{"id":"W4313121388","doi":"10.1109/dsa56465.2022.00059","title":"Security Pattern Detection Through Diagonally Distributed Matrix Matching","year":2022,"lang":"en","type":"article","venue":"2022 9th International Conference on Dependable Systems and Their Applications (DSA)","topic":"Software System Performance and Reliability","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Software security assurance; Security testing; Computer security model; Diagonal; Software; Data mining; Matching (statistics); Security service; Security information and event management; Computer security; Cloud computing security; Information security; Statistics; Mathematics; Operating system","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":[0.0006813845,0.0002483356,0.0002694603,0.0001392609,0.0008834254,0.0004009384,0.001103425,0.00007433303,0.0001767076],"category_scores_gemma":[0.00001288874,0.000216027,0.00009331489,0.0004000371,0.00004540097,0.0004966261,0.0005928445,0.0004315705,0.000060342],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002606914,"about_ca_system_score_gemma":0.0001156965,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007115961,"about_ca_topic_score_gemma":0.00005063567,"domain_scores_codex":[0.9977565,0.0001878647,0.0004932557,0.0006916196,0.0005817303,0.0002890077],"domain_scores_gemma":[0.9985771,0.000127933,0.000303283,0.0006591218,0.0002375444,0.00009506161],"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":[0.000115764,0.0009925407,0.004174622,0.0004149275,0.0004685418,0.00002644541,0.005505275,0.01040688,0.003735985,0.8988679,0.001875666,0.07341547],"study_design_scores_gemma":[0.001484633,0.0004035484,0.001278662,0.0001248498,0.00002472472,0.0005808963,0.004597281,0.6019668,0.001136483,0.06907492,0.3181792,0.001147918],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02850169,0.0003031041,0.9631851,0.001083334,0.002081069,0.0009769276,0.0007517513,0.0003090213,0.002807948],"genre_scores_gemma":[0.9971115,0.00005639257,0.0001580146,0.0001043925,0.0001600274,0.001718736,0.0001798127,0.0000159763,0.0004951225],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9686098,"threshold_uncertainty_score":0.8809325,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01743986984128922,"score_gpt":0.2678022408660957,"score_spread":0.2503623710248065,"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."}}