{"id":"W4400041843","doi":"10.4108/eetsis.6111","title":"Comprehensive Review of Advanced Machine Learning Techniques for Detecting and Mitigating Zero-Day Exploits","year":2024,"lang":"en","type":"article","venue":"ICST Transactions on Scalable Information Systems","topic":"Network Security and Intrusion Detection","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University Canada West","funders":"","keywords":"Exploit; Zero (linguistics); Computer science; Machine learning; Artificial intelligence; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007389022,0.0001450358,0.000253951,0.0002744561,0.0003162246,0.0002516564,0.0001558055,0.00008173151,0.000005582132],"category_scores_gemma":[0.00004904727,0.0001364633,0.00008893543,0.0006276294,0.00002668271,0.002401449,0.00001043209,0.0002716172,0.00001181839],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005481856,"about_ca_system_score_gemma":0.0000344087,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003093712,"about_ca_topic_score_gemma":0.000001442761,"domain_scores_codex":[0.9986066,0.0001037902,0.0006771142,0.0001821804,0.0002598022,0.0001704634],"domain_scores_gemma":[0.9988196,0.0003999402,0.0002147688,0.0001929854,0.000315213,0.0000574475],"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":[0.00001322884,0.00001411569,0.000001809777,0.01492486,0.00004155616,5.038643e-7,0.001545741,0.008422513,0.001499607,0.002530229,0.000102554,0.9709033],"study_design_scores_gemma":[0.0002303251,0.0003036313,0.00000317993,0.01404387,0.00002188328,0.00006359305,0.0003400704,0.7316932,0.02759764,0.0001551384,0.2253111,0.000236352],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0006977414,0.00835151,0.9884281,0.0001639042,0.0006737008,0.0007924011,0.00001962522,0.0004672017,0.0004058728],"genre_scores_gemma":[0.9647232,0.01057462,0.0236867,0.0003323136,0.00006245303,0.0004688028,0.00001972267,0.00002070969,0.0001115136],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9706669,"threshold_uncertainty_score":0.5564812,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01680321999606444,"score_gpt":0.2563561254937192,"score_spread":0.2395529054976548,"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."}}