{"id":"W4392157564","doi":"10.1109/jiot.2024.3365142","title":"A Privacy-Preserving Federated Learning Scheme Against Poisoning Attacks in Smart Grid","year":2024,"lang":"en","type":"article","venue":"IEEE Internet of Things Journal","topic":"Privacy-Preserving Technologies in Data","field":"Computer Science","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of New Brunswick","funders":"Program of Shanghai Academic Research Leader; Science and Technology Commission of Shanghai Municipality; National Natural Science Foundation of China","keywords":"Computer science; Computer security; Upload; Server; Encryption; Robustness (evolution); Homomorphic encryption; Scheme (mathematics); Cloud computing; Internet privacy; Information privacy; Computer network; World Wide Web","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":["metaresearch","metaepi_narrow","scholarly_communication","open_science","research_integrity"],"consensus_categories":["open_science"],"category_scores_codex":[0.002216247,0.0003274764,0.0004370328,0.0008868403,0.0001528842,0.00175343,0.0228502,0.000237662,0.00004719856],"category_scores_gemma":[0.01508012,0.0003071947,0.0001859441,0.0009743785,0.0001069648,0.003641413,0.03282347,0.002949725,0.00005031825],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000344531,"about_ca_system_score_gemma":0.0001941316,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001588679,"about_ca_topic_score_gemma":0.00001099177,"domain_scores_codex":[0.9967359,0.0002147292,0.0009798169,0.0006618673,0.0007018893,0.0007058384],"domain_scores_gemma":[0.9968027,0.0003874622,0.0004066235,0.002085111,0.0001831874,0.0001349267],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001424717,0.0003470561,0.0361855,0.0009303758,0.0008215377,0.005384742,0.01177334,0.001523329,0.1530486,0.001870949,0.6299503,0.1580217],"study_design_scores_gemma":[0.0004055612,0.0001442956,0.0003394311,0.003520944,0.000007906267,0.0006187996,0.0001389205,0.9449249,0.02905111,0.01364699,0.00681277,0.0003884049],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6569133,0.001732143,0.31975,0.01446072,0.00374251,0.0001602907,0.000002178229,0.001068766,0.002170113],"genre_scores_gemma":[0.8412644,0.0002003528,0.157863,0.0002235773,0.0001627523,0.000006154864,0.000003382968,0.00004085393,0.0002354533],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9434015,"threshold_uncertainty_score":0.999938,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02552025049173602,"score_gpt":0.2847433186071655,"score_spread":0.2592230681154295,"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."}}