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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.006 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), 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".