{"id":"W4403724102","doi":"10.1109/dsaa61799.2024.10722785","title":"AddShare+: Efficient Selective Additive Secret Sharing Approach for Private Federated Learning","year":2024,"lang":"en","type":"article","venue":"","topic":"Cryptography and Data Security","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Computer science; Secret sharing; Computer security; Theoretical computer science; Cryptography","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":[0.0003676958,0.0001865885,0.0001629968,0.0001866527,0.0003825696,0.0009974168,0.0005299404,0.00007603103,0.00005217765],"category_scores_gemma":[0.00007983142,0.0001615801,0.000130309,0.001048985,0.00003177035,0.0004311425,0.0003835682,0.0003194745,0.00002547442],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005177717,"about_ca_system_score_gemma":0.00006093408,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002222843,"about_ca_topic_score_gemma":0.000004636401,"domain_scores_codex":[0.9983087,0.00004253301,0.0001890668,0.0008518828,0.0002069394,0.0004008345],"domain_scores_gemma":[0.9993049,0.0001991063,0.00003811199,0.0002419082,0.0001133086,0.0001026526],"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":[0.00003358332,0.0001421018,0.0001291966,0.0001446059,0.0001623483,0.00001427125,0.003347882,0.002965711,0.0006746011,0.9644278,0.006085994,0.02187188],"study_design_scores_gemma":[0.0002026644,0.0001132747,0.000217225,0.0000416535,0.00001029423,0.000008756691,0.000147662,0.9804688,0.003622758,0.003104117,0.01180831,0.0002544659],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.005912611,0.0001787731,0.9828681,0.00006128994,0.0001792736,0.0004633255,0.00009735831,0.0009891929,0.009250103],"genre_scores_gemma":[0.9008761,0.000008333821,0.09815777,0.0001051126,0.0001084456,0.0001679404,0.0004056746,0.00001974488,0.0001508437],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9775031,"threshold_uncertainty_score":0.9618114,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01659881889561727,"score_gpt":0.2521640346067706,"score_spread":0.2355652157111533,"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."}}