{"id":"W4391974622","doi":"10.1109/mnet.2024.3367788","title":"A Comprehensive Overview of Backdoor Attacks in Large Language Models Within Communication Networks","year":2024,"lang":"en","type":"article","venue":"IEEE Network","topic":"Network Security and Intrusion Detection","field":"Computer Science","cited_by":51,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of New Brunswick","funders":"National Key Research and Development Program of China; National Natural Science Foundation of China","keywords":"Backdoor; Computer science; Computer security; Computer network; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006376097,0.0001726059,0.0002962956,0.0001093383,0.00009898418,0.0001217557,0.0007026851,0.0001577325,0.00001770503],"category_scores_gemma":[0.00000507132,0.0001676226,0.0001078337,0.001345705,0.00004856895,0.000608427,0.0002533639,0.000497075,0.00002655502],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005428291,"about_ca_system_score_gemma":0.00004364792,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001001119,"about_ca_topic_score_gemma":0.0003745286,"domain_scores_codex":[0.9982597,0.0003044051,0.0004797473,0.0003572496,0.0002335337,0.0003653233],"domain_scores_gemma":[0.9987073,0.0002683084,0.0001220115,0.0007693019,0.00006929615,0.00006381103],"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":[0.00003747379,0.00008662719,0.00006177324,0.0001615855,0.00004440761,0.00003381168,0.004040756,0.902602,0.00008084194,0.06113693,0.01889663,0.01281723],"study_design_scores_gemma":[0.0002262298,0.00005347524,0.0002370362,0.0007622679,0.000007983343,0.00001271186,0.00004603397,0.976647,0.0000697398,0.01432356,0.007441097,0.0001729301],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1525419,0.1600395,0.6692076,0.0006758089,0.01142687,0.0009778553,0.00001241188,0.0007743528,0.0043437],"genre_scores_gemma":[0.9927641,0.002467908,0.003343431,0.0005330367,0.0007590801,0.00002618699,0.00001067298,0.00001949113,0.00007614541],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8402221,"threshold_uncertainty_score":0.6835452,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03520444815215881,"score_gpt":0.2945481379891765,"score_spread":0.2593436898370177,"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."}}