{"id":"W2968685279","doi":"10.1007/978-3-030-26948-7_2","title":"Quantum Cryptanalysis in the RAM Model: Claw-Finding Attacks on SIKE","year":2019,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Quantum Computing Algorithms and Architecture","field":"Computer Science","cited_by":80,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Isogeny; Key encapsulation; Cryptanalysis; Computer science; Quantum computer; Supersingular elliptic curve; Computation; Post-quantum cryptography; Quantum; Cryptography; Theoretical computer science; Algorithm; Public-key cryptography; Key exchange; Elliptic curve; Mathematics; Computer security; Quantum mechanics; Physics; Encryption","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","scholarly_communication","open_science","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.002285336,0.000866611,0.0009066058,0.001638702,0.0004395962,0.001075797,0.007435448,0.0004500183,0.00000826097],"category_scores_gemma":[0.0001143188,0.0006141441,0.0003609268,0.001606265,0.0004990124,0.000366083,0.001472668,0.002456737,0.00008188724],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003281678,"about_ca_system_score_gemma":0.0006768079,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003144399,"about_ca_topic_score_gemma":0.00006415101,"domain_scores_codex":[0.9936047,0.0001426202,0.0008162923,0.002343545,0.001913904,0.001178919],"domain_scores_gemma":[0.9950466,0.001442203,0.000433263,0.002779651,0.0001461732,0.0001521474],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000004929064,0.00003660989,0.00002947399,0.00002086518,0.00001142757,0.00008914312,0.001307433,0.7799174,0.00001501618,0.04314557,0.00003064361,0.1753915],"study_design_scores_gemma":[0.0002461333,0.0002002929,0.00008472415,0.0003991573,0.00001059546,0.00005017099,4.672397e-7,0.8570244,0.00005938553,0.1408759,0.0004000188,0.0006487393],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001935137,0.0002496882,0.990141,0.002431313,0.001438373,0.0005432453,0.000006177152,0.000162842,0.003092277],"genre_scores_gemma":[0.8001413,0.00004789126,0.1916193,0.007086391,0.0007016748,0.00001238857,0.000008486531,0.00007914447,0.000303373],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7985216,"threshold_uncertainty_score":0.9999612,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02308760408930807,"score_gpt":0.2668998800100151,"score_spread":0.2438122759207071,"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."}}