{"id":"W2130463662","doi":"10.1109/re.2008.32","title":"Selecting Security Patterns that Fulfill Security Requirements","year":2008,"lang":"en","type":"article","venue":"","topic":"Information and Cyber Security","field":"Computer Science","cited_by":54,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Computer science; Computer security model; Security service; Security information and event management; Security testing; Cloud computing security; Security through obscurity; Security engineering; Software security assurance; Computer security; Selection (genetic algorithm); Information security; Cloud computing; Artificial intelligence","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":[],"consensus_categories":[],"category_scores_codex":[0.0003607422,0.0001917968,0.0001767198,0.0001061119,0.0004468716,0.0001441461,0.0008416037,0.00008850651,0.0002705787],"category_scores_gemma":[0.0000280144,0.0001761272,0.0000975174,0.0003497271,0.00003491327,0.001970108,0.0002773477,0.0002495288,0.0002897923],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007538999,"about_ca_system_score_gemma":0.00007361353,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001965581,"about_ca_topic_score_gemma":0.0001106654,"domain_scores_codex":[0.9982354,0.00007386429,0.0003198192,0.0003413665,0.0005661153,0.0004634409],"domain_scores_gemma":[0.998939,0.00003875103,0.0001372706,0.0005814437,0.0001380223,0.0001655164],"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":[0.00003128917,0.000894574,0.3775585,0.0002142538,0.0001623983,0.0002376461,0.1619252,0.00002080541,0.0001884232,0.3854349,0.05902544,0.01430662],"study_design_scores_gemma":[0.008071863,0.0007712083,0.2200819,0.0002202326,0.00004564189,0.00249172,0.004767338,0.35881,0.1433189,0.05986807,0.1957581,0.005794983],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6883982,0.00003567525,0.1531911,0.0007848079,0.000820632,0.0002963133,0.000007265299,0.0009301798,0.1555359],"genre_scores_gemma":[0.9956401,0.0000244083,0.001898956,0.002074459,0.00006500015,0.00001007804,0.00000790073,0.000006930914,0.0002721755],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3587892,"threshold_uncertainty_score":0.7182257,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03374151258665916,"score_gpt":0.2534274244132124,"score_spread":0.2196859118265533,"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."}}