{"id":"W2567006683","doi":"10.1109/ares.2016.22","title":"Using Expert Systems to Statically Detect \"Dynamic\" Conflicts in XACML","year":2016,"lang":"en","type":"article","venue":"","topic":"Access Control and Trust","field":"Social Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"XACML; Computer science; Prolog; Search engine indexing; Logic programming; Programming language; Compile time; Access control; Expert system; Static analysis; Constraint logic programming; Constraint (computer-aided design); Security policy; Distributed computing; Theoretical computer science; Software engineering; Computer security; Compiler; Artificial intelligence; Constraint satisfaction","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":[],"consensus_categories":[],"category_scores_codex":[0.0003703053,0.00007019297,0.0001401121,0.0000686616,0.0001162562,0.00008577824,0.0001929646,0.00005797668,0.0002182954],"category_scores_gemma":[0.0002725581,0.00004374855,0.00002327737,0.000165416,0.00007216124,0.0001973244,0.00003525544,0.0000298502,0.0001021806],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001422944,"about_ca_system_score_gemma":0.00008620288,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0135726,"about_ca_topic_score_gemma":0.01282567,"domain_scores_codex":[0.9989772,0.0001131757,0.0001758873,0.0001682905,0.0002437359,0.0003216411],"domain_scores_gemma":[0.999447,0.0002030209,0.0000289309,0.0001098315,0.0000604924,0.0001506627],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003020669,0.0002354178,0.02789892,0.00004673041,0.0001166589,0.0001808311,0.06022064,0.0003424275,0.08862986,0.4859748,0.001208079,0.3348435],"study_design_scores_gemma":[0.01092293,0.0005795814,0.04275092,0.001447441,0.00006129489,0.00001249969,0.05152599,0.03355428,0.002278193,0.01341666,0.8397768,0.003673362],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7173329,0.0002843517,0.1536485,0.006394663,0.0007939607,0.0009342941,0.000009017095,0.0001962694,0.1204061],"genre_scores_gemma":[0.9959414,0.0000188129,0.001016703,0.0004084675,0.00007717773,0.00001803521,9.70638e-8,0.000006949407,0.002512351],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8385687,"threshold_uncertainty_score":0.9929961,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06427564867676276,"score_gpt":0.3856848811941438,"score_spread":0.3214092325173811,"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."}}