{"id":"W3096829912","doi":"10.18280/ts.370403","title":"Phishing Website Detection Using Machine Learning Classifiers Optimized by Feature Selection","year":2020,"lang":"en","type":"article","venue":"Traitement du signal","topic":"Spam and Phishing Detection","field":"Computer Science","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Random forest; Phishing; Feature selection; Decision tree; Computer science; Machine learning; Artificial intelligence; k-nearest neighbors algorithm; Selection (genetic algorithm); Feature (linguistics); Data mining; World Wide Web; The Internet","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":[0.0003467384,0.0002159593,0.0001932595,0.0001025672,0.0005113854,0.000429595,0.000318173,0.0001253673,0.0000866473],"category_scores_gemma":[0.00004127679,0.00022352,0.0001068417,0.0006803567,0.00002084079,0.0009641739,0.00007393301,0.0005577458,0.0000172714],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001615174,"about_ca_system_score_gemma":0.00003255875,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001134498,"about_ca_topic_score_gemma":0.00001398276,"domain_scores_codex":[0.9983485,0.0001964414,0.0002349329,0.0005049517,0.000400919,0.0003142412],"domain_scores_gemma":[0.9994377,0.00005145667,0.0001748124,0.0001010226,0.0000645402,0.0001704538],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002310139,0.0000618639,0.001603924,0.00003804184,0.00009301316,0.000009256694,0.001813372,0.06590092,0.8988698,0.0001071966,0.001344747,0.02992681],"study_design_scores_gemma":[0.0009108258,0.0002506909,0.0001967226,0.00001571695,0.00002787284,0.00002155488,0.00003504402,0.942259,0.04728792,0.00003119805,0.008718105,0.0002453526],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1159827,0.0001282939,0.8812822,0.001437607,0.0003031961,0.0001932792,0.000002819138,0.0005344231,0.0001355388],"genre_scores_gemma":[0.980733,0.00001218023,0.01808085,0.0006904803,0.0003660443,0.00001038016,0.00001347188,0.00002296318,0.00007067422],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8763581,"threshold_uncertainty_score":0.9114882,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02181908028561128,"score_gpt":0.2176225694893505,"score_spread":0.1958034892037392,"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."}}