Could Network View Inconsistency Affect Virtualized Network Security\n Functions?
Bibliographic record
Abstract
With SDN increasingly becoming an enabling technology for NFV in the cloud,\nmany virtualized network functions need to monitor the network state in order\nto function properly. An outdated network view at the controllers can impact\nthe performance of those virtualized network functions. In earlier work, we\nidentified two main factors contributing to an outdated network view in the\ncase of a load-balancer: network state collection and controllers' state\ndistribution. In this paper, we anticipate that the impact might be different\nin case of security functions. Therefore, we study the impact of an outdated\nnetwork view on an anomaly-based IDS application. In particular, we\ninvestigate: (1) the impact of controllers' state distribution on the\nperformance of a distributed IDS in the case of a DDoS attack; and (2) the\nimpact of network state collection on the performance of an IDS in the case of\na TCP SYN flood attack. Our results showed that the outdated network view had\nnegative impact on the IDS anomaly-detection performance in the experiments\nthat we conducted.\n
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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 | 0.005 | 0.052 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.006 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".