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"version": "1.0.0",
"dataset": "xpertsystems/cyb011-sample",
"task": "7-class attack_phase classification",
"baselines": {
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"majority_class": "evasion_attempt",
"random_guess_accuracy": 0.14285714285714285
},
"split": {
"strategy": "group-aware (GroupShuffleSplit on campaign_id, nested 70/15/15)",
"rationale": "200 campaigns x 70 timesteps each. Timesteps from the same campaign share attacker, target segment, and tier - so train/test contamination is a real risk with random splitting. ~30 test campaigns per fold.",
"events_train": 9730,
"events_val": 2170,
"events_test": 2100,
"seed": 42
},
"n_features": 37,
"label_classes": [
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"feature_space_probe",
"perturbation_craft",
"evasion_attempt",
"feedback_adaptation",
"campaign_consolidation",
"idle_dwell"
],
"class_distribution_train": {
"evasion_attempt": 5082,
"idle_dwell": 1677,
"feature_space_probe": 983,
"campaign_consolidation": 571,
"reconnaissance": 558,
"perturbation_craft": 511,
"feedback_adaptation": 348
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"class_distribution_test": {
"evasion_attempt": 1057,
"idle_dwell": 388,
"feature_space_probe": 220,
"reconnaissance": 128,
"campaign_consolidation": 116,
"perturbation_craft": 115,
"feedback_adaptation": 76
},
"oracle_excluded_features": [
"detection_outcome (perfect oracle for evasion_attempt phase)",
"detector_confidence_score (mechanical decoder for detection_outcome)",
"evasion_budget_consumed (==0 is perfect oracle for 3 early phases)"
],
"timestep_kept_as_legitimate_feature": "timestep is KEPT as a feature. It's a partial oracle for 3 phases (reconnaissance, feedback_adaptation, campaign_consolidation) but is a legitimate campaign-progress observable a defender would have at decision time. Removing it drops accuracy by ~9pp.",
"leakage_audit_note": "See leakage_diagnostic.json for the full 6-oracle-path audit, 4 unlearnable README-suggested targets, and the missing nation_state attacker tier note.",
"models": {
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"framework": "xgboost",
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"feedback_adaptation": 0.7151515151515152,
"campaign_consolidation": 0.8075471698113208,
"idle_dwell": 0.7040971168437026
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"confusion_matrix": {
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"mlp": {
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"framework": "pytorch",
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