Developing a Secure Web Application Using OWASP Guidelines
Bibliographic record
Abstract
Developing a secure Web application is very difficult task. Therefore developers need a guideline to help them to develop a secure Web application. Guideline can be used as a checklist for developer to achieve minimum standard of secure Web application. This study evaluates how good is OWASP guideline in helping developer to build secure Web application. The developed system is then tested using code auditing and penetration testing to identify the achievement of the system security for the application. After applying the testing techniques from Open Source Security Testing Methodology (OSSTMM) on the Top Ten Critical vulnerabilities as defined by OWASP, a standard measure score are calculated. The score is used to decide on the level of security of the developed web application. A high percentage score would indicate that the guideline helps in building a secured web application. Hence, the result proved that OWASP guideline is effective in ensuring the trustworthiness of the system and can be used as referral by other web developer especially in developing applications for a university.
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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 | 0.004 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".