PolicyVis: firewall security policy visualization and inspection
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Firewalls have an important role in network security. However, managing firewall policies is an extremely complex task because the large number of interacting rules in single or distributed firewalls significantly increases the possibility of policy misconfiguration and network vulnerabilities. Moreover, due to low-level representation of firewall rules, the semantic of firewall policies become very incomprehensible, which makes inspecting of firewall policy's properties a difficult and error-prone task. In this paper, we propose a tool called PolicyVis which visualizes firewall rules and policies in such a way that efficiently enhances the understanding and inspecting firewall policies. Unlike previous works that attempt to validate or inspect firewall rules based on specific queries or errors, our approach is to visualize firewall policies to enable the user to place general inquiry such as does my policy what I intend to do unrestrictedly. We describe the design principals in PolicyVis and provide concepts and examples dealing with firewall policy's properties, rule anomalies and distributed firewalls. As a result, PolicyVis considerably simplifies the management of firewall policies and hence effectively improves the network security.
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.
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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 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 it