{"id":"W4407102832","doi":"10.1145/3716139","title":"DSADA: Detecting Spoofing Attacks in Driver Assistance Systems Using Objects’ Spatial Shapes","year":2025,"lang":"en","type":"article","venue":"ACM Transactions on Autonomous and Adaptive Systems","topic":"Advanced Malware Detection Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Computer science; Spoofing attack; Computer security; Computer vision; Artificial intelligence","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003891064,0.0003101935,0.0004436133,0.00057911,0.0004694812,0.0002824442,0.0005112566,0.0001691996,0.000001964917],"category_scores_gemma":[0.00003608214,0.0003221571,0.00008629469,0.0006640275,0.00007097521,0.0006370905,0.00004382506,0.0004212346,0.00000302732],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005836487,"about_ca_system_score_gemma":0.0001496506,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002535664,"about_ca_topic_score_gemma":0.0005300736,"domain_scores_codex":[0.9978567,0.0001966561,0.0005661655,0.00075229,0.0002253455,0.0004028905],"domain_scores_gemma":[0.9987217,0.0003070032,0.0002189502,0.0005469326,0.0001257023,0.00007969583],"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":[0.0001614533,0.0003052973,0.0004147324,0.0004902852,0.0002635692,0.0001739552,0.001960995,0.3229579,0.0178164,0.01083578,0.00001566512,0.644604],"study_design_scores_gemma":[0.0009207976,0.0003149565,0.001893523,0.001585787,0.00003900291,0.0001169956,0.001962374,0.9773571,0.0121244,0.0008487623,0.00205344,0.0007828292],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01168824,0.0007168663,0.9848197,0.00007749889,0.001001222,0.0006556655,0.00001075552,0.0005354519,0.0004945988],"genre_scores_gemma":[0.9756776,0.00005262669,0.0236548,0.00004729535,0.0000433517,0.0001373286,3.340326e-7,0.00002173168,0.0003649341],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9639894,"threshold_uncertainty_score":0.9999231,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0234804078940159,"score_gpt":0.2695694232527809,"score_spread":0.246089015358765,"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."}}