{"id":"W2788959741","doi":"10.48550/arxiv.1802.08415","title":"TARANET: Traffic-Analysis Resistant Anonymity at the NETwork layer","year":2018,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Internet Traffic Analysis and Secure E-voting","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal","funders":"Zurich Information Security and Privacy Center; Eidgenössische Technische Hochschule Zürich; European Commission","keywords":"Computer science; Anonymity; Computer network; Latency (audio); Network packet; Traffic analysis; Overhead (engineering); Network layer; Overlay network; Layer (electronics); Computer security; Telecommunications; The Internet; Operating system","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001160294,0.00051064,0.0007731182,0.0002322128,0.0006603728,0.0003180008,0.003666066,0.0003865003,0.0004598047],"category_scores_gemma":[0.00003506015,0.0004186961,0.001281835,0.002223935,0.0002935448,0.0001910953,0.002996971,0.0007708991,0.0003058728],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003491501,"about_ca_system_score_gemma":0.0001445216,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001278916,"about_ca_topic_score_gemma":0.004056153,"domain_scores_codex":[0.9962282,0.0005238276,0.0004634776,0.001784397,0.0002771262,0.0007229373],"domain_scores_gemma":[0.9968337,0.000273464,0.000581056,0.001819772,0.0002967167,0.000195228],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00004823374,0.00004652305,0.0004524712,0.00001409817,0.001844725,0.0001884687,0.0003312116,0.935272,0.000001418028,0.05578014,0.005901394,0.0001192588],"study_design_scores_gemma":[0.0001891991,0.00004158557,0.0008847649,0.0000344112,0.001640825,0.000002596597,0.00004605949,0.9926764,0.000007729809,0.0003216502,0.003650969,0.0005037622],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.528342,0.0002081448,0.4682929,0.0001944219,0.0005562562,0.0002097619,0.00001522388,0.000214079,0.001967197],"genre_scores_gemma":[0.9921643,0.00007272451,0.0006418059,0.0002730341,0.0003938974,0.000001127348,0.00004484641,0.00002177226,0.006386516],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4676511,"threshold_uncertainty_score":0.9998265,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04879770286016186,"score_gpt":0.1892530254033777,"score_spread":0.1404553225432158,"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."}}