{"id":"W4389193083","doi":"10.22215/etd/2023-15855","title":"Leveraging the MITRE ATT&amp;CK Framework to Enhance Organizations Cyberthreat Detection Procedures","year":2023,"lang":"en","type":"dissertation","venue":"","topic":"Information and Cyber Security","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Adversary; Computer security; Computer science; Adversarial system; Threat model; Artificial intelligence","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001930824,0.0002886291,0.0001947896,0.0002385955,0.0007209731,0.0006284566,0.001101718,0.0002715273,0.0001346704],"category_scores_gemma":[0.0005511687,0.000221844,0.00008380079,0.002383341,0.0000129493,0.0004808526,0.0001334293,0.0004779615,0.002378512],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009202588,"about_ca_system_score_gemma":0.0002678761,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001914732,"about_ca_topic_score_gemma":0.006995613,"domain_scores_codex":[0.9982776,0.00004653797,0.000397841,0.0004498374,0.0004957429,0.0003324299],"domain_scores_gemma":[0.9982753,0.0001261073,0.0001845615,0.0007685558,0.0005421491,0.000103301],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00006216891,0.0002073128,0.0003044218,0.0008710384,0.0003329679,0.000009290895,0.4843152,0.001555576,0.001740125,0.1663928,0.1069042,0.2373049],"study_design_scores_gemma":[0.001066709,0.0004498542,0.0923117,0.00461507,0.0004152497,0.000162012,0.05185782,0.03055037,0.2990105,0.1197422,0.3895507,0.01026792],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04406039,0.0001037343,0.9242982,0.003252061,0.004829132,0.001053457,0.000005223733,0.001700846,0.02069701],"genre_scores_gemma":[0.8401482,0.0001279648,0.0178807,0.004907163,0.0004895076,0.0003449724,0.0004249993,0.0001037111,0.1355727],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9064174,"threshold_uncertainty_score":0.9983982,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01003095632049619,"score_gpt":0.2820432931542398,"score_spread":0.2720123368337436,"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."}}