{"id":"W2920590155","doi":"10.1145/3297067.3297096","title":"Detecting Blind Cross-Site Scripting Attacks Using Machine Learning","year":2018,"lang":"en","type":"article","venue":"","topic":"Web Application Security Vulnerabilities","field":"Computer Science","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University of Edmonton","funders":"Ministère de l'Économie, de la Science et de l'Innovation - Québec","keywords":"Cross-site scripting; Computer science; Scripting language; Web application; Computer security; World Wide Web; Web server; Server; Web page; Web application security; Operating system; The Internet; Web development","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001673877,0.001223781,0.0009814921,0.002932954,0.0004194987,0.001162941,0.0009065705,0.001138058,0.0007249498],"category_scores_gemma":[0.005840013,0.0003227844,0.0007210582,0.001016558,0.0005358548,0.001738215,0.000719948,0.001174857,0.0006611156],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006394412,"about_ca_system_score_gemma":0.0009571972,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00256279,"about_ca_topic_score_gemma":0.00225417,"domain_scores_codex":[0.9978508,0.0004918858,0.0002002145,0.0004930059,0.0007205136,0.0002436591],"domain_scores_gemma":[0.9949373,0.002039914,0.001035726,0.0007497467,0.0009747758,0.0002623668],"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":[0.0005793313,0.001894616,0.1409742,0.0002735875,0.0003713681,0.0006963167,0.0001590917,0.2539694,0.03356706,0.003236963,0.008227636,0.5560505],"study_design_scores_gemma":[0.000008129841,0.0001475446,0.00602232,0.00001553785,0.00002415106,0.000128472,0.00002969997,0.9793308,0.01107348,0.002380417,0.0008192245,0.00002015485],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.5453617,0.001336415,0.4374026,0.0006626703,0.0001535157,0.0003626913,0.0009096297,0.00869712,0.005113663],"genre_scores_gemma":[0.9268689,0.0002022798,0.06991249,0.0001422349,0.00004435567,0.00007401872,0.001138824,0.0000651635,0.001551876],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.002932954,"threshold_uncertainty_score":0.008852422,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05213637726759891,"score_gpt":0.3356718794094752,"score_spread":0.2835355021418763,"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."}}