{"id":"W2916401208","doi":"10.1109/glocom.2018.8647679","title":"DNS Typo-Squatting Domain Detection: A Data Analytics & Machine Learning Based Approach","year":2018,"lang":"en","type":"article","venue":"","topic":"Network Security and Intrusion Detection","field":"Computer Science","cited_by":35,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Classifier (UML); Cluster analysis; Ensemble learning; Commit; Domain Name System; Domain (mathematical analysis); Analytics; Statistical classification","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":[0.001544701,0.0008945151,0.000949194,0.005136169,0.0004514533,0.001875469,0.0009377085,0.001008988,0.0005117123],"category_scores_gemma":[0.003913911,0.0001965099,0.000680941,0.00284851,0.0003509289,0.001678418,0.0007106792,0.001118158,0.0005628893],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007528246,"about_ca_system_score_gemma":0.000662192,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003219311,"about_ca_topic_score_gemma":0.002736,"domain_scores_codex":[0.9986156,0.0002665978,0.0001473379,0.0002864897,0.0005342291,0.0001496402],"domain_scores_gemma":[0.9967119,0.001010757,0.0005715858,0.0004314116,0.001124919,0.0001493395],"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":[0.0004252143,0.001621665,0.1398976,0.000317667,0.0003230036,0.0009367754,0.0005462928,0.1227957,0.03060897,0.004274932,0.008233084,0.690019],"study_design_scores_gemma":[0.000006074252,0.0001809495,0.02192478,0.00004194232,0.00004382367,0.0002925812,0.0004143995,0.956002,0.01532533,0.002752515,0.002973682,0.00004178753],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4385044,0.001663687,0.5452836,0.001950433,0.0001829899,0.0003739761,0.002179193,0.003366941,0.006494846],"genre_scores_gemma":[0.8707526,0.0004487876,0.1243033,0.0001551541,0.0001148004,0.0001139444,0.002327541,0.00003696997,0.001746876],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005136169,"threshold_uncertainty_score":0.008169234,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07004877818819896,"score_gpt":0.2795089501042216,"score_spread":0.2094601719160226,"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."}}