{"id":"W4414199074","doi":"10.1109/dac63849.2025.11132094","title":"RAP-Track: Efficient Control Flow Attestation via Parallel Tracking in Commodity MCUs","year":2025,"lang":"en","type":"article","venue":"","topic":"Security and Verification in Computing","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"TRACE (psycholinguistics); Control flow; Context (archaeology); Control (management); Flow control (data); Instrumentation (computer programming); Code (set theory); Flow (mathematics); Commodity; Track (disk drive)","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000978951,0.000947988,0.0005819918,0.001102909,0.0008086856,0.001156265,0.002539272,0.0006974606,0.004701553],"category_scores_gemma":[0.004583703,0.000521105,0.0004398584,0.0009283283,0.001198018,0.002658493,0.0022359,0.001162398,0.001003084],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001053785,"about_ca_system_score_gemma":0.00265007,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005933184,"about_ca_topic_score_gemma":0.005414878,"domain_scores_codex":[0.9982743,0.0002445775,0.0001036472,0.0004102601,0.0007085294,0.0002586379],"domain_scores_gemma":[0.9969345,0.0007207605,0.0004094547,0.00138231,0.0003928347,0.0001602115],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.005209106,0.0005788164,0.013841,0.0006973144,0.0002021072,0.001227885,0.001129473,0.105751,0.1684179,0.03693179,0.02668672,0.639327],"study_design_scores_gemma":[0.0002399386,0.0009652427,0.002411921,0.00009591089,0.0001183994,0.0006554695,0.0001262997,0.7414079,0.2148593,0.01125921,0.02772603,0.0001342858],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2647052,0.001882857,0.6393756,0.0004062829,0.0003211156,0.0006072031,0.000490211,0.08178572,0.01042589],"genre_scores_gemma":[0.8122739,0.0001929197,0.181882,0.0002081435,0.00003890603,0.0001953092,0.000327391,0.00084198,0.004039448],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005933184,"threshold_uncertainty_score":0.01572829,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01685712802893225,"score_gpt":0.2786980902551329,"score_spread":0.2618409622262006,"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."}}