{"id":"W3017197594","doi":"10.1007/978-3-030-45371-8_26","title":"A Rejection-Based Approach for Detecting SQL Injection Vulnerabilities in Web Applications","year":2020,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Web Application Security Vulnerabilities","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université du Québec en Outaouais","funders":"","keywords":"Computer science; SQL injection; Vulnerability (computing); Secure coding; Web application; SQL; Software engineering; Focus (optics); Software; World Wide Web; Database; Software security assurance; Computer security; Information security; Operating system; Web search query; Query by Example","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":[0.003516738,0.001277358,0.001414477,0.004159494,0.001059648,0.002788017,0.003568289,0.002482435,0.004288805],"category_scores_gemma":[0.009494906,0.0005091354,0.001258308,0.001384487,0.001124537,0.002699659,0.00211861,0.001793709,0.002773897],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006753136,"about_ca_system_score_gemma":0.001215086,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001694892,"about_ca_topic_score_gemma":0.003667043,"domain_scores_codex":[0.9945933,0.001007607,0.000289544,0.0007569215,0.002924907,0.0004277916],"domain_scores_gemma":[0.9905885,0.00385368,0.001067551,0.00118773,0.002973517,0.0003290001],"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":[0.001651017,0.001259485,0.03550606,0.000635009,0.0004112816,0.001551558,0.0006882447,0.02076867,0.1923845,0.01906836,0.01255999,0.7135158],"study_design_scores_gemma":[0.0001335425,0.001032833,0.01175517,0.00009674096,0.0004183743,0.00340543,0.0006081262,0.8522548,0.09181764,0.0215145,0.0167507,0.0002120907],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.08989332,0.0007498068,0.8847814,0.0006446147,0.0002617416,0.0005374977,0.0003156595,0.008303626,0.01451231],"genre_scores_gemma":[0.5702434,0.000332491,0.4055444,0.0007236222,0.0002012167,0.0001979326,0.001079871,0.0006616322,0.0210154],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004288805,"threshold_uncertainty_score":0.0185985,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02317331207462903,"score_gpt":0.2554986700648891,"score_spread":0.2323253579902601,"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."}}