Schema‐level access control policies for XML documents
Bibliographic record
Abstract
Purpose The purpose of this paper is to consider the secure publishing of XML documents, where a single copy of an XML document is disseminated and a stated role‐based access control policy (RBACP) is enforced via selective encryption. It describes a more efficient solution over previously proposed approaches, in which both policy specification and key generation are performed once, at the schema‐level. In lieu of the commonly used super‐encryption technique, in which nodes residing in the intersection of multiple roles are encrypted with multiple keys, it describes a new approach called multi‐encryption that guarantees each node is encrypted at most once. Design/methodology/approach This paper describes two alternative algorithms for key generation and single‐pass algorithms for multi‐encrypting and decrypting a document. The solution typically results in a smaller number of keys being distributed to each user. Findings The paper proves the correctness of the presented algorithms, and provides experimental results indicating the superiority of multi‐encryption over super‐encryption, in terms of encryption and decryption time requirements. It also demonstrates the scalability of the approach as the size of the input document and complexity of the schema‐level RBACP are increased. Research limitations/implications An extension of this work involves designing and implementing re‐usability of keyrings when a schema or ACP is modified. In addition, more flexible solutions for handling cycles in schema graphs are possible. The current solution encounters difficulty when schema graphs are particularly deep and broad. Practical implications The experimental results indicate that the proposed approach is scalable, and is applicable to scenarios in which XML documents conforming to a common schema are to be securely published. Originality/value This paper contributes to the efficient implementation of secure XML publication systems.
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 | 0.001 | 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 | 0.001 | 0.009 |
| Open science | 0.002 | 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".