{"id":"W4388185945","doi":"10.1109/rfid-ta58140.2023.10290221","title":"Enhancing Radio Frequency Identification Systems Security using KLEIN algorithm","year":2023,"lang":"en","type":"article","venue":"","topic":"Cryptographic Implementations and Security","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University of Edmonton","funders":"","keywords":"Computer science; Radio-frequency identification; Cryptography; Key (lock); Identification (biology); Computer security; Power consumption; Algorithm; Software; Power (physics); 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008226776,0.0001123359,0.0001299049,0.0003289329,0.0003194881,0.0004261262,0.0004548252,0.00004755514,0.00002657857],"category_scores_gemma":[0.00002040638,0.0001122859,0.00006682873,0.001708055,0.00002503336,0.00069554,0.0001270742,0.00008940724,0.00008911967],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006370493,"about_ca_system_score_gemma":0.0000629799,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001171328,"about_ca_topic_score_gemma":0.0001130476,"domain_scores_codex":[0.9984916,0.00009024369,0.0004060456,0.000370381,0.0003285195,0.0003131987],"domain_scores_gemma":[0.9991391,0.00006321634,0.0001094446,0.000494589,0.0001159837,0.00007767764],"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":[0.000001040955,0.0001260455,0.002393822,0.0001339551,0.00008901842,0.00005955277,0.009456289,0.0003247701,0.06709825,0.8903794,0.002446069,0.02749175],"study_design_scores_gemma":[0.0002200096,0.00001917692,0.00235185,0.00002101117,0.000009326788,0.0000284569,0.0009629063,0.9728925,0.004112015,0.01849612,0.0006318077,0.0002547905],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1343972,0.00008185436,0.8635512,0.0001306154,0.0009280723,0.0002250348,0.000009502119,0.0004781219,0.0001984518],"genre_scores_gemma":[0.9536795,0.00003301643,0.04599921,0.000034229,0.0001092318,0.00002903304,0.00002881603,0.000009326163,0.00007760221],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9725677,"threshold_uncertainty_score":0.4578887,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02839129005981245,"score_gpt":0.2998009949234637,"score_spread":0.2714097048636513,"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."}}