{"id":"W4387870855","doi":"10.1109/icc45041.2023.10279119","title":"RPM: Ransomware Prevention and Mitigation Using Operating Systems' Sensing Tactics","year":2023,"lang":"en","type":"article","venue":"","topic":"Advanced Malware Detection Techniques","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"Natural Sciences and Engineering Research Council of Canada; Concordia University; National Science Foundation","keywords":"Ransomware; Malware; Computer security; Computer science; Offensive; Extortion; Damages; Botnet; Risk analysis (engineering); Business; Engineering; The Internet; Operations research; Operating system; Law","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":[0.0002615182,0.00008193799,0.0000917072,0.0001360528,0.0002177053,0.0002267496,0.00008676441,0.00004844377,0.00000106497],"category_scores_gemma":[0.00006730967,0.0000832508,0.00001906894,0.0004647766,0.00001478559,0.0008420045,0.0001073941,0.00007325404,0.000005583691],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004898538,"about_ca_system_score_gemma":0.00002374009,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000347297,"about_ca_topic_score_gemma":0.000004251122,"domain_scores_codex":[0.9992194,0.00006722988,0.0001815959,0.0002417845,0.0001450181,0.0001449367],"domain_scores_gemma":[0.9995437,0.00005964614,0.00007257674,0.0001913697,0.00009503819,0.00003763668],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000007267045,0.00003612084,0.0009161571,0.0004802263,0.00005814349,0.00009801675,0.002710625,0.0417403,0.4919026,0.04553546,0.0005781907,0.4159369],"study_design_scores_gemma":[0.0000967112,0.00002976419,0.0001052177,0.00008467403,0.000003731399,0.00007550682,0.0002139949,0.942093,0.05507698,0.001914346,0.0001847235,0.0001213422],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09312113,0.00002364045,0.9049025,0.00008115123,0.0002100209,0.0001931678,4.10288e-7,0.001294091,0.0001739431],"genre_scores_gemma":[0.6749641,0.00001094911,0.3246679,0.0000306861,0.00003803187,0.000003489314,0.000001741859,0.000008986783,0.0002740789],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9003527,"threshold_uncertainty_score":0.3394869,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02918783718778296,"score_gpt":0.3071002600793333,"score_spread":0.2779124228915504,"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."}}