{"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":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.002322776,0.0001037301,0.0001938645,0.0001592277,0.00150123,0.0001512962,0.0005421761,0.00003089937,0.000007606396],"category_scores_gemma":[0.00001309161,0.00008444849,0.00007192248,0.0005003943,0.0001259922,0.0003516821,0.0001792209,0.0002505096,4.553921e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004635744,"about_ca_system_score_gemma":0.00005987783,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001119521,"about_ca_topic_score_gemma":0.000003893339,"domain_scores_codex":[0.9984707,0.00007850453,0.0004142337,0.0002391528,0.0005449287,0.0002524453],"domain_scores_gemma":[0.9992691,0.0001125738,0.0003642644,0.0001028848,0.00005227758,0.00009891958],"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":[0.0002597968,0.00004377365,0.000009078233,0.00003887553,0.00001079459,0.000008738697,0.002629884,0.4593241,0.006065493,0.02237576,0.001104819,0.5081289],"study_design_scores_gemma":[0.0002170951,0.0005491596,0.00001521429,0.00001364229,0.00001085355,0.0002933207,0.0004366409,0.987198,0.001587241,0.00889301,0.0006834019,0.0001024464],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3168364,0.0001686196,0.6797808,0.0004398776,0.002431196,0.0001567031,0.000001312277,0.0000321551,0.0001528711],"genre_scores_gemma":[0.9910908,0.00001004199,0.007665475,0.0002118112,0.0009926551,0.00001658923,3.325939e-7,0.000004377462,0.000007885376],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6742544,"threshold_uncertainty_score":0.9997987,"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."}}