{"id":"W4406657986","doi":"10.1109/ist64061.2024.10843494","title":"Federated Learning: Attacks, Defenses, Opportunities and Challenges","year":2024,"lang":"en","type":"article","venue":"","topic":"Privacy-Preserving Technologies in Data","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Computer science; Computer security","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01377581,0.0009554611,0.001091264,0.001995423,0.002337466,0.006843007,0.002284842,0.003658902,0.001688163],"category_scores_gemma":[0.02912808,0.0004118711,0.001038728,0.001485463,0.005303839,0.01224885,0.00517376,0.005271868,0.0005893807],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002487782,"about_ca_system_score_gemma":0.001681714,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001395625,"about_ca_topic_score_gemma":0.0008028984,"domain_scores_codex":[0.9875865,0.005564534,0.0005892597,0.001304348,0.003887849,0.001067474],"domain_scores_gemma":[0.9719881,0.01494034,0.001898673,0.007341513,0.002852282,0.0009791466],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0003315026,0.0003815586,0.01289145,0.0005189795,0.000199062,0.0003152255,0.00142676,0.08342921,0.002796597,0.3713964,0.008115342,0.518198],"study_design_scores_gemma":[0.00003622122,0.0003837727,0.002891114,0.0007561782,0.0000718076,0.001211414,0.002069701,0.3553894,0.007820852,0.5912911,0.03798041,0.00009809021],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"review","genre_scores_codex":[0.09580814,0.0112843,0.8320161,0.02886542,0.0004096818,0.0002884751,0.0001781464,0.001935446,0.02921436],"genre_scores_gemma":[0.908293,0.003189968,0.08284578,0.001977366,0.0002719952,0.00016834,0.0001405952,0.0000958444,0.003017111],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.01377581,"threshold_uncertainty_score":0.07285434,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1399510934537067,"score_gpt":0.2943298621120974,"score_spread":0.1543787686583907,"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."}}