Validation of network simulation model and scalability tests using example malware
Bibliographic record
Abstract
The design of a new behavioral simulator, under the Cyber Army Modeling and Simulation (CyAMS) program features the ability to model various cyber effects including propagation of malicious software. Previous work is expanded using data from both an emulated network, and the validated ns-3 simulation model. Behavioral modeling is used to break up the network and applications into individual behaviors, allowing for accurate mapping between simulators, and the emulated applications. By scaling the previous validation tests beyond the limit of the emulation network, the ns-3 model can show potential scalability, while being used to validate the new CyAMS simulator. Results demonstrate that the CyAMS simulation model is capable of matching both the emulation based experiments and the previous ns-3 validation experiment results. In addition, several tests show the potential scaling power of the CyAMS model including a test featuring ~1 billion virtual hosts. The scalability test results show the potential for the CyAMS simulator to scale to a global size network.
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.
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 | 0.001 | 0.001 |
| 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 | 0.000 |
| 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 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".