{"id":"W4405907177","doi":"10.1109/msec.2024.3492132","title":"ThreatScout: Automated Threat Hunting Solution Using Machine Reasoning","year":2024,"lang":"en","type":"article","venue":"IEEE Security & Privacy","topic":"Advanced Malware Detection Techniques","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ericsson (Canada); Concordia University","funders":"","keywords":"Computer science; Artificial intelligence; Automated reasoning; Computer security","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001128404,0.00164659,0.0005374185,0.001547243,0.001084193,0.001761566,0.002029859,0.001658459,0.006827414],"category_scores_gemma":[0.004373395,0.0004753746,0.001635369,0.0004433909,0.0007149823,0.002379195,0.002214426,0.002251558,0.002378082],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000618159,"about_ca_system_score_gemma":0.001823621,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003035208,"about_ca_topic_score_gemma":0.005630004,"domain_scores_codex":[0.998638,0.000250421,0.00007896801,0.0002390976,0.0006702808,0.0001233426],"domain_scores_gemma":[0.9984344,0.0008061982,0.000152999,0.0002709856,0.0002505416,0.00008491625],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0006296607,0.001416174,0.007733026,0.001398261,0.00048435,0.001767742,0.0008078187,0.1189545,0.05015496,0.02960115,0.1092442,0.677808],"study_design_scores_gemma":[0.000127643,0.0002288276,0.001571226,0.0001532458,0.0001479233,0.000889881,0.0002831348,0.8759992,0.02583738,0.04086212,0.05379916,0.0001002912],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.04118835,0.0009206158,0.8502986,0.002007787,0.0005295252,0.0009238783,0.001839705,0.07967559,0.02261592],"genre_scores_gemma":[0.2356364,0.0005205944,0.7496192,0.001036594,0.00009995393,0.0003068387,0.004047991,0.001189909,0.007542504],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.006827414,"threshold_uncertainty_score":0.02283996,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02091807385054465,"score_gpt":0.3121394986568999,"score_spread":0.2912214248063553,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}