{"id":"W2534327730","doi":"10.1007/978-3-319-56617-7_11","title":"Quantum Authentication and Encryption with Key Recycling","year":2017,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Quantum Information and Cryptography","field":"Computer Science","cited_by":24,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Eavesdropping; Computer science; BB84; Encryption; Quantum cryptography; Quantum key distribution; Cryptography; Computer security; Authentication (law); Key (lock); Theoretical computer science; Quantum; Quantum information; Physics; Quantum mechanics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0007260083,0.0007879617,0.0007284089,0.0008804809,0.001103972,0.002407684,0.0008387963,0.001769223,0.01239567],"category_scores_gemma":[0.00162475,0.0004775497,0.0008179013,0.001368764,0.00319743,0.005877713,0.002400399,0.002410079,0.005016264],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008741819,"about_ca_system_score_gemma":0.0006003061,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001387831,"about_ca_topic_score_gemma":0.0001061186,"domain_scores_codex":[0.999222,0.0002185646,0.00004626812,0.0001122408,0.0003027275,0.00009830326],"domain_scores_gemma":[0.9995226,0.0001587393,0.00003513261,0.0002172136,0.00005258551,0.00001373738],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002563435,0.00001233437,0.00001779118,0.00009285133,0.000005717675,0.00002872116,0.0000758051,0.00108497,0.001640336,0.9672819,0.002980654,0.02675337],"study_design_scores_gemma":[0.000009022637,0.00002263975,0.00004508196,0.00004273055,0.000007630061,0.0002104211,0.00002431618,0.00516952,0.003726085,0.9571818,0.03353981,0.00002110723],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.02334461,0.01587997,0.5762236,0.003693187,0.00229924,0.0002314765,0.0002420233,0.0007875016,0.3772984],"genre_scores_gemma":[0.5421831,0.01489349,0.1370348,0.001093717,0.00151883,0.0003409588,0.0002752698,0.0005080359,0.3021518],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.01239567,"threshold_uncertainty_score":0.04146767,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01578869599947482,"score_gpt":0.2416260550880449,"score_spread":0.22583735908857,"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."}}