{"id":"W3003970904","doi":"10.1109/ficloud.2019.00013","title":"Anonymous IoT Mutual Inter-Device Authentication Scheme Based on Incremental Counter (AIMIA-IC)","year":2019,"lang":"en","type":"article","venue":"","topic":"User Authentication and Security Systems","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University; University of Victoria","funders":"","keywords":"Computer science; Authentication (law); Mutual authentication; Computer security; Authentication protocol; Overhead (engineering); Protocol (science); Computer network; Botnet; Cryptography; Security analysis; Internet of Things; Cryptographic protocol; The Internet","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0003939991,0.0001804971,0.0001750465,0.0001773965,0.00007494748,0.0002750122,0.0009053015,0.00007974105,0.0007651101],"category_scores_gemma":[0.00002226081,0.0001589839,0.00008384686,0.0002741127,0.00003027756,0.0002844297,0.0001513543,0.0001384257,0.005431481],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001147917,"about_ca_system_score_gemma":0.00007029258,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005638946,"about_ca_topic_score_gemma":0.00002035159,"domain_scores_codex":[0.9982629,0.000102422,0.0003481252,0.0005114189,0.0005055235,0.0002695652],"domain_scores_gemma":[0.9986014,0.00009164132,0.0001149813,0.0009641327,0.0001163569,0.0001114856],"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":[0.0003781031,0.005633552,0.1429502,0.0007583254,0.0003958019,0.00003920433,0.1256413,0.00005092028,0.2109067,0.4536165,0.04403077,0.01559866],"study_design_scores_gemma":[0.0008712685,0.0001854482,0.002593887,0.00006118971,0.000005753282,0.000005545652,0.0001981885,0.9736633,0.006689768,0.0001275026,0.01531488,0.0002832412],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8514636,0.00001495126,0.1191905,0.003609485,0.001303393,0.0008115432,0.000007832716,0.0005155096,0.02308312],"genre_scores_gemma":[0.9897864,4.054058e-7,0.002752939,0.003279253,0.00004833569,0.00002124735,0.00001790187,0.00001365879,0.004079836],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9736124,"threshold_uncertainty_score":0.9953429,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01522606178443957,"score_gpt":0.2486908636435872,"score_spread":0.2334648018591477,"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."}}