{"id":"W4226069469","doi":"10.1109/qrs54544.2021.00012","title":"Analyzing Structural Security Posture to Evaluate System Design Decisions","year":2021,"lang":"en","type":"article","venue":"2021 IEEE 21st International Conference on Software Quality, Reliability and Security (QRS)","topic":"Software Engineering Research","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Leverage (statistics); Computer science; Computer security; Software security assurance; Security testing; Computer security model; Identification (biology); Resource (disambiguation); Security information and event management; Secure coding; Security service; Security through obscurity; Software; Cloud computing security; Risk analysis (engineering); Information security; Artificial intelligence; Cloud computing; Business","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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.003278807,0.0004873911,0.0006546951,0.0003187039,0.0003990422,0.001071898,0.001846054,0.0003027568,0.0002528661],"category_scores_gemma":[0.01101391,0.0004794949,0.0002391353,0.0009231057,0.0001435595,0.0006523737,0.001022841,0.0009929362,0.0001346777],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005519725,"about_ca_system_score_gemma":0.0006627147,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000239813,"about_ca_topic_score_gemma":0.000110417,"domain_scores_codex":[0.9935381,0.001276874,0.0009152037,0.001690858,0.001911463,0.0006675054],"domain_scores_gemma":[0.9911456,0.003904001,0.0001888774,0.001576271,0.002585355,0.0005998815],"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":[0.0007734597,0.001183837,0.08302734,0.001122347,0.0008809125,0.0007068283,0.02086988,0.01923363,0.002720099,0.819656,0.00358143,0.04624429],"study_design_scores_gemma":[0.004985053,0.001351063,0.1502917,0.003138156,0.0001580487,0.0006048137,0.004429731,0.5606636,0.01254264,0.2527576,0.004005407,0.005072106],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6047367,0.000154493,0.3876893,0.003461663,0.002309908,0.0005743137,0.0002572152,0.0004643998,0.0003519891],"genre_scores_gemma":[0.9713441,0.00009804448,0.02776814,0.0003016954,0.0002265868,0.00006870931,0.00005707623,0.00002597098,0.0001096879],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5668983,"threshold_uncertainty_score":0.9999651,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07041286786716698,"score_gpt":0.3641071605009214,"score_spread":0.2936942926337544,"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."}}