{"id":"W4310041601","doi":"10.3390/s22239144","title":"Towards an Optimized Ensemble Feature Selection for DDoS Detection Using Both Supervised and Unsupervised Method","year":2022,"lang":"en","type":"article","venue":"Sensors","topic":"Network Security and Intrusion Detection","field":"Computer Science","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Artificial intelligence; Computer science; Feature selection; Machine learning; Denial-of-service attack; Feature (linguistics); Ensemble learning; Unsupervised learning; Feature learning; Autoencoder; Generalization; Supervised learning; Data mining; Pattern recognition (psychology); Deep learning; Artificial neural network; The Internet","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007521206,0.0001783183,0.0002182255,0.0002107703,0.0011884,0.0001720098,0.0002415433,0.0001063793,0.00003204085],"category_scores_gemma":[0.00003732999,0.0001909438,0.00009358365,0.000686156,0.00001994171,0.0004495793,0.0001562589,0.000300962,7.239523e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001416541,"about_ca_system_score_gemma":0.00005979338,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001943864,"about_ca_topic_score_gemma":0.00006028529,"domain_scores_codex":[0.9981626,0.0004981051,0.0001889064,0.0005580565,0.0002780471,0.0003142445],"domain_scores_gemma":[0.9993376,0.00009141461,0.00008791433,0.0002741232,0.00009661171,0.0001123477],"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":[0.0006936524,0.0001501993,0.00003123656,0.00004696633,0.00006612983,0.000005751225,0.003739304,0.2013373,0.225493,0.001693563,0.000170381,0.5665725],"study_design_scores_gemma":[0.00104357,0.0005098669,0.0000686104,0.000004382337,0.00002338999,0.0001709578,0.0002337023,0.9560333,0.03534426,0.001376053,0.004962866,0.000228988],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.508145,0.00008729946,0.4903766,0.0002247966,0.0005226395,0.0003886425,0.000004401104,0.0002025641,0.00004804345],"genre_scores_gemma":[0.583953,0.00003389617,0.415167,0.0003438409,0.0002356778,0.00007440446,0.000008854506,0.00003044866,0.0001528708],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7546961,"threshold_uncertainty_score":0.9140336,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02469834112788495,"score_gpt":0.2786693424216744,"score_spread":0.2539710012937895,"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."}}