{"id":"W4401511719","doi":"10.3390/s24165210","title":"IoT Forensics: Current Perspectives and Future Directions","year":2024,"lang":"en","type":"article","venue":"Sensors","topic":"Digital and Cyber Forensics","field":"Computer Science","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Digital forensics; Network forensics; Computer security; Computer science; Internet of Things; Data science; Field (mathematics); Identification (biology); Cloud computing; Computer forensics; Variety (cybernetics); Digital evidence; Internet privacy","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00003834217,0.00009464912,0.00007388788,0.00006852602,0.0000739799,0.0003133842,0.0001111314,0.00002506516,0.000004561569],"category_scores_gemma":[0.00000615538,0.000074752,0.00005258025,0.0002945655,0.0000740211,0.0001748647,0.00008610973,0.0001158136,0.00005464133],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002098885,"about_ca_system_score_gemma":0.0000236285,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005693551,"about_ca_topic_score_gemma":0.000008141032,"domain_scores_codex":[0.9993614,0.00001106686,0.00007186097,0.0002889546,0.0001184845,0.0001482464],"domain_scores_gemma":[0.9996822,0.00002888057,0.000009963766,0.000173262,0.00003753219,0.0000681523],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[4.453816e-7,0.000008413783,0.00001672661,0.000009999932,0.0000107259,0.000009974026,0.003041264,0.000002878987,0.000003821075,0.343338,0.001418908,0.6521389],"study_design_scores_gemma":[0.00005976148,0.00003341934,0.001654575,0.00003825779,0.00001002002,0.00008085452,0.001106351,0.01436749,0.0001368629,0.04746354,0.9348464,0.0002025052],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7685902,0.09045179,0.009863811,0.01559896,0.01440367,0.0003888543,0.00005362079,0.002649046,0.09800003],"genre_scores_gemma":[0.9875279,0.002375103,0.005173334,0.0001056278,0.001904385,0.000009139441,0.00000357283,0.00002587738,0.002875064],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9334275,"threshold_uncertainty_score":0.3048298,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00814556354847022,"score_gpt":0.23602974202911,"score_spread":0.2278841784806397,"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."}}