{"id":"W4287095742","doi":"10.18280/ijsse.120314","title":"Analysis of Autoencoder Compression Performance in Intrusion Detection System","year":2022,"lang":"en","type":"article","venue":"International Journal of Safety and Security Engineering","topic":"Network Security and Intrusion Detection","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Institut Teknologi Sepuluh Nopember","keywords":"Autoencoder; Computer science; Intrusion detection system; Data mining; Process (computing); Reduction (mathematics); Intrusion; Artificial neural network; Artificial intelligence; Mathematics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006467251,0.00007188089,0.0002096224,0.0008641043,0.00007224394,0.00002616938,0.0003885051,0.00003223051,0.00001461312],"category_scores_gemma":[0.00001930502,0.00007220128,0.00008644173,0.0006732469,0.00001009638,0.0004361219,0.0002534075,0.0003125485,1.481077e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001824775,"about_ca_system_score_gemma":0.00001828579,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002322772,"about_ca_topic_score_gemma":0.00001019582,"domain_scores_codex":[0.998797,0.00005695928,0.0004881643,0.0001090177,0.0004619485,0.00008692889],"domain_scores_gemma":[0.9994052,0.00006706462,0.0002720402,0.00008619065,0.0001323969,0.00003711389],"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":[0.0001934963,0.00005874113,0.001565637,0.00003166838,0.0002033865,0.0000245091,0.001844557,0.9683597,0.002363952,0.0029783,0.000001937966,0.02237409],"study_design_scores_gemma":[0.0003343446,0.0001017174,0.01745059,0.00007187179,0.00002455985,0.0001259186,0.00009263294,0.9792542,0.001167708,0.00003618294,0.001273843,0.0000664406],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7217327,0.0002349619,0.2765881,0.0001023761,0.001216325,0.0000397781,0.000004007982,0.00001960371,0.0000621093],"genre_scores_gemma":[0.9988811,0.0002068122,0.0008332404,0.00001405428,0.00005706785,0.000001449618,0.000001642255,0.000003013426,0.000001647826],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2771483,"threshold_uncertainty_score":0.2944283,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004511144746502157,"score_gpt":0.1981504547183251,"score_spread":0.1936393099718229,"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."}}