{"id":"W7117359608","doi":"10.1007/s41870-025-02989-w","title":"Intruder Detection in Driverless Cars Using Collaborated Learning with Self-Attention Mechanism and Long Short-Term Memory Architecture","year":2025,"lang":"en","type":"article","venue":"International Journal of Information Technology","topic":"Vehicular Ad Hoc Networks (VANETs)","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Enabling; Intrusion detection system; Automotive industry; Edge computing; Edge device; Architecture; Key (lock); Enhanced Data Rates for GSM Evolution; Exploit","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":[0.0001911752,0.000117172,0.0001612279,0.001576591,0.00004071261,0.00007292486,0.0001768081,0.0001802635,0.000003734658],"category_scores_gemma":[0.00003861505,0.0001121277,0.00002181071,0.0006642357,0.00003303802,0.0006426317,0.00004445594,0.0005421495,0.000001025665],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003614865,"about_ca_system_score_gemma":0.00006342808,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003896567,"about_ca_topic_score_gemma":0.00007359772,"domain_scores_codex":[0.9991258,0.00002421681,0.000442668,0.00006111766,0.0002103762,0.0001357682],"domain_scores_gemma":[0.9992098,0.00001963185,0.0001660385,0.00006050547,0.0005186236,0.00002541833],"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":[0.00005682925,0.00001322355,0.009211755,0.0000367903,0.0002514333,0.00004668094,0.0003884521,0.914731,0.008502934,0.000636019,0.000005853529,0.06611898],"study_design_scores_gemma":[0.002557166,0.0001780077,0.01552497,0.0007650958,0.00008875169,0.002075071,0.001917298,0.9323676,0.0418669,0.001966469,0.0003636443,0.000328989],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7376906,0.00006984405,0.2615275,0.0001074789,0.0003442306,0.00009390448,0.000001011274,0.00009561135,0.00006973925],"genre_scores_gemma":[0.9966246,0.00008951323,0.003206988,0.00002473358,0.00003044265,0.000004484813,0.000007030433,0.000008829098,0.000003379513],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.258934,"threshold_uncertainty_score":0.4572434,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.001965916788809114,"score_gpt":0.2005826457944011,"score_spread":0.198616729005592,"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."}}