Scalable, Server-Passive, User-Anonymous Timed Release Public Key Encryption from Bilinear Pairing.
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
We consider the problem of sending messages into the future, commonly known as timed release cryptography. Existing schemes for this task either solve the relative time problem with uncontrollable, coarse-grained release time (time-lock puzzle approach) or do not provide anonymity to sender and/or receiver and are not scalable (server-based approach). Using a bilinear paring on any Gap Di#e-Hellman group, we solve this problem by giving a scalable, server-passive and user-anonymous timed release public-key encryption scheme which allows precise absolute release time specifications. Unlike the existing server-based schemes, the trusted time server in our scheme is completely passive --- no interaction between it and the sender or receiver is needed; it is even not aware of the existence of a user, thus assuring the anonymity of both the sender and receiver of a message and the privacy of the message. Besides, our scheme also has a number of desirable properties including self-authenticated time-bound key updates, a single form of update for all receivers, simple public-key renewal and key insulation, making it a scalable and appealing solution.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.005 | 0.009 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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