{"id":"W4387133786","doi":"10.18280/ijsse.130412","title":"Enhancing Cyber Forensics with AI and Machine Learning: A Study on Automated Threat Analysis and Classification","year":2023,"lang":"en","type":"article","venue":"International Journal of Safety and Security Engineering","topic":"Digital and Cyber Forensics","field":"Computer Science","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Computer security; Artificial intelligence; Machine learning","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002551071,0.0000970493,0.0001638435,0.0003107397,0.00004712181,0.000177461,0.0001317714,0.00002527263,5.747503e-7],"category_scores_gemma":[0.00003690055,0.00007554028,0.00003143206,0.0003623122,0.00002193477,0.00041549,0.00008910037,0.0001797031,6.371744e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002237327,"about_ca_system_score_gemma":0.00001201047,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001032799,"about_ca_topic_score_gemma":0.00003194077,"domain_scores_codex":[0.999234,0.00001421863,0.0002207432,0.0001376832,0.0003010167,0.00009230705],"domain_scores_gemma":[0.9995369,0.00008569217,0.0000989957,0.00006233678,0.0001471699,0.00006890795],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001194045,0.0007679201,0.3881068,0.0001527726,0.01128771,0.00181333,0.05461951,0.1530203,0.003387431,0.1685819,0.000123917,0.2169443],"study_design_scores_gemma":[0.0006309752,0.0003029444,0.2557822,0.00006288275,0.00007067137,0.0001314945,0.0002025265,0.7415518,0.0001969872,0.0007029589,0.0002378694,0.0001266188],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8457246,0.00007167536,0.1529048,0.0009025638,0.0001315227,0.00005428436,0.000004837625,0.0001149912,0.00009078013],"genre_scores_gemma":[0.9991279,0.0001153347,0.0006614999,0.00003523177,0.00003301713,7.015344e-7,0.00000501535,0.000005216236,0.00001611193],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5885315,"threshold_uncertainty_score":0.3080443,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00974004396735911,"score_gpt":0.2348237360649749,"score_spread":0.2250836920976158,"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."}}