{"id":"W2750254065","doi":"10.5555/3107979.3107985","title":"Formal modeling and simulation to analyze the dynamics of malware propagation in networks using cell-DEVS","year":2017,"lang":"en","type":"article","venue":"Communications and Networking Symposium","topic":"Energy Efficient Wireless Sensor Networks","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Malware; Computer science; DEVS; Computer network; Distributed computing; Wireless network; Wireless; Channel (broadcasting); Wireless sensor network; Theoretical computer science; Modeling and simulation; Computer security; Simulation; Telecommunications","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":[0.001670623,0.0006961043,0.0006904629,0.001026888,0.0008146142,0.001279451,0.001349206,0.001011341,0.002539807],"category_scores_gemma":[0.004426812,0.0004621249,0.001427783,0.000633534,0.001527953,0.001949372,0.001144581,0.001594647,0.0002834636],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001847955,"about_ca_system_score_gemma":0.001551748,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007935628,"about_ca_topic_score_gemma":0.006845036,"domain_scores_codex":[0.9994085,0.0002066992,0.00004428052,0.00005931692,0.0001944102,0.00008677488],"domain_scores_gemma":[0.996885,0.002066597,0.0002717298,0.0003610717,0.0003032626,0.0001122286],"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":[0.00001361483,0.00003690831,0.0006525001,0.00004175592,0.0000246972,0.00007633378,0.0001068037,0.7882204,0.001339712,0.2056359,0.0004604922,0.003390871],"study_design_scores_gemma":[0.000005006173,0.000006137448,0.00003823684,0.000005695662,0.000005093687,0.0000115205,0.000009489127,0.9798534,0.0004233913,0.01847001,0.001168471,0.00000359813],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02716356,0.000251835,0.9646421,0.0005429173,0.00009357658,0.0001051318,0.0002059927,0.0005953149,0.006399579],"genre_scores_gemma":[0.6573526,0.001025865,0.33253,0.0002953155,0.0001333219,0.0007030353,0.0004868231,0.0003464862,0.007126633],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007935628,"threshold_uncertainty_score":0.0157789,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02948269444359464,"score_gpt":0.281069690587275,"score_spread":0.2515869961436804,"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."}}