{"id":"W6891565231","doi":"10.4224/40003534","title":"CloudAPT: a benchmark dataset to evaluate APT countermeasures in cloud environments","year":2024,"lang":"en","type":"dataset","venue":"NRC Digital Repository","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada","funders":"","keywords":"Cloud computing; Benchmark (surveying); Privilege (computing); Cloud computing security; Data security; Data breach","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001400955,0.002099466,0.0009084234,0.003064996,0.001107226,0.001632135,0.002889809,0.002173728,0.003241012],"category_scores_gemma":[0.00554717,0.0003096856,0.001282776,0.004460079,0.0007176813,0.001852225,0.001887147,0.001335632,0.005129904],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001967098,"about_ca_system_score_gemma":0.001729514,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03129989,"about_ca_topic_score_gemma":0.05709186,"domain_scores_codex":[0.9976879,0.0004199637,0.0003068933,0.0005385015,0.0007509968,0.0002957782],"domain_scores_gemma":[0.9972312,0.0006291484,0.0003360571,0.0007604954,0.0007411318,0.0003020129],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0005117911,0.0005813695,0.02724527,0.001357119,0.0002662374,0.0003113204,0.0001584936,0.01603154,0.001599162,0.001845808,0.9150699,0.03502201],"study_design_scores_gemma":[0.0006843657,0.0006548583,0.1141512,0.0006458171,0.000213706,0.001322368,0.001303787,0.1062553,0.007760807,0.006121647,0.7606274,0.0002587101],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.04386491,0.001353461,0.002448729,0.001044992,0.0003267581,0.0003689406,0.9405004,0.003367566,0.006724216],"genre_scores_gemma":[0.0248965,0.0002364237,0.003213152,0.0001812157,0.00003762835,0.0001750668,0.9701118,0.0001051023,0.001043118],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.03129989,"threshold_uncertainty_score":0.06223541,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01515434574979376,"score_gpt":0.2747794212193137,"score_spread":0.25962507546952,"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."}}