{"id":"W4393308209","doi":"10.36227/techrxiv.171171935.55745155/v1","title":"Security Analysis of Digital-Based Physically Unclonable Functions: Dataset Generation, Machine Learning Modeling, and Correlation Analysis","year":2024,"lang":"en","type":"preprint","venue":"","topic":"Physical Unclonable Functions (PUFs) and Hardware Security","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Computer science; Correlation; Artificial intelligence; Security analysis; Pattern recognition (psychology); Machine learning; Computer security; Mathematics","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":[0.0004843175,0.000495124,0.001086691,0.001817322,0.000303236,0.001009513,0.0006652859,0.0002675196,0.0001092065],"category_scores_gemma":[0.0001338602,0.0004582627,0.0007850627,0.005566576,0.00009181242,0.0006526567,0.001824596,0.001065337,0.00003486198],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001263408,"about_ca_system_score_gemma":0.0003012862,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001311301,"about_ca_topic_score_gemma":0.00069001,"domain_scores_codex":[0.9963715,0.0001706902,0.0008193273,0.00155456,0.0007464365,0.0003374736],"domain_scores_gemma":[0.9972595,0.000188391,0.00035846,0.001439936,0.0005537135,0.0001999764],"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":[0.00001188481,0.0002835605,0.001527885,0.0001129721,0.005134634,0.000003508773,0.0001613963,0.9795099,0.00003468195,0.01117924,0.001217196,0.0008230938],"study_design_scores_gemma":[0.0001506818,0.00006349516,0.0001497633,0.00002053924,0.008248904,4.476163e-7,0.00001551159,0.9755405,0.00002999071,0.01427599,0.001064288,0.0004398612],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02645408,0.0005619613,0.9665852,0.0003970718,0.0003036506,0.0002730915,0.004372717,0.0003468845,0.0007053005],"genre_scores_gemma":[0.9561863,0.00005202682,0.002410259,0.00009147577,0.000140823,0.00005286907,0.0406399,0.00002117923,0.000405186],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.964175,"threshold_uncertainty_score":0.9997869,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02032290468560098,"score_gpt":0.2533481241082178,"score_spread":0.2330252194226168,"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."}}