{"id":"W6997448752","doi":"","title":"Visualizing Insider USB File Exfiltration Anomalies: A Financial Services Case Study","year":2021,"lang":"","type":"dissertation","venue":"TSpace","topic":"Time Series Analysis and Forecasting","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Dashboard; USable; Visualization; Confidentiality; Anomaly detection; Debugging; USB; Insider threat","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.002269899,0.0005238423,0.0002974427,0.00237572,0.001957855,0.002310688,0.0009800442,0.001650804,0.002468113],"category_scores_gemma":[0.007180389,0.0002420583,0.0003680452,0.002612168,0.001444307,0.0022253,0.001479536,0.00115987,0.000431554],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001509001,"about_ca_system_score_gemma":0.0007957106,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.013362,"about_ca_topic_score_gemma":0.02385002,"domain_scores_codex":[0.9986071,0.0006486803,0.00007149917,0.0001503058,0.000377878,0.0001445904],"domain_scores_gemma":[0.9928175,0.0048485,0.0006025987,0.0004974973,0.0008776815,0.0003561632],"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":[0.001187617,0.002201444,0.1653545,0.00154392,0.0001944494,0.03346051,0.2715136,0.0272504,0.03212269,0.02084382,0.05697352,0.3873536],"study_design_scores_gemma":[0.0001832365,0.001500408,0.2105198,0.00122126,0.0002283949,0.01776879,0.2205542,0.1959237,0.06298916,0.01796271,0.2707187,0.0004296809],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9624664,0.0005229314,0.02025354,0.003833176,0.00005948557,0.0002669303,0.001122805,0.0009215106,0.01055322],"genre_scores_gemma":[0.964497,0.0004217657,0.03083995,0.0001662635,0.00003702097,0.00006777817,0.0004587844,0.0001662314,0.003345225],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.013362,"threshold_uncertainty_score":0.02656841,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02803102073759073,"score_gpt":0.338855601310237,"score_spread":0.3108245805726462,"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."}}