{"id":"W4409882654","doi":"10.1109/tdsc.2025.3564697","title":"Poisoning as a Post-Protection: Mitigating Membership Privacy Leakage From Gradient and Prediction of Federated Models","year":2025,"lang":"en","type":"article","venue":"IEEE Transactions on Dependable and Secure Computing","topic":"HIV, Drug Use, Sexual Risk","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"National Natural Science Foundation of China","keywords":"Leakage (economics); Computer science; Computer security; Privacy protection; Information privacy; Internet privacy","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":[],"consensus_categories":[],"category_scores_codex":[0.0002353515,0.0002361779,0.000395391,0.0002579493,0.0005720694,0.00008772976,0.00006040471,0.0001788083,0.00002992214],"category_scores_gemma":[0.00004201408,0.0002346402,0.00007577733,0.0003821127,0.0000710919,0.0002483333,0.000006924984,0.0005834503,0.000002557725],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007598168,"about_ca_system_score_gemma":0.0001092057,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0012448,"about_ca_topic_score_gemma":0.0001197469,"domain_scores_codex":[0.9984369,0.0001007458,0.0004631924,0.0004793397,0.0002428609,0.0002769609],"domain_scores_gemma":[0.9991174,0.0002233554,0.0001299656,0.000196905,0.0001920189,0.0001403542],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.003813329,0.001692658,0.002412883,0.002911407,0.00272965,0.0002518773,0.1215579,0.1237438,0.2329426,0.001366224,0.0001693895,0.5064084],"study_design_scores_gemma":[0.003200486,0.0008861894,0.0007658422,0.002018499,0.0004343076,0.0001695292,0.02109174,0.8677737,0.1022153,0.001092174,0.00006650188,0.0002857368],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7275604,0.0002611851,0.2701049,0.000414316,0.0002318383,0.000401938,0.00003546939,0.0001313915,0.0008585529],"genre_scores_gemma":[0.9974415,0.00004467929,0.002012824,0.0001942451,0.00005681298,0.00001220958,0.00001901454,0.00002705657,0.0001916832],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7440299,"threshold_uncertainty_score":0.9568351,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04057071849102817,"score_gpt":0.2899999680208071,"score_spread":0.2494292495297789,"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."}}