Security Evaluation and Hardening of Free and Open Source Software (FOSS)
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
Recently, Free and Open Source Software (FOSS) has emerged as an alternative to Commercial-Off- The-Shelf (COTS) software. Now, FOSS is perceived as a viable long-term solution that deserves careful consideration because of its potential for significant cost savings, improved reliability, and numerous advantages over proprietary software. However, the secure integration of FOSS in IT infrastructures is very challenging and demanding. Methodologies and technical policies must be adapted to reliably compose large FOSS-based software systems. A DRDC Valcartier-Concordia University feasibility study completed in March 2004 concluded that the most promising approach for securing FOSS is to combine advanced design patterns and Aspect-Oriented Programming (AOP). Following the recommendations of this study a three years project have been conducted as a collaboration between Concordia University, DRDC Valcartier, and Bell Canada. This paper aims at presenting the main contributions of this project. It consists of a practical framework with the underlying solid semantic foundations for the security evaluation and hardening of FOSS.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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