{"id":"W4220733056","doi":"10.18280/ria.360106","title":"Security of Federated Learning: Attacks, Defensive Mechanisms, and Challenges","year":2022,"lang":"en","type":"article","venue":"Revue d intelligence artificielle","topic":"Privacy-Preserving Technologies in Data","field":"Computer Science","cited_by":37,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Federated learning; Computer security; Tracing; Train; Private information retrieval; Data science; Internet privacy; Artificial intelligence","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["open_science"],"consensus_categories":["open_science"],"category_scores_codex":[0.0007626261,0.0001656839,0.000257405,0.0001640358,0.000435433,0.0000663078,0.006928171,0.00007382775,0.00009070897],"category_scores_gemma":[0.004074623,0.0001843497,0.00005413,0.0005643832,0.0001283447,0.000249022,0.03735938,0.0004870548,0.00002722477],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005651451,"about_ca_system_score_gemma":0.00004447016,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002970136,"about_ca_topic_score_gemma":0.00000801629,"domain_scores_codex":[0.9981586,0.0002063429,0.0003711574,0.0006427341,0.0002879185,0.0003331843],"domain_scores_gemma":[0.9967239,0.000291403,0.0002138975,0.002583132,0.0001253933,0.00006223214],"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":[0.00007659365,0.0008569621,0.0004394023,0.0006512572,0.0001696609,0.0002522599,0.008661476,0.02261831,0.02247488,0.6061662,0.02368546,0.3139475],"study_design_scores_gemma":[0.00003794781,0.0003106608,0.00001851376,0.00002669782,0.000005621616,0.00007959238,0.003132477,0.6539887,0.06737623,0.2659709,0.008827773,0.0002248536],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04618283,0.01061467,0.8947838,0.04267982,0.0007343746,0.0006174679,0.0000333292,0.00114807,0.003205644],"genre_scores_gemma":[0.975567,0.00201944,0.02218012,0.00006814177,0.00001081451,0.00003842415,0.000007456618,0.00001433054,0.00009426136],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9293842,"threshold_uncertainty_score":0.9984448,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06644983805045748,"score_gpt":0.2769107763036031,"score_spread":0.2104609382531456,"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."}}