{"id":"W2899962524","doi":"10.1109/tsmc.2018.2875250","title":"Input-Based Event-Triggering Consensus of Multiagent Systems Under Denial-of-Service Attacks","year":2018,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Systems","topic":"Distributed Control Multi-Agent Systems","field":"Computer Science","cited_by":259,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"Natural Science Foundation of Zhejiang Province","keywords":"Denial-of-service attack; Event (particle physics); Computer science; Computer security; Multi-agent system; Consensus; Denial; Distributed computing; Artificial intelligence; Psychology; World Wide Web; Physics; The Internet","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":[0.001103779,0.0006141847,0.001251439,0.0005477465,0.0002769986,0.0003707227,0.001024348,0.0003883938,0.000005392843],"category_scores_gemma":[0.00001440888,0.000590615,0.0002438007,0.0009254102,0.0002500519,0.000179722,0.00001769328,0.0002961563,0.00008648509],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002310938,"about_ca_system_score_gemma":0.0002373435,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004320871,"about_ca_topic_score_gemma":0.0002537145,"domain_scores_codex":[0.994364,0.00078745,0.002069019,0.0009400615,0.001144177,0.0006953008],"domain_scores_gemma":[0.9952834,0.0005082333,0.001159252,0.001627302,0.001040411,0.000381416],"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":[0.0003991711,0.001571383,0.0006545662,0.007980492,0.001810401,0.00008520324,0.003316424,0.9220727,0.04115658,0.0172436,0.001294992,0.002414479],"study_design_scores_gemma":[0.003376198,0.0006283202,0.0002120137,0.002289993,0.0001785126,0.0001763773,0.001450432,0.9795787,0.009072212,0.000008123642,0.002263392,0.0007657763],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09501059,0.001600601,0.892426,0.000123781,0.007753222,0.002072469,0.0002437837,0.0002626739,0.000506876],"genre_scores_gemma":[0.9985751,0.0000200743,0.0002776993,0.00004887589,0.0002231266,0.000217292,0.000006258692,0.00006639889,0.0005651613],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9035645,"threshold_uncertainty_score":0.9996545,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02514848116404525,"score_gpt":0.2549696866138593,"score_spread":0.229821205449814,"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."}}