Could network view inconsistency affect virtualized network security functions?
Bibliographic record
Abstract
With SDN increasingly becoming an enabling technology for NFV in the cloud, many virtualized network functions need to monitor the network state in order to function properly. An outdated network view at the controllers can impact the performance of those virtualized network functions. In earlier work, we identified two main factors contributing to an outdated network view in the case of a load-balancer: network state collection and controllers' state distribution. In this paper, we anticipate that the impact might be different in case of security functions. Therefore, we study the impact of an outdated network view on an anomaly-based IDS application. In particular, we investigate: (1) the impact of controllers' state distribution on the performance of a distributed IDS in the case of a DDoS attack; and (2) the impact of network state collection on the performance of an IDS in the case of a TCP SYN flood attack. Our results showed that the outdated network view had negative impact on the IDS anomaly-detection performance in the experiments that we conducted.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.004 | 0.007 |
| Research integrity | 0.001 | 0.002 |
| 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".