{"id":"W1555588376","doi":"10.1002/spe.2108","title":"Linguistic security testing for text communication protocols","year":2012,"lang":"en","type":"article","venue":"Software Practice and Experience","topic":"Web Application Security Vulnerabilities","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University; Sheridan College","funders":"","keywords":"Computer science; Syntax; Protocol (science); Programming language; Grammar; Test (biology); Formal grammar; Cryptographic protocol; Communications protocol; Natural language processing; Rule-based machine translation; Computer security; Computer network; Linguistics","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":[0.006564078,0.0008384299,0.0006978432,0.001822616,0.001154623,0.002609271,0.00220118,0.001519456,0.00349345],"category_scores_gemma":[0.01816519,0.0004391893,0.00135941,0.0006908394,0.005919674,0.00503206,0.00270261,0.002495948,0.0006738603],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002027514,"about_ca_system_score_gemma":0.00276496,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003196317,"about_ca_topic_score_gemma":0.001333998,"domain_scores_codex":[0.9859009,0.006060364,0.001024263,0.0009986012,0.005321196,0.000694634],"domain_scores_gemma":[0.9812051,0.01095811,0.001350076,0.002576176,0.003561227,0.0003492955],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0005332747,0.0005171318,0.003103957,0.0005813371,0.00009149568,0.001580903,0.002601181,0.0764092,0.07168814,0.6637595,0.005760595,0.1733733],"study_design_scores_gemma":[0.0001937145,0.0002893279,0.000929056,0.0002633294,0.00007789372,0.0008055571,0.0004946669,0.5146616,0.1054074,0.3575793,0.01911548,0.000182681],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.05752132,0.0001700573,0.928237,0.001054204,0.00007176936,0.0002639675,0.0001259243,0.004094419,0.008461286],"genre_scores_gemma":[0.6514609,0.0001527055,0.3434695,0.0003886489,0.00005931924,0.0003520061,0.0003735226,0.0006077598,0.003135514],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.006564078,"threshold_uncertainty_score":0.03471458,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05456387560853018,"score_gpt":0.3688064179561888,"score_spread":0.3142425423476586,"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."}}