{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01903824,0.0008975317,0.001741715,0.001913874,0.002681496,0.008618782,0.003933798,0.005901746,0.001245613],"category_scores_gemma":[0.02982527,0.0006871419,0.001242143,0.001943326,0.007319448,0.01673386,0.007598832,0.00755062,0.0006450284],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002981095,"about_ca_system_score_gemma":0.002155378,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008587685,"about_ca_topic_score_gemma":0.0003410658,"domain_scores_codex":[0.9814921,0.007606529,0.001136356,0.001887436,0.006461081,0.001416439],"domain_scores_gemma":[0.9604753,0.01646803,0.002986156,0.01632537,0.002856478,0.0008886285],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0002472969,0.0001651313,0.003470029,0.0003909054,0.000167662,0.0002857857,0.0009107158,0.03051799,0.002769376,0.7413257,0.008450824,0.2112985],"study_design_scores_gemma":[0.00003483499,0.0001193302,0.0006883617,0.0004145074,0.00004850234,0.0008350508,0.0004938297,0.156681,0.006904799,0.808575,0.02512319,0.00008167714],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"review","genre_scores_codex":[0.05695482,0.01652125,0.8516002,0.05359198,0.0007409074,0.0002057303,0.0001844587,0.001969703,0.01823104],"genre_scores_gemma":[0.8973877,0.005797922,0.08829302,0.004403819,0.000757374,0.0002213494,0.0001268189,0.0001087717,0.002903181],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.01903824,"threshold_uncertainty_score":0.100685,"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."}}