{"id":"W2157160814","doi":"10.1109/nsw.2011.6004640","title":"A pattern recognition framework for the prediction of network vulnerabilities","year":2011,"lang":"en","type":"article","venue":"","topic":"Network Security and Intrusion Detection","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Defence Research and Development Canada","funders":"","keywords":"Computer science; Toolbox; Robustness (evolution); Leverage (statistics); Machine learning; Artificial intelligence; Classifier (UML); Data mining; Artificial neural network; Vulnerability (computing); Feature extraction; Pattern recognition (psychology); Computer security","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":[0.000357936,0.00006474261,0.00007865132,0.00002445573,0.0001737938,0.00002686591,0.0002769796,0.00007365413,0.000176239],"category_scores_gemma":[0.00005675862,0.00004367366,0.00006922166,0.0001918802,0.00004370341,0.0002574828,0.00006326358,0.0001078784,0.000008789974],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00000910535,"about_ca_system_score_gemma":0.00001114428,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008920234,"about_ca_topic_score_gemma":0.00003167518,"domain_scores_codex":[0.9993361,0.00005142549,0.0001988667,0.0001592072,0.0001088836,0.000145569],"domain_scores_gemma":[0.9990949,0.0003909505,0.00008688489,0.0003009461,0.0001034231,0.00002290983],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0000437909,0.00007505497,0.0006135362,0.0000306763,0.00003844934,1.931067e-7,0.00319344,0.0001390999,0.00001729564,0.1085531,0.004279523,0.8830158],"study_design_scores_gemma":[0.0001871296,0.0004933841,0.003784594,0.0000707944,0.00001817947,0.00000582728,0.0001563686,0.2075201,0.003830911,0.7803497,0.003473596,0.000109402],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.005332217,0.00007248609,0.9916828,0.0001933516,0.001189879,0.000265424,0.000004812751,0.000108972,0.001150061],"genre_scores_gemma":[0.8986694,0.00007192485,0.1001953,0.0004050827,0.0004918053,0.0001076553,0.000002458831,0.000005743476,0.00005062597],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8933371,"threshold_uncertainty_score":0.1929693,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05393110373082664,"score_gpt":0.2357353903116974,"score_spread":0.1818042865808707,"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."}}