{"id":"W4288968100","doi":"10.5539/nct.v7n1p55","title":"An overview of Intrusion Detection within an Information System: The Improvment by Process Mining","year":2022,"lang":"en","type":"article","venue":"Network and Communication Technologies","topic":"Business Process Modeling and Analysis","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Intrusion detection system; Confidentiality; Process (computing); Anomaly-based intrusion detection system; Field (mathematics); Fuzzy logic; Computer security; Event (particle physics); Data mining; Set (abstract data type); Information security; Information sensitivity; Artificial intelligence","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002344964,0.00128483,0.001148679,0.00657683,0.0006970616,0.004110456,0.002052331,0.001882771,0.001311268],"category_scores_gemma":[0.002709945,0.001096842,0.001660737,0.007569496,0.001436458,0.005939816,0.001212206,0.002198667,0.001038547],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001498093,"about_ca_system_score_gemma":0.001814483,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00211207,"about_ca_topic_score_gemma":0.001250082,"domain_scores_codex":[0.9969598,0.000648967,0.0003618041,0.00063438,0.001269636,0.0001254628],"domain_scores_gemma":[0.9976829,0.001301875,0.0002046796,0.0002465526,0.0004838917,0.00008002712],"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":[0.00009486279,0.0002890616,0.005314257,0.00550116,0.0002492506,0.000518234,0.0006071317,0.01247903,0.005469183,0.07247612,0.008673663,0.8883281],"study_design_scores_gemma":[0.00003660356,0.0006342805,0.009606014,0.00444203,0.0003922532,0.004662809,0.000745462,0.1477545,0.01358732,0.1929436,0.6249034,0.0002916836],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.005766867,0.3719299,0.5943137,0.004134383,0.00066177,0.0003544261,0.0003254876,0.001102731,0.02141074],"genre_scores_gemma":[0.0927567,0.3937617,0.5008692,0.001237045,0.002101818,0.0004252414,0.0008767627,0.0001963562,0.007775191],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00657683,"threshold_uncertainty_score":0.01240152,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02387827074069321,"score_gpt":0.2453520916806961,"score_spread":0.2214738209400029,"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."}}