{"id":"W2158223124","doi":"10.1109/infcom.2009.5062146","title":"An Efficient Privacy-Preserving Scheme against Traffic Analysis Attacks in Network Coding","year":2009,"lang":"en","type":"article","venue":"","topic":"Cooperative Communication and Network Coding","field":"Computer Science","cited_by":88,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Linear network coding; Computer science; Homomorphic encryption; Network packet; Computer network; Traffic analysis; Coding (social sciences); Security analysis; Encryption; Computer security; Mathematics","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":[0.002109293,0.0006861158,0.0008432934,0.0008628449,0.001000423,0.001216091,0.001444895,0.001255671,0.0008685163],"category_scores_gemma":[0.007056665,0.0003041241,0.0005591329,0.00122733,0.001672751,0.003211278,0.003266617,0.001445532,0.0003257717],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008792493,"about_ca_system_score_gemma":0.00144873,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004895499,"about_ca_topic_score_gemma":0.0003056562,"domain_scores_codex":[0.9969228,0.001042548,0.0001643042,0.0003834339,0.0010896,0.0003973205],"domain_scores_gemma":[0.9944978,0.001867715,0.0008081188,0.001962193,0.0006894129,0.0001748417],"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":[0.0009914816,0.000232021,0.001181536,0.0002779289,0.0001253079,0.0005847469,0.0009681072,0.2090539,0.1017387,0.467187,0.003502181,0.2141571],"study_design_scores_gemma":[0.0001186012,0.0003501299,0.000347557,0.00005068263,0.00007597545,0.0008385774,0.0001185119,0.8158522,0.06332818,0.1129484,0.005874818,0.00009649201],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04489648,0.0002160685,0.9505081,0.0003829422,0.0000492136,0.0001278988,0.00008027509,0.000351174,0.003387851],"genre_scores_gemma":[0.8934371,0.0002028072,0.1030565,0.0001518168,0.0000543996,0.0001618312,0.0001133152,0.00003117746,0.002790987],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002109293,"threshold_uncertainty_score":0.01115513,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03127791796280333,"score_gpt":0.3042366616767051,"score_spread":0.2729587437139018,"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."}}