{"id":"W3009468109","doi":"10.1109/globecom38437.2019.9013921","title":"Exploiting Dynamic Platform Protection Technique for Increasing Service MTTF","year":2019,"lang":"en","type":"article","venue":"","topic":"Network Security and Intrusion Detection","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Mean time between failures; Computer science; Service (business); Software deployment; Process (computing); Network service; Reliability engineering; Computer security; Distributed computing; Computer network; Real-time computing; Failure rate; Engineering; Operating system","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008888134,0.0007698287,0.0005412236,0.001511161,0.0004825771,0.00061618,0.0007378957,0.0006118672,0.0008869303],"category_scores_gemma":[0.004702841,0.0002585851,0.0007864229,0.0008721875,0.0007024421,0.001337591,0.0006214642,0.001069418,0.0001783204],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001431196,"about_ca_system_score_gemma":0.001118443,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003384723,"about_ca_topic_score_gemma":0.002192902,"domain_scores_codex":[0.9991398,0.0001296433,0.00003749369,0.0001742813,0.000335609,0.0001831222],"domain_scores_gemma":[0.9976522,0.001101067,0.0005584576,0.0003061398,0.0003035871,0.00007845895],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001196693,0.0000657526,0.007773736,0.0001228584,0.00004606282,0.0002504692,0.0001447243,0.8864587,0.03756509,0.01332348,0.0006442211,0.05348526],"study_design_scores_gemma":[0.000002081292,0.00006450051,0.0009197912,0.000004866844,0.00001011036,0.0001317485,0.00001731753,0.9917825,0.004984656,0.001729099,0.0003453936,0.000007912274],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1758627,0.0006401953,0.8201607,0.0002859613,0.00006187402,0.00005224097,0.00009120107,0.0007698185,0.002075297],"genre_scores_gemma":[0.9710857,0.000203453,0.02806709,0.00002187986,0.00001312363,0.00002620495,0.00004140694,0.00004393905,0.0004972896],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003384723,"threshold_uncertainty_score":0.01038408,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01845650386120978,"score_gpt":0.2364886508936678,"score_spread":0.218032147032458,"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."}}