{"id":"W2054673916","doi":"10.1109/3pgcic.2012.12","title":"Assessing Trade-Offs between Stealthiness and Node Recruitment Rates in Peer-to-Peer Botnets","year":2012,"lang":"en","type":"article","venue":"","topic":"Network Security and Intrusion Detection","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"","keywords":"Botnet; Computer security; Computer science; Resilience (materials science); Peer-to-peer; Denial-of-service attack; Command and control; Computer network; Adversary; Node (physics); Malware; The Internet; Engineering; World Wide Web","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":[0.003834913,0.0006029811,0.000556241,0.001671293,0.0004704706,0.001072915,0.0007785904,0.001433498,0.0006045909],"category_scores_gemma":[0.02532002,0.0003538374,0.0003465455,0.0007415232,0.0011373,0.002489172,0.001104189,0.0007544599,0.0002598324],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008984528,"about_ca_system_score_gemma":0.0002919167,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009696508,"about_ca_topic_score_gemma":0.000904879,"domain_scores_codex":[0.9980035,0.0006890358,0.0001377301,0.0003356442,0.0005005247,0.0003334669],"domain_scores_gemma":[0.9700096,0.02234896,0.003874752,0.001539693,0.001326138,0.0009008878],"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":[0.001425787,0.0007530483,0.09001777,0.0002443959,0.0001955766,0.0006482109,0.0005139756,0.8037663,0.05504017,0.007670438,0.0006162924,0.03910807],"study_design_scores_gemma":[0.00003623392,0.001792775,0.0334723,0.00003898924,0.00005665715,0.0006668345,0.0003187042,0.9321618,0.02527028,0.005762456,0.0003633783,0.00005955357],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9811183,0.0002230266,0.01676802,0.00007440287,0.000008615756,0.00005144485,0.00006104719,0.00009869439,0.001596389],"genre_scores_gemma":[0.9974697,0.00006825772,0.002126719,0.00000944037,0.000003538222,0.00002026528,0.00003471873,0.000008912547,0.0002584773],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003834913,"threshold_uncertainty_score":0.02028126,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09554701017489402,"score_gpt":0.3542093914981737,"score_spread":0.2586623813232797,"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."}}