Database and application security XV : IFIP TC11/WG11.3 Fifteenth Annual Working Conference on Database and Application Security, July 15-18, 2001, Niagara on the Lake, Ontario, Canada
Bibliographic record
Abstract
Preface. Part I: Keynote address. Recent Advances in Access Control Models S. Jajodia, D. Wijesekera. Part II: Role and Constraint-Based Access Control. Role-based Access Control on the Web Using LDAP J.S. Park, Gail-Joon Ahn, R. Sandhu. Constraints-based Access Control Wee Yeh Tan. Secure Role-Based Workflow Models S. Kandala, R. Sandhu. Part III: Distributed Systems. Subject Switching Algorithms for Access Control in Federated Databases J. Yang, D. Wijesekera, S. Jajodia. Efficient Damage Assessment and Repair in Resilient Distributed Database Systems Peng Liu, Xu Hao.Administering Permissions for Distributed Data: Factoring and Automated Inference A. Rosenthal, E. Sciore. State-Dependent Security Decisions for Distributed Object-Systems J. Biskup, T. Leineweber. Part IV: Information Warfare and Intrusion Detection. Reorganization of Database Log for Information Warfare Data Recovery R. Sobhan, B. Panda. Randomly Roving Agents For Intrusion Detection I.S. Moskowitz, Myong H. Kang, Li Wu Chang, G.E. Longdon. Public Telephone Network Vulnerabilities G. Lorenz, J. Keller, G. Manes, J. Hale, S. Shenoi. Part V: Relational Databases. Flexible Security Policies in SQL S. Barker, A. Rosenthal. The Inference Problem and Updates in Relational Databases C. Farkas, T.S. Toland, C.M. Eastman. Managing Classified Documents in a Relational Database A. Spalka. Part VI: Implementation Issues. A Comparison Between ConSA and Current Linux Security Implementations A. Hardy, M.S. Olivier. A Novel Approach to Certificate Revocation Management R. Mukkamala, S. Jajodia. ODAR: An On-the-fly Damage Assessment and Repair System for Commercial Database Applications P. Luenam, Peng Liu. Part VII: Multilevel Systems. An Extended Transaction Model Approach for Multilevel Secure Transaction Processing V. Atluri, R. Mukkamala. Maintaining the Confidentiality of Interoperable Databases with a Multilevel Federated Security System M. Oliva, F. Saltor. Part VIII: New Application Areas. Security Procedures for Classification Mining Algorithms T. Johnsten, V.V. Raghavan. Regulating Access to XML documents A. Gabillon, E. Bruno. Part IX: Panel and discussion. Panel on XML and Security S. Osborn, B. Thuraisingham, P. Samarati. Selected Summary of Discussions D.L. Spooner, M.S. Olivier. Index.
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 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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.074 | 0.065 |
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".