{"id":"W2982581462","doi":"10.48550/arxiv.1910.14169","title":"Secure Logging with Security against Adaptive Crash Attack","year":2019,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Digital and Cyber Forensics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Adversary; Computer security; Scheme (mathematics); Insider; Crash; Computer security model; File system; Operating system","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":[0.003279973,0.0007232502,0.001004983,0.0008965685,0.00154883,0.002882211,0.001600605,0.001711414,0.004099799],"category_scores_gemma":[0.008724225,0.0005718482,0.0009615243,0.001031406,0.003571367,0.009544539,0.005973896,0.003518057,0.001575574],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001557851,"about_ca_system_score_gemma":0.002030293,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000671337,"about_ca_topic_score_gemma":0.0002906551,"domain_scores_codex":[0.9954645,0.0009900351,0.000439844,0.0006466552,0.001652335,0.0008066942],"domain_scores_gemma":[0.9850398,0.004413448,0.00142851,0.007497847,0.001270096,0.0003502839],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.002753441,0.0005378695,0.008210331,0.0008007162,0.0001604628,0.001110413,0.002780142,0.06247839,0.07965504,0.5957471,0.01236483,0.2334013],"study_design_scores_gemma":[0.0003724073,0.0007695653,0.001941258,0.0001549135,0.0001958091,0.001624053,0.0004534603,0.3590598,0.1132631,0.4945592,0.02737455,0.0002318554],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.2040998,0.0008499736,0.7675147,0.002130948,0.0002183499,0.0003557799,0.0002778459,0.009559255,0.01499334],"genre_scores_gemma":[0.9430423,0.0002679798,0.05140284,0.0002656359,0.0001228531,0.0001497204,0.0001702029,0.000244519,0.004333923],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004099799,"threshold_uncertainty_score":0.01734632,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04846037471739188,"score_gpt":0.1692540080754501,"score_spread":0.1207936333580582,"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."}}