Functionality-based application confinement: A parameterised and hierarchical approach to policy abstraction for rule-based application-oriented access controls
Bibliographic record
Abstract
Access controls are traditionally designed to protect resources from users, and consequently make access decisions based on the identity of the user, treating all processes as if they are acting on behalf of the user that runs them. However, this user-oriented approach is insufficient at protecting against contemporary threats, where security compromises are often due to applications running malicious code, either due to software vulnerabilities or malware. Application-oriented access controls can mitigate this threat by managing the authority of individual applications. Rule-based application-oriented access controls can restrict applications to only allow access to the specific finely-grained resources required for them to carry out their tasks, and thus can significantly limit the damage that can be caused by malicious code. Unfortunately existing application-oriented access controls have policy complexity and usability problems that have limited their use. \n \nThis thesis proposes a new access control model, known as functionality-based application confinement (FBAC). The FBAC model has a number of unique features designed to overcome problems with previous approaches. Policy abstractions, known as functionalities, are used to assign authority to applications based on the features they provide. Functionalities authorise elaborate sets of finely grained privileges based on high-level security goals, and adapt to the needs of specific applications through parameterisation. FBAC is hierarchical, which enables it to provide layers of abstraction and encapsulation in policy. It also simultaneously enforces the security goals of both users and administrators by providing discretionary and mandatory controls. \n \nAn LSM-based (Linux security module) prototype implementation, known as FBAC-LSM, was developed as a proof-of-concept and was used to evaluate the new model and associated techniques. The policy requirements of over one hundred applications were analysed, and policy abstractions and application policies were developed. Analysis showed that the FBAC model is capable of representing the privilege needs of applications. The model is also well suited to automaiii tion techniques that can in many cases create complete application policies a priori, that is, without first running the applications. This is an improvement over previous approaches that typically rely on learning modes to generate policies. A usability study was conducted, which showed that compared to two widely-deployed alternatives (SELinux and AppArmor), FBAC-LSM had significantly higher perceived usability and resulted in significantly more protective policies. Qualitative analysis was performed and gave further insight into the issues surrounding the usability of application-oriented access controls, and confirmed the success of the FBAC model.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".