{"id":"W4401344934","doi":"10.1016/j.cose.2024.104034","title":"IoT-PRIDS: Leveraging packet representations for intrusion detection in IoT networks","year":2024,"lang":"en","type":"article","venue":"Computers & Security","topic":"Network Security and Intrusion Detection","field":"Computer Science","cited_by":52,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada; Research and Productivity Council; University of New Brunswick","funders":"Canadian Institute of Planners; National Research Council Canada","keywords":"Internet of Things; Computer science; Intrusion detection system; Network packet; Computer network; Computer security","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0007118401,0.000241422,0.0002496714,0.000402269,0.0003346983,0.0005687571,0.00059305,0.000178493,0.00001434453],"category_scores_gemma":[0.00004756231,0.0002563671,0.0001774544,0.001302557,0.00005437068,0.0005019949,0.0003805987,0.0005346581,0.00002089105],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000213648,"about_ca_system_score_gemma":0.00005766525,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001347376,"about_ca_topic_score_gemma":0.0002400622,"domain_scores_codex":[0.9977617,0.0001829296,0.0004625555,0.0008546853,0.0002602776,0.000477813],"domain_scores_gemma":[0.9987004,0.0004496615,0.00008573364,0.000547963,0.00009214866,0.0001240647],"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":[0.00008376695,0.0001967309,0.000162612,0.0002184545,0.00006795544,0.00007938981,0.007701234,0.05444074,0.00078558,0.02640588,0.01544355,0.8944141],"study_design_scores_gemma":[0.0003538736,0.0001144036,0.0006818717,0.0001833864,0.000009057311,0.00003846396,0.00003450371,0.9457791,0.001402526,0.02925157,0.02187391,0.0002772644],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1099173,0.0009155544,0.8816241,0.001363716,0.004909985,0.0005239779,0.0000025785,0.0006213639,0.0001214592],"genre_scores_gemma":[0.989563,0.0001088725,0.008879538,0.0004795837,0.0008383672,0.00007350331,0.00001216104,0.00002243597,0.00002251567],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8941368,"threshold_uncertainty_score":0.9999889,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01585681615057286,"score_gpt":0.2624055541270984,"score_spread":0.2465487379765256,"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."}}