{"id":"W4384519193","doi":"10.1109/access.2023.3296311","title":"5G Aviation Networks Using Novel AI Approach for DDoS Detection","year":2023,"lang":"en","type":"article","venue":"IEEE Access","topic":"Anomaly Detection Techniques and Applications","field":"Computer Science","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Cranfield University; Government of the United Kingdom; Department of Transport, UK Government","keywords":"Computer science; Denial-of-service attack; Deep learning; Convolutional neural network; Artificial intelligence; Robustness (evolution); Feature extraction; Data mining; Machine learning; Real-time computing; Pattern recognition (psychology)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003517284,0.0009054836,0.0004451898,0.001127572,0.0003118255,0.0006353668,0.0006781743,0.0005345746,0.001357836],"category_scores_gemma":[0.0008544527,0.0001724993,0.0005228489,0.000691561,0.0002235642,0.0008084799,0.0004620791,0.0006794556,0.0005277271],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007397817,"about_ca_system_score_gemma":0.0005427051,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01070714,"about_ca_topic_score_gemma":0.0119548,"domain_scores_codex":[0.9997137,0.0000448579,0.00001364456,0.00006055259,0.0001090237,0.0000582363],"domain_scores_gemma":[0.9997845,0.00006039931,0.00003414146,0.00002326634,0.00008435117,0.00001329772],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002556943,0.0001976755,0.005807479,0.0001139723,0.0001373948,0.00033565,0.00009620183,0.4607551,0.02206566,0.006025657,0.004855612,0.4993538],"study_design_scores_gemma":[0.000003738305,0.0000349771,0.0006533516,0.000003994126,0.00001125027,0.00005019731,0.00001586915,0.99429,0.002708939,0.001177181,0.001044785,0.00000571419],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1464535,0.00232701,0.8307917,0.0008099832,0.000438175,0.0002413522,0.0005461889,0.003949567,0.01444258],"genre_scores_gemma":[0.8546879,0.0006711052,0.1362873,0.0003047525,0.0001555218,0.0001007064,0.0007288155,0.0000567382,0.007007152],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01070714,"threshold_uncertainty_score":0.02128965,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07753624705448252,"score_gpt":0.3513351605599842,"score_spread":0.2737989135055017,"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."}}