{"id":"W7148458500","doi":"10.1109/wifs66636.2025.00038","title":"Trust-Based Framework for Securing Decentralized Federated Learning against Malicious Clients","year":2025,"lang":"","type":"article","venue":"","topic":"Cryptography and Data Security","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University; Polytechnique Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Key (lock); Government (linguistics); Information privacy; Field (mathematics); Feature (linguistics); Federated learning","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004154971,0.0007493426,0.001251182,0.0008759187,0.001040112,0.001644656,0.002717623,0.00157145,0.0008069701],"category_scores_gemma":[0.01154844,0.0004365275,0.0006615959,0.0007609533,0.001661545,0.003275556,0.003290461,0.001769182,0.0003380016],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001778281,"about_ca_system_score_gemma":0.002704626,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003536009,"about_ca_topic_score_gemma":0.003198598,"domain_scores_codex":[0.9967225,0.0008566678,0.0002116603,0.0006627136,0.001177523,0.0003690492],"domain_scores_gemma":[0.9942953,0.001413689,0.0008288053,0.00175205,0.001337981,0.000372192],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0004299843,0.0002328719,0.003895677,0.00009627691,0.0001262367,0.0003717754,0.0003681249,0.7959033,0.006819114,0.0373167,0.00340748,0.1510325],"study_design_scores_gemma":[0.000008622733,0.00002422495,0.0000848644,0.000003381319,0.000005572753,0.00003734445,0.00001528765,0.9910071,0.001157071,0.007266075,0.0003843715,0.000005980299],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02212751,0.0001651888,0.9751573,0.0002861028,0.00002741318,0.00005324903,0.00003705796,0.001380966,0.0007651836],"genre_scores_gemma":[0.8956856,0.0000749782,0.102835,0.0001147331,0.0000297976,0.00007012906,0.00008637503,0.00004631854,0.001057128],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004154971,"threshold_uncertainty_score":0.02197385,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01470448449099143,"score_gpt":0.288776198172131,"score_spread":0.2740717136811395,"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."}}