{"id":"W4295046730","doi":"10.1109/tac.2022.3205548","title":"Linear Encryption Against Eavesdropping on Remote State Estimation","year":2022,"lang":"en","type":"article","venue":"IEEE Transactions on Automatic Control","topic":"Security in Wireless Sensor Networks","field":"Computer Science","cited_by":37,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Eavesdropping; Encryption; Computer science; Covariance; Transmission (telecommunications); Algorithm; Mathematics; Computer security; Statistics; Telecommunications","routes":{"ca_aff":true,"ca_fund":true,"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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004800162,0.0002524929,0.0002934149,0.0003652531,0.0007449195,0.0001298159,0.0006175212,0.00006007923,0.0001072182],"category_scores_gemma":[0.00001607635,0.0002781747,0.0001680263,0.0006081305,0.00003782995,0.0003082204,0.00000530092,0.0005042665,0.0001861901],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003729634,"about_ca_system_score_gemma":0.00008165327,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003173703,"about_ca_topic_score_gemma":0.000009239204,"domain_scores_codex":[0.9974906,0.0003803571,0.0004956839,0.0004863861,0.0007461327,0.0004008292],"domain_scores_gemma":[0.9983235,0.0004952839,0.000213587,0.0007910252,0.00005927888,0.0001173486],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001876426,0.0001148139,2.026384e-7,0.00001034143,0.00003332365,0.00001564332,0.0005868202,0.6764161,0.0005994263,0.0001471628,0.00004672051,0.3220107],"study_design_scores_gemma":[0.001304264,0.0002978952,0.00003851875,0.000058019,0.00002183609,0.0000236995,0.00003638535,0.9956705,0.001127722,0.000987671,0.0001672157,0.0002662705],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04830308,0.00001480248,0.9471113,0.001320619,0.001428426,0.0006174521,0.00002263303,0.0009402588,0.0002414121],"genre_scores_gemma":[0.979423,0.00001028905,0.01869144,0.001584218,0.00003482355,0.00008494394,0.000004182963,0.0000286168,0.0001385111],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9311199,"threshold_uncertainty_score":0.999967,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01203567767486045,"score_gpt":0.2391493196691815,"score_spread":0.2271136419943211,"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."}}