{"id":"W4400653898","doi":"10.5267/j.ijdns.2024.7.003","title":"Securing cryptocurrency transactions: Innovations in malware detection using machine learning","year":2024,"lang":"en","type":"article","venue":"International Journal of Data and Network Science","topic":"Advanced Malware Detection Techniques","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Cryptocurrency; Malware; Computer science; Hacker; AdaBoost; Computer security; Naive Bayes classifier; Decision tree; Machine learning; Cybercrime; Ransomware; Artificial intelligence; The Internet; World Wide Web","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":[0.001753386,0.0008184376,0.0006980252,0.004019165,0.0004809372,0.001878117,0.0009150892,0.0009755084,0.000482564],"category_scores_gemma":[0.004354984,0.0003176923,0.0006840348,0.002580346,0.0008238782,0.00250044,0.0005334648,0.001825931,0.0005135057],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008124092,"about_ca_system_score_gemma":0.000761835,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002505774,"about_ca_topic_score_gemma":0.002038856,"domain_scores_codex":[0.998827,0.00028907,0.00008499,0.0002813584,0.0004497373,0.00006774287],"domain_scores_gemma":[0.9968317,0.001568158,0.0003381912,0.000296105,0.0008559049,0.0001098524],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001015321,0.0005846076,0.01573309,0.0004999961,0.0001244083,0.0001645612,0.00021633,0.04906671,0.0112292,0.007689863,0.003441794,0.911148],"study_design_scores_gemma":[0.00001727728,0.0003952847,0.01240111,0.0003592512,0.00007587831,0.0007734274,0.0002763369,0.9155291,0.02973991,0.01628682,0.0240291,0.0001164498],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2138564,0.05173619,0.7109054,0.00533734,0.0008230087,0.0004381947,0.0005460819,0.001974625,0.0143827],"genre_scores_gemma":[0.7044271,0.01800869,0.2717315,0.0005039916,0.0006139625,0.0001362565,0.0007786183,0.000074095,0.003725734],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004019165,"threshold_uncertainty_score":0.009272933,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03497642215793439,"score_gpt":0.3454103918870187,"score_spread":0.3104339697290843,"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."}}