{"id":"W4285357590","doi":"10.4018/ijcini.20211001.oa9","title":"Cyber Threat Hunting","year":2022,"lang":"en","type":"article","venue":"International Journal of Cognitive Informatics and Natural Intelligence","topic":"Complex Network Analysis Techniques","field":"Physics and Astronomy","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada; Canadian Nuclear Laboratories","funders":"Lawrence Berkeley National Laboratory; Government of Canada; Canadian Nuclear Laboratories; Defense Advanced Research Projects Agency; Mitacs; University of Manitoba","keywords":"Computer science; Computer security; Situation awareness; Visualization; Intelligence analysis; Event (particle physics); Artificial intelligence; Cyber-attack; Human–computer interaction; Machine learning","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003580328,0.000095535,0.0001523039,0.0002042542,0.0001355479,0.00009201093,0.0003254073,0.00000965403,0.0006864768],"category_scores_gemma":[0.00003106999,0.00008231633,0.0001248743,0.000134474,0.0000516276,0.0003573703,0.0002964818,0.0004026447,0.00000389056],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003410131,"about_ca_system_score_gemma":0.00003340748,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002665916,"about_ca_topic_score_gemma":0.000001147778,"domain_scores_codex":[0.9988036,0.00002900688,0.0005553555,0.00004879854,0.0004421363,0.0001211359],"domain_scores_gemma":[0.9984683,0.0002452126,0.0005440527,0.00004157495,0.0006599622,0.00004088016],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001762205,0.000146923,0.0368152,0.000005483049,0.0009145281,0.00002124691,0.003413744,0.0009692816,0.0001007656,0.03940595,0.0006441519,0.9173865],"study_design_scores_gemma":[0.00361099,0.001902605,0.02829734,0.001590644,0.001017887,0.001962655,0.1226877,0.3328949,0.05196653,0.3922238,0.05886842,0.002976622],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.824409,0.0005461721,0.1625446,0.0002372831,0.000842725,0.0001279799,0.0000472121,0.00001694767,0.01122812],"genre_scores_gemma":[0.9975699,0.00003568969,0.001818431,0.0002148111,0.0002341619,0.000004058264,0.00001796566,0.000005098609,0.00009995048],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9144099,"threshold_uncertainty_score":0.7516439,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01291636000388051,"score_gpt":0.3009066349432626,"score_spread":0.2879902749393821,"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."}}