SDN-Guard: DoS Attacks Mitigation in SDN Networks
Why this work is in the frame
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Bibliographic record
Abstract
Software Defined Networking (SDN) has recently emerged as a new networking technology offering an unprecedented programmability that allows network operators to dynamically configure and manage their infrastructures. The main idea of SDN is to move the control plane into a central controller that is in charge of taking all routing decisions in the network. However, despite all the advantages offered by this technology, Deny-of-Service (DoS) attacks are considered a major threat to such networks as they can easily overload the controller processing and communication capacity and flood switch CAM tables, resulting in a critical degradation of the overall network performance. To address this issue, we propose in this paper SDN-Guard, a novel scheme able to efficiently protect SDN networks against DoS attacks by dynamically (1) rerouting potential malicious traffic, (2) adjusting flow timeouts and (3) aggregating flow rules. Realistic experiments using Mininet show that the proposed solution succeeds in minimizing by up to 32% the impact of DoS attacks on~the controller performance, switch memory usage and control plane bandwidth and thereby maintaining acceptable network performance during such attacks.
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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 | 0.000 | 0.000 |
| 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 | 0.001 | 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 it