{"id":"W2766731932","doi":"10.1007/s11036-017-0956-0","title":"Hybrid Cryptography Algorithm with Precomputation for Advanced Metering Infrastructure Networks","year":2017,"lang":"en","type":"article","venue":"Mobile Networks and Applications","topic":"Smart Grid Security and Resilience","field":"Engineering","cited_by":23,"is_retracted":false,"has_abstract":false,"ca_institutions":"École de Technologie Supérieure; Université du Québec à Montréal","funders":"","keywords":"Precomputation; Computer science; Encryption; Overhead (engineering); Smart grid; Computer network; Secure communication; Cryptography; Distributed computing; Key exchange; Public-key cryptography; Embedded system; Computer security; Computation; Algorithm; Operating system","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":[0.0007510734,0.0004782047,0.0006102122,0.0006802286,0.0006781404,0.001190883,0.0009272462,0.0005967197,0.004522336],"category_scores_gemma":[0.001851675,0.000229615,0.000405213,0.0008289717,0.0005381377,0.002130005,0.001300778,0.001009376,0.001196049],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007433557,"about_ca_system_score_gemma":0.00142209,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006567095,"about_ca_topic_score_gemma":0.0008007128,"domain_scores_codex":[0.9991098,0.0002523555,0.00005677238,0.0001389091,0.0003062148,0.0001358764],"domain_scores_gemma":[0.9989406,0.0002837121,0.0000895863,0.0004174313,0.0002311412,0.0000375018],"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":[0.001954448,0.0003211018,0.001719902,0.0002657381,0.0001532419,0.0002548831,0.0001808035,0.1786095,0.04927194,0.1713496,0.009238559,0.5866803],"study_design_scores_gemma":[0.0001639217,0.0003356874,0.0004939042,0.00003278549,0.00005185372,0.0004544564,0.00004457555,0.8903959,0.03379191,0.06604869,0.008142677,0.00004350672],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04736337,0.0006696175,0.9432825,0.0003685915,0.0002001157,0.0001041905,0.00008971348,0.0008892501,0.007032676],"genre_scores_gemma":[0.708882,0.000331162,0.2819346,0.0001731047,0.0001479299,0.0001262752,0.0002379727,0.00007960905,0.008087243],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004522336,"threshold_uncertainty_score":0.01512867,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.002859225951666388,"score_gpt":0.2093044361219021,"score_spread":0.2064452101702357,"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."}}