{"id":"W3214290217","doi":"10.36227/techrxiv.16964857.v1","title":"CRESS: Framework for Vulnerability Assessment of Attack Scenarios in Hardware Reverse Engineering","year":2021,"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":"Infineon Technologies (Canada)","funders":"","keywords":"Computer science; Vulnerability (computing); Computer security; Reverse engineering; Vulnerability assessment; Honeypot; The Internet; Risk analysis (engineering); World Wide Web; Business","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":[0.01579016,0.003623864,0.001800269,0.01334717,0.001633929,0.008239335,0.004010846,0.00306019,0.009027853],"category_scores_gemma":[0.0368927,0.00115073,0.003831908,0.004597751,0.003281253,0.006350673,0.006041483,0.003697932,0.003545863],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003649614,"about_ca_system_score_gemma":0.004588292,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009690188,"about_ca_topic_score_gemma":0.0112236,"domain_scores_codex":[0.9844133,0.006790255,0.002234861,0.001239302,0.004600359,0.0007219587],"domain_scores_gemma":[0.9804816,0.009460841,0.002455813,0.002430201,0.004289039,0.0008825456],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0002433093,0.0003496989,0.01291862,0.001745077,0.000490327,0.0008525535,0.001965402,0.2069222,0.003984335,0.4896276,0.03173902,0.249162],"study_design_scores_gemma":[0.00004861085,0.0001679649,0.001860211,0.0005567333,0.0001043739,0.000674927,0.0007234815,0.7135112,0.002312086,0.2322686,0.04762536,0.0001464829],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00201352,0.0002376445,0.9872821,0.0003405091,0.00004769905,0.0005922203,0.0008854282,0.004568682,0.004032178],"genre_scores_gemma":[0.06386038,0.0003836541,0.929987,0.0001475864,0.00007955342,0.001025434,0.001944496,0.0004722457,0.002099606],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01579016,"threshold_uncertainty_score":0.0835073,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03761447533850017,"score_gpt":0.3275243052394257,"score_spread":0.2899098299009256,"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."}}