{"id":"W2024474165","doi":"10.1109/dasc.2011.26","title":"S2XS2: A Server Side Approach to Automatically Detect XSS Attacks","year":2011,"lang":"en","type":"article","venue":"","topic":"Web Application Security Vulnerabilities","field":"Computer Science","cited_by":44,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Cross-site scripting; Computer science; Client-side; Server-side; Scripting language; Overhead (engineering); Side channel attack; Dynamic web page; Web application; Computer security; Operating system; Web page; World Wide Web; Web application security; Cryptography","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.000462693,0.0001621044,0.0001844904,0.0001008353,0.00008853739,0.0001432117,0.001450241,0.00007340522,0.0001360196],"category_scores_gemma":[0.00007822651,0.0001392691,0.00007022673,0.0004658187,0.00005079357,0.0004092885,0.0005083005,0.0001240188,0.001162249],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004417121,"about_ca_system_score_gemma":0.00006694778,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001229058,"about_ca_topic_score_gemma":0.000030074,"domain_scores_codex":[0.9983864,0.00008215374,0.0003072272,0.0005363084,0.0003444116,0.0003434638],"domain_scores_gemma":[0.9982433,0.0001002663,0.00004529117,0.001257803,0.0001222194,0.0002311414],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000005503997,0.0002219764,0.0002666374,0.00004270849,0.00001987712,0.000002152954,0.007866854,0.00002987254,0.0004583468,0.9749823,0.004165072,0.01193867],"study_design_scores_gemma":[0.001833528,0.0007967913,0.1046318,0.00006627796,0.00004296713,0.0001975242,0.001384646,0.3696821,0.1085735,0.3561188,0.05329168,0.003380284],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03624366,0.000007206501,0.7653784,0.0004527388,0.00005505046,0.0003542265,8.072572e-7,0.0007070865,0.1968008],"genre_scores_gemma":[0.564198,2.790714e-7,0.4334735,0.001267744,0.00002201665,0.0001280766,4.718554e-7,0.000008894322,0.0009010237],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6188635,"threshold_uncertainty_score":0.9996155,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04585423571730011,"score_gpt":0.2523752188025485,"score_spread":0.2065209830852484,"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."}}