{"id":"W2046555538","doi":"10.13089/jkiisc.2013.23.2.181","title":"A system for detecting document leakage by insiders through continuous user authentication by using document reading behavior","year":2013,"lang":"en","type":"article","venue":"Journal of the Korea Institute of Information Security and Cryptology","topic":"User Authentication and Security Systems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Kootenay Association for Science & Technology","funders":"","keywords":"Computer science; Leakage (economics); Reading (process); Information leakage; Document processing; Word processing; Information retrieval; Artificial intelligence; World Wide Web; Natural language processing; Computer security","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":[0.001552253,0.001025379,0.001110872,0.003207097,0.0006551925,0.001481936,0.001026667,0.0009897697,0.002372011],"category_scores_gemma":[0.006067041,0.0004211582,0.0003435948,0.001237327,0.0004453835,0.002619896,0.0009214981,0.0009343721,0.002755938],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004639156,"about_ca_system_score_gemma":0.0007037487,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000934405,"about_ca_topic_score_gemma":0.0009272458,"domain_scores_codex":[0.9980106,0.00037245,0.0002785685,0.0005821368,0.0006495258,0.0001068797],"domain_scores_gemma":[0.9902637,0.002722051,0.002248931,0.002155327,0.0021071,0.000502916],"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":[0.003365563,0.001102995,0.0643743,0.0007814434,0.0002828937,0.0007853304,0.001218432,0.001658117,0.214014,0.001796504,0.0120593,0.6985611],"study_design_scores_gemma":[0.0004830917,0.004617359,0.1233646,0.0002852524,0.0009059315,0.006371645,0.0007048672,0.2611099,0.5592272,0.00326842,0.03903817,0.0006237028],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3130336,0.001562234,0.4814971,0.0003860632,0.0002690081,0.001088562,0.002535388,0.1939165,0.00571152],"genre_scores_gemma":[0.7808088,0.0003974606,0.2090825,0.0002506083,0.000130275,0.0004356579,0.001694043,0.0006891903,0.006511392],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003207097,"threshold_uncertainty_score":0.008209229,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01164549280926052,"score_gpt":0.2500855628318475,"score_spread":0.2384400700225869,"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."}}