Next Generation Application-Layer DDoS Defences: Applying the Concepts of Outlier Detection in Data Streams with Concept Drift
Bibliographic record
Abstract
The existing state-of-the art in the field of application-layer DDoS protection is generally designed, and thus effective, only for static Web-domains. To the best of our knowledge, this paper is the first one to study the problem of application-layer DDoS defense in Web-sites of dynamic content and/or organization and under non-trivial bot (i.e., Attack) behavior. The main contributions of the paper are threefold: 1) we provide a detailed taxonomy of the existing and next-generation application-layer HTTP-based DDoS attacks, 2) we discuss the relevance of a branch of data mining theory -- known as data streams with concept drift -- to the problem of application-layer DDoS defense in dynamic Web-domains, 3) we present the outline of our next-generation anti-DDoS system that is intended for dynamic Web-domains facing different sophisticated variants of application-layer DDoS attacks. The paper also includes some of our preliminary experimental results concerning the detection of malicious Web-users/sessions using the proposed system.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 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".