{"id":"W4226070228","doi":"10.46382/mjbas.2022.6103","title":"Artificial Neural Network Model for Intrusion Detection System","year":2022,"lang":"en","type":"article","venue":"Mediterranean Journal of Basic and Applied Sciences","topic":"Network Security and Intrusion Detection","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Artificial neural network; Computer science; Intrusion detection system; Artificial intelligence; Realization (probability); Operator (biology); Data mining; Confidentiality; Machine learning; Network security; Receiver operating characteristic; Computer security","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007820312,0.00115848,0.0008826699,0.001135193,0.0004687262,0.001467062,0.001969499,0.001857542,0.006276484],"category_scores_gemma":[0.0022971,0.0003115904,0.0008369313,0.001188907,0.0003681493,0.001226207,0.0006179891,0.001849507,0.002017557],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001217569,"about_ca_system_score_gemma":0.0008966983,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01467845,"about_ca_topic_score_gemma":0.009235425,"domain_scores_codex":[0.9992844,0.0001715336,0.00006367352,0.0002158985,0.0001818044,0.0000826671],"domain_scores_gemma":[0.9993537,0.0002604751,0.00006325038,0.00003051445,0.0002757002,0.00001638965],"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":[0.0001539521,0.0001054631,0.00374411,0.0003031364,0.0001082719,0.000297167,0.00008322527,0.9151683,0.001454902,0.01008692,0.006842638,0.06165188],"study_design_scores_gemma":[0.000004939694,0.00002102132,0.0003164849,0.00001411408,0.00001153016,0.00003841961,0.000007288978,0.9951484,0.000215918,0.002332468,0.001882007,0.000007327339],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07274164,0.008685047,0.8682481,0.002846624,0.001480739,0.0005801243,0.00439464,0.003473677,0.03754931],"genre_scores_gemma":[0.8782192,0.004342791,0.0788123,0.0004437263,0.0003208066,0.001175299,0.003925063,0.0001116112,0.0326492],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01467845,"threshold_uncertainty_score":0.02918601,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03613432046932893,"score_gpt":0.2401545251963559,"score_spread":0.2040202047270269,"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."}}