{"id":"W7116969372","doi":"10.18280/mmep.121130","title":"A Deep Learning Framework for Black Hole Attack Detection in SDN-Integrated MANET-IoT Environments","year":2025,"lang":"","type":"article","venue":"Mathematical Modelling and Engineering Problems","topic":"Network Security and Intrusion Detection","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Deep learning; Black box; Feature (linguistics); Artificial neural network; Deep hole drilling; Noise (video)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.001085811,0.0005883987,0.0008868171,0.0005790521,0.0003982958,0.0009992588,0.001723098,0.001037646,0.001719773],"category_scores_gemma":[0.001842269,0.0003768103,0.0005798629,0.0005602741,0.0005851444,0.001414262,0.001553606,0.001553408,0.0002974257],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001048405,"about_ca_system_score_gemma":0.001621629,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01005623,"about_ca_topic_score_gemma":0.01073535,"domain_scores_codex":[0.999635,0.00007784347,0.00001706242,0.00007658153,0.0001032235,0.00009028795],"domain_scores_gemma":[0.9993597,0.0002459375,0.00005630792,0.00005180086,0.000228743,0.00005746035],"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":[0.00008315982,0.00009543946,0.0009981868,0.00005307479,0.0000691306,0.00006259359,0.000028986,0.8915625,0.001910295,0.01953942,0.002336983,0.08326026],"study_design_scores_gemma":[9.801824e-7,0.000004866522,0.00002747146,0.00000153056,0.000002116011,0.000002846951,0.000001558962,0.9976571,0.0001246779,0.00207712,0.00009860413,0.000001094388],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01055059,0.0002943969,0.9874135,0.0002203926,0.00004599165,0.00001916691,0.00006343053,0.0004177462,0.0009747702],"genre_scores_gemma":[0.7464718,0.0006153014,0.2457544,0.0003347892,0.0001246293,0.0001312274,0.0004118484,0.000102954,0.006053003],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01005623,"threshold_uncertainty_score":0.01999539,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01853394159434252,"score_gpt":0.2262892380206708,"score_spread":0.2077552964263283,"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."}}