{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0006962477,0.0003281531,0.000292554,0.0007337854,0.0004939049,0.00110949,0.001697443,0.0001941275,0.000008054908],"category_scores_gemma":[0.00004774698,0.0002677183,0.00005750881,0.0001940715,0.0007063299,0.001406853,0.0004544983,0.0004444207,0.00002927843],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007013093,"about_ca_system_score_gemma":0.0002185591,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001194754,"about_ca_topic_score_gemma":0.00002973786,"domain_scores_codex":[0.9977737,0.00001716922,0.0003582338,0.0008051727,0.000683248,0.0003624799],"domain_scores_gemma":[0.9978872,0.0001344138,0.0004340983,0.00120179,0.0002055202,0.0001370006],"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":[0.000008792339,0.00001439587,0.0001397973,0.00005000389,0.000010613,0.00001454196,0.002347618,0.0009727775,0.0001010449,0.3610895,0.000008916371,0.635242],"study_design_scores_gemma":[0.0003090352,0.0001982765,0.001163563,0.0005086894,0.000009886196,0.00008660712,4.965329e-7,0.6837924,0.000357116,0.3108602,0.002142761,0.0005709329],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.000630973,0.0001682776,0.99322,0.0007288149,0.000619983,0.0002526995,0.000001479822,0.0001289506,0.004248828],"genre_scores_gemma":[0.6656266,0.0001757632,0.3329167,0.0008422587,0.0002206228,0.00001189237,0.000008032565,0.00002575521,0.0001723184],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6828197,"threshold_uncertainty_score":0.9999775,"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."}}