{"id":"W2962911305","doi":"10.5539/cis.v12n3p72","title":"Enterprise Cybersecurity: Investigating and Detecting Ransomware Infections Using Digital Forensic Techniques","year":2019,"lang":"en","type":"article","venue":"Computer and Information Science","topic":"Advanced Malware Detection Techniques","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Ransomware; Computer security; Computer science; Digital forensics; Malware; Key (lock); Internet privacy; Risk analysis (engineering); Business","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001782172,0.0005270515,0.0004184856,0.007350738,0.0007054137,0.001952645,0.0007734829,0.001790346,0.0008488573],"category_scores_gemma":[0.004339154,0.0003228379,0.0004278163,0.001522227,0.0007432069,0.003100303,0.001144678,0.0007453667,0.0005599922],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005196148,"about_ca_system_score_gemma":0.0006935466,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001245734,"about_ca_topic_score_gemma":0.002682121,"domain_scores_codex":[0.9987419,0.0003585268,0.00007659196,0.0001765479,0.0004647507,0.0001816787],"domain_scores_gemma":[0.9973944,0.0008238491,0.0007395211,0.0002729892,0.000668042,0.0001010116],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.000208815,0.0008872542,0.1288141,0.0007208842,0.0001602811,0.002174097,0.002426341,0.009010416,0.07525973,0.008155097,0.004395424,0.7677876],"study_design_scores_gemma":[0.00006340822,0.001445034,0.1657109,0.001534152,0.000481267,0.01696786,0.01344917,0.3918161,0.3354121,0.02889241,0.04387809,0.0003497294],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.712447,0.006138529,0.2564666,0.002194199,0.0001670161,0.0008077536,0.0003421378,0.001519114,0.01991751],"genre_scores_gemma":[0.8130035,0.002417723,0.1815306,0.0002257328,0.00004224392,0.00008735964,0.0001845751,0.00003407263,0.002474141],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007350738,"threshold_uncertainty_score":0.009425163,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008797596823884077,"score_gpt":0.2438557693504363,"score_spread":0.2350581725265523,"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."}}