{"id":"W3198713703","doi":"10.1109/coins51742.2021.9524269","title":"Malicious URL Detection using Logistic Regression","year":2021,"lang":"en","type":"article","venue":"","topic":"Spam and Phishing Detection","field":"Computer Science","cited_by":56,"is_retracted":false,"has_abstract":true,"ca_institutions":"Brandon University","funders":"","keywords":"Computer science; The Internet; Set (abstract data type); Logistic regression; Computer security; Malware; Web application security; World Wide Web; Machine learning; Web development","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004149866,0.001471194,0.001518188,0.005245953,0.0004946417,0.001963378,0.001464276,0.001561902,0.001348243],"category_scores_gemma":[0.01500922,0.0004729872,0.0013449,0.002797306,0.0005166989,0.001950225,0.001224891,0.001920818,0.0029922],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006940068,"about_ca_system_score_gemma":0.0006166083,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003756523,"about_ca_topic_score_gemma":0.001996884,"domain_scores_codex":[0.9961564,0.001803913,0.0002721282,0.0006510661,0.0008210878,0.000295396],"domain_scores_gemma":[0.9915235,0.004700516,0.001423721,0.0007568003,0.001413175,0.0001823118],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0009344551,0.001178282,0.1665306,0.0004432583,0.000718692,0.001710936,0.0003253032,0.3124032,0.0122285,0.005749532,0.0141325,0.4836447],"study_design_scores_gemma":[0.000006309723,0.00005396707,0.003566118,0.00001542609,0.00002422902,0.0001876238,0.00003518429,0.9929284,0.001520452,0.0009195245,0.0007226724,0.00001994755],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.358459,0.002688356,0.6195745,0.001822485,0.0002552762,0.0002896912,0.001213944,0.008718272,0.00697852],"genre_scores_gemma":[0.92993,0.0005941997,0.06498554,0.000132056,0.0001801669,0.00007297349,0.001090553,0.0001212688,0.002893098],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005245953,"threshold_uncertainty_score":0.02194685,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06063518242347787,"score_gpt":0.2927865376594185,"score_spread":0.2321513552359406,"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."}}