An Efficient and Flexible Scheme to Support Biometric-Based and Role-Based Access Control
Bibliographic record
Abstract
Introduced at EuroCrypt'05, threshold attribute-based encryption (thABE) is a subclass of identity-based encryption which views each identity as a set of descriptive attributes. In order to decrypt a ciphertext c encrypted for a set ω of attributes, users must have attribute keys associated with a sufficiently large subset of ω. Applications of thABE include both biometric-based and role-based cryptographic access control. This paper presents an efficient and flexible thABE scheme which is provably secure in the random oracle model. Let d be a minimal number of attributes which a decryptor must have to decipher a ciphertext. The proposed scheme requires only two pairings for decryption (instead of d pairings as in the original thABE scheme). Moreover, the new scheme enables system engineers to specify various threshold values for distinct sets of attributes. Therefore, this paper describes a practical cryptographic mechanism to support both biometric-based and role-based access control.
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 | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".