{"id":"W1899838367","doi":"10.1002/sec.413","title":"A secure, efficient, and cost‐effective distributed architecture for spam mitigation on LTE 4G mobile networks","year":2012,"lang":"en","type":"article","venue":"Security and Communication Networks","topic":"Internet Traffic Analysis and Secure E-voting","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ericsson (Canada); Concordia University","funders":"","keywords":"Computer science; Computer network; Dimensioning; Flooding (psychology); Architecture; Distributed computing; Network packet; Network architecture; Cellular network; Computer security","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":[0.0005367904,0.0002715284,0.0003384765,0.0003981761,0.0005755699,0.0005729858,0.0008410853,0.0005503144,0.0008299767],"category_scores_gemma":[0.000865614,0.0001369735,0.0002128056,0.000234443,0.0005006939,0.0007154404,0.0005683651,0.0003707551,0.0002188163],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000892642,"about_ca_system_score_gemma":0.0005605684,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00142492,"about_ca_topic_score_gemma":0.001502655,"domain_scores_codex":[0.9997092,0.00008356275,0.00001568586,0.00004492534,0.0001004212,0.00004615183],"domain_scores_gemma":[0.9994823,0.0001108805,0.0000652919,0.0001228459,0.0001822581,0.00003637554],"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":[0.0008940585,0.0004153505,0.004692924,0.0001305994,0.00009835539,0.0004881356,0.0002909818,0.6011411,0.1682478,0.02461377,0.003120557,0.1958664],"study_design_scores_gemma":[0.00006379258,0.0002168998,0.0007021934,0.000004989854,0.00002925053,0.00007339772,0.00003002385,0.9707692,0.02326772,0.003345004,0.00148732,0.00001025465],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3848701,0.0002839411,0.6082618,0.0003209518,0.00005713735,0.0001580066,0.00002682506,0.001937362,0.004083816],"genre_scores_gemma":[0.9667805,0.00003470125,0.03215898,0.00003029619,0.00001145844,0.00002976724,0.00001561375,0.0000100853,0.0009285961],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00142492,"threshold_uncertainty_score":0.006476581,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006695986757950451,"score_gpt":0.2402966456008903,"score_spread":0.2336006588429398,"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."}}