{"id":"W3095348168","doi":"10.1007/978-3-030-88238-9_9","title":"Improved Attacks Against Key Reuse in Learning with Errors Key Exchange","year":2021,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"User Authentication and Security Systems","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Key (lock); Reuse; Key exchange; Computer security; Public-key cryptography; Encryption; Engineering","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001126764,0.000582042,0.0006820876,0.00101094,0.0002361358,0.0008171484,0.004090692,0.0003607935,0.00002053896],"category_scores_gemma":[0.0001860292,0.0005192737,0.000117457,0.001166213,0.000418349,0.0006613627,0.001838301,0.001371644,0.00003355351],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003615307,"about_ca_system_score_gemma":0.0006610116,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000596428,"about_ca_topic_score_gemma":0.001104126,"domain_scores_codex":[0.9955337,0.0001252277,0.000654866,0.00188041,0.001020349,0.0007854191],"domain_scores_gemma":[0.9965533,0.0002961504,0.0003852379,0.002211347,0.0003261584,0.0002278002],"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":[0.00006093639,0.0004064249,0.00366048,0.0008736601,0.0001206859,0.002032022,0.3226407,0.02796168,0.002814884,0.01730779,0.0001443227,0.6219764],"study_design_scores_gemma":[0.000761627,0.0002558249,0.0003062972,0.001354382,0.000008301424,0.00008836914,0.000005403685,0.9811,0.0008326403,0.003942616,0.01019344,0.001151085],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.003703939,0.0007420837,0.9896078,0.001638386,0.001198692,0.0005687931,0.000002715494,0.0002163509,0.002321285],"genre_scores_gemma":[0.8564705,0.000163923,0.1368255,0.002297856,0.0004900641,0.00004804286,0.00003020833,0.0001029364,0.003571017],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9531384,"threshold_uncertainty_score":0.9997259,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01833587009128559,"score_gpt":0.2421084689024504,"score_spread":0.2237725988111648,"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."}}