{"id":"W4394566753","doi":"10.15866/irecap.v13i6.24482","title":"Examining Machine Learning Models Toward Green Network Intrusion Detection","year":2023,"lang":"en","type":"article","venue":"International Journal on Communications Antenna and Propagation (IRECAP)","topic":"Network Security and Intrusion Detection","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"École de Technologie Supérieure; Université de Montréal; Polytechnique Montréal","funders":"","keywords":"Computer science; Intrusion detection system; Artificial intelligence; Machine learning; Intrusion; Geology","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":[0.006264203,0.0009497246,0.0005966702,0.001937071,0.0004942154,0.001619376,0.0009753036,0.0009830049,0.000869519],"category_scores_gemma":[0.01943706,0.000233089,0.0006682452,0.00120953,0.0004975501,0.001712575,0.0005654554,0.001661034,0.0003253933],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001360043,"about_ca_system_score_gemma":0.001211742,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01164447,"about_ca_topic_score_gemma":0.01091861,"domain_scores_codex":[0.9982855,0.001025262,0.00008117751,0.0001988365,0.00030019,0.0001090079],"domain_scores_gemma":[0.9792926,0.01692562,0.0007957026,0.000662739,0.002127056,0.000196319],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001262029,0.0003460951,0.01764332,0.00009470298,0.0001018316,0.00004984751,0.00009479931,0.9271235,0.0004537865,0.003737801,0.001926537,0.0483016],"study_design_scores_gemma":[0.000002353513,0.00002750674,0.0007187006,0.000009868863,0.000005947699,0.000006950556,0.00002078707,0.9973058,0.0002103342,0.00151726,0.0001717569,0.000002732874],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7782661,0.00268472,0.2067995,0.003593317,0.0002070933,0.0002008709,0.0007495078,0.0009937839,0.006505127],"genre_scores_gemma":[0.9504986,0.0006120178,0.04669983,0.0001923496,0.00005921578,0.00007292646,0.0008221027,0.00003569526,0.001007164],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01164447,"threshold_uncertainty_score":0.03312868,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07475618957483281,"score_gpt":0.278191624633352,"score_spread":0.2034354350585192,"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."}}