{"id":"W2346415545","doi":"10.1002/sec.1420","title":"AD‐ASGKA – authenticated dynamic protocols for asymmetric group key agreement","year":2016,"lang":"en","type":"article","venue":"Security and Communication Networks","topic":"Security in Wireless Sensor Networks","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Computer science; Group key; Computer security; Public-key cryptography; Key (lock); Key-agreement protocol; Session key; Key encapsulation; Encryption; ID-based cryptography; Key distribution; Symmetric-key algorithm; Cryptography; Pre-shared key; Shared secret; Computer network","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":[],"consensus_categories":[],"category_scores_codex":[0.0009715375,0.000281367,0.0003244018,0.0001695973,0.000487172,0.0002822252,0.002069212,0.0002635735,0.00001681801],"category_scores_gemma":[0.00009376467,0.0002303603,0.0001205205,0.0007067051,0.0002152525,0.0005423275,0.0008389085,0.0003172234,0.0000183929],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001129608,"about_ca_system_score_gemma":0.00003002263,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001528723,"about_ca_topic_score_gemma":0.0001244613,"domain_scores_codex":[0.9976509,0.0003769446,0.000536579,0.0005741193,0.0003011397,0.0005602763],"domain_scores_gemma":[0.9961488,0.0009664785,0.0003193993,0.002158374,0.0002179129,0.0001890319],"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":[0.0001457438,0.0007598212,0.0004739783,0.0001117404,0.0001718552,0.000003022345,0.003395609,0.0002253,0.0001581328,0.3950686,0.003445489,0.5960407],"study_design_scores_gemma":[0.002365127,0.0003234688,0.001723139,0.0004656825,0.00003346493,0.00001713541,0.00009027305,0.8762582,0.00008120575,0.07502416,0.0429666,0.0006515742],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.005127659,0.003682355,0.972036,0.006999593,0.0002651127,0.01048548,0.00001642672,0.0004718144,0.0009155793],"genre_scores_gemma":[0.9810897,0.001619462,0.01214237,0.0004210959,0.00005303251,0.004506459,0.00004128812,0.00002496053,0.0001016143],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.975962,"threshold_uncertainty_score":0.9393821,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01524188463967639,"score_gpt":0.2705871614325165,"score_spread":0.2553452767928401,"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."}}