{"id":"W4416728576","doi":"10.1109/mwscas53549.2025.11244511","title":"Efficient and Secure Neural Network Inference with Homomorphic Encryption","year":2025,"lang":"","type":"article","venue":"","topic":"Cryptography and Data Security","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"","keywords":"Homomorphic encryption; MNIST database; Speedup; Inference; Artificial neural network; Cloud computing; Latency (audio); Computation","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":[0.001174785,0.0007780953,0.000888617,0.0005939509,0.0006671724,0.001450397,0.001768592,0.0008485088,0.003371735],"category_scores_gemma":[0.003818279,0.0005273213,0.0008400473,0.0007190641,0.0009117637,0.004020969,0.002449353,0.002029617,0.001646362],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001242787,"about_ca_system_score_gemma":0.002316679,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002646212,"about_ca_topic_score_gemma":0.005265783,"domain_scores_codex":[0.9986165,0.0002884385,0.0000978547,0.0002412982,0.0005576441,0.000198301],"domain_scores_gemma":[0.9975876,0.000519532,0.0001945782,0.001420485,0.0002242261,0.00005365008],"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":[0.0009616492,0.0003706459,0.002632676,0.0001920575,0.0002157201,0.0005016748,0.0002269084,0.3795332,0.03492537,0.1098006,0.01325018,0.4573893],"study_design_scores_gemma":[0.00004119494,0.0000361913,0.0002511207,0.000009714178,0.00001544485,0.0001067248,0.00003293267,0.9456391,0.01870785,0.0338687,0.001278611,0.00001235575],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.04809831,0.0002971134,0.9426009,0.0005393958,0.00007884185,0.0001078374,0.0003417901,0.003557923,0.004377773],"genre_scores_gemma":[0.6991373,0.0003579888,0.2926995,0.0002107643,0.00009882185,0.0001844294,0.0009470256,0.0002138287,0.006150334],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003371735,"threshold_uncertainty_score":0.01127958,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008553379776621541,"score_gpt":0.2320799719817822,"score_spread":0.2235265922051606,"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."}}