{"id":"W3029231014","doi":"","title":"Multicollision Attacks on some Generalized Sequential Hash Functions.","year":2006,"lang":"en","type":"preprint","venue":"IACR Cryptology ePrint Archive","topic":"Cryptographic Implementations and Security","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Hash function; Collision attack; SHA-2; Iterated function; Computer science; Cryptographic hash function; Double hashing; Hash chain; Collision resistance; Set (abstract data type); MDC-2; Class (philosophy); Function (biology); Theoretical computer science; Mathematics; Computer security; Programming language; Artificial intelligence","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":[0.002511324,0.0009825652,0.0009567965,0.0009991651,0.001206926,0.001847923,0.001213253,0.001441155,0.001933747],"category_scores_gemma":[0.008438331,0.0005325487,0.001426691,0.001427042,0.003281541,0.006101077,0.003307875,0.00223587,0.0004635469],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001278303,"about_ca_system_score_gemma":0.0007074093,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003849069,"about_ca_topic_score_gemma":0.0002819066,"domain_scores_codex":[0.9954587,0.001256451,0.0002458798,0.0007718258,0.001565851,0.0007012751],"domain_scores_gemma":[0.9925922,0.002794759,0.001198691,0.002657606,0.0005330754,0.000223789],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001103077,0.0001098665,0.003654513,0.0002812755,0.000308817,0.001186885,0.0009260084,0.05355124,0.04474191,0.8288336,0.002693917,0.06260902],"study_design_scores_gemma":[0.0001410583,0.0004932833,0.00151021,0.00005884044,0.0001133822,0.002703649,0.0001785094,0.2848457,0.04860031,0.6454119,0.01584762,0.00009561711],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.275311,0.0009251219,0.7098476,0.0007628799,0.0001361712,0.0003247946,0.0002589632,0.0004898167,0.01194366],"genre_scores_gemma":[0.9338896,0.0004752819,0.06109139,0.000287912,0.0001259722,0.0001749495,0.0001535474,0.00005907918,0.003742352],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002511324,"threshold_uncertainty_score":0.01328129,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03238088409572054,"score_gpt":0.3096803961251157,"score_spread":0.2772995120293952,"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."}}