Centralized Web Application Firewall Security System
Bibliographic record
Abstract
In this paper we propose a centralized web firewall system for web application security which will provide a new type of synchronized system, which has the ability to  detect  and prevent a variety of web application attacks for a wide range of hosts at the same time , using an centralized command and control system, the attacked client then sends the information to a centralized command and control server which will distribute the attack information to all of the integrated clients connected to it. The distributed information contains all of the attack information including the type of attack, the IP address of the attacker, and the time of attack. The process of receiving the attacker's information and distributing it through the centralized web firewall is done automatically and immediately at the time of the attack. And all of the receiving clients will take actions against the threat depending on the distributed information such as banning the IP address of the attacker. The main process aims to protect multiple clients from any possible attack from the same attacker or the same type of attack. The system has been implemented to protect a real web application. Experiments showed that the attacks has been successfully prevented on multiple hosts at the time. This paper came to provide a centralized web firewall system that connect different web firewalls in order to detect and prevent different types of web attacks and work as a fully integrated system with the different clients.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".