{"id":"W4400185172","doi":"10.2139/ssrn.4878189","title":"MACHINE LEARNING IN CYBERSECURITY: HARNESSING AI FOR DEFENSE","year":2024,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Network Security and Intrusion Detection","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Wycliffe College","funders":"","keywords":"Computer security; Computer science; Business","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":[0.002411615,0.0005025642,0.0005713421,0.001090474,0.0004896704,0.003411041,0.0009237551,0.001332675,0.003000375],"category_scores_gemma":[0.007752276,0.0002504216,0.0003958087,0.0007992743,0.003459567,0.004817485,0.001483167,0.002997242,0.0008326454],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007859595,"about_ca_system_score_gemma":0.001029124,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001151223,"about_ca_topic_score_gemma":0.001233726,"domain_scores_codex":[0.9989851,0.0005435167,0.00003974089,0.000122498,0.0002566968,0.0000523683],"domain_scores_gemma":[0.9924442,0.006105769,0.0002117812,0.0006613159,0.0003974856,0.000179355],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0000989804,0.0002286207,0.004200485,0.0008335943,0.0001677114,0.0001150531,0.0004966954,0.03676225,0.004835594,0.5115631,0.01417351,0.4265243],"study_design_scores_gemma":[0.00001943157,0.00008727806,0.000749336,0.0002316845,0.00002570817,0.00007436949,0.0001718406,0.1258702,0.001807243,0.8398159,0.03111579,0.00003127848],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"review","genre_scores_codex":[0.04545649,0.06643815,0.7106742,0.06586203,0.001695373,0.0001062657,0.0002125208,0.00123963,0.1083153],"genre_scores_gemma":[0.7954636,0.02509094,0.1638411,0.003640369,0.001841879,0.0001150917,0.0001348827,0.000157839,0.009714273],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.003411041,"threshold_uncertainty_score":0.01275402,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008152610680445472,"score_gpt":0.2454318939111332,"score_spread":0.2372792832306877,"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."}}