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5 Commits

Author SHA1 Message Date
Jacquin Antoine
f88b739992 feat(e2e): add distributed E2E test framework with parametric traffic generation 
Add run-e2e-test.sh with CLI parameters (--hits, --http-ratio, --dns, --tls,
--src-ips, --keep-analysis, --up) for configurable traffic generation. Traffic
runs from VM endpoints with multiple source IPs (alias IPs on eth0) to produce
distinct sessions for the ML pipeline. Fix curl TLS flags (--tlsv1.2 instead
of --tls-v1-2), skip redundant local verification in distributed mode, and
fix dashboard is_available() cache that never retried after ClickHouse recovery.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
 2026-04-15 00:09:32 +02:00
Jacquin Antoine
7894d39f1c feat(ml): replace logistic regression with MLP fusion and KS drift with ADWIN online learning 
Replace the LogisticRegression meta-learner with a PyTorch MetaFusionMLP
(Linear(3,16)->BN->ReLU->Dropout->Linear(16,1)->Sigmoid) for non-linear
fusion of EIF, NF, and XGBoost scores. Replace KS-test + quantile digest
drift detection with ADWIN (adaptive sliding window, Hoeffding bound).
Replace weekly XGBoost batch retraining with River HoeffdingAdaptiveTree
for incremental online learning (learn_one per cycle). Update all thesis
documentation sections (2.4.2c, 2.4.3, 3.8, discussion, conclusion).

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
 2026-04-13 16:32:34 +02:00
Jacquin Antoine
c6cb12981c feat(ml): replace NetworkX/Louvain with PyTorch Geometric GraphSAGE for fleet detection 
Rewrite fleet.py to use a GNN-based approach: nodes are src_ip with ML feature
vectors, edges connect IPs sharing (JA4, ASN) pairs, GraphSAGE (2 SAGEConv
layers, in→64→32) produces 32D embeddings clustered by HDBSCAN. PyG NeighborLoader
activates for >50k nodes. Update thesis docs (§5.2, §6.4, §2, §8) to reflect
GraphSAGE architecture and PyG scalability.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
 2026-04-13 15:45:34 +02:00
Jacquin Antoine
c1821dcbc4 feat(ml): replace Autoencoder with RealNVP Normalizing Flow and add SessionTransformer embeddings 
Replace TrafficAutoEncoder (MSE reconstruction scoring) with TrafficNormalizingFlow
(RealNVP via FrEIA, 4 affine coupling blocks, anomaly score = -log p(x)) for
mathematically rigorous density estimation. Add SessionTransformer module producing
32-dimensional sequence embeddings from raw HTTP request sequences (path, method,
timing) via a lightweight TransformerEncoder, replacing path_transition_entropy and
cadence_cv features. Update thesis documentation sections 2.4.2b and 3.8 accordingly.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
 2026-04-13 15:11:21 +02:00
Jacquin Antoine
0e5f94dd0d docs: restructure thesis into chapter files with corrected references 
Split monolithic thesis into separate chapter markdown files under
docs/thesis/. Remove fabricated bibliography entries, correct inflated
claims, add GNN/Transformers section, and rename MetaLearner to Fusion LR.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
 2026-04-13 13:51:38 +02:00