferred choice, specifically for users, such as government/corporate agents, journalists, and human rights activists with highly confidential secrets, when caught and interrogated in a hostile territory. Using secure storage on a trusted platform module (TPM) and modern CPU's trusted execution mode (e.g., Intel TXT), we design Gracewipe to enable secure and verifiable deletion of encryption keys through a special deletion password. When coerced, a user can fake compliance and enter the deletion password; and then, the user can prove to the adversary that Gracewipe has been executed and the real key is no longer available (through a TPM quote), hoping for a favorable situation (e.g., end of torture). To unlock the target encryption key, the adversary can only guess passwords through the valid Gracewipe environment with a high-risk of triggering deletion of the real key. Based on our two primary Gracewipe prototypes (i.e., software-based FDE with TrueCrypt and hardware-based FDE with self-encrypting drive), we also design and implement an extended family of unlocking schemes for triggering deletion, to achieve better plausibility, security and usability. We incur between 2-2.5 seconds delay during boot, and no performance penalty at run-time.
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.
How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".