{"id":"W4291972620","doi":"10.1145/3556977","title":"Practical Software-Based Shadow Stacks on x86-64","year":2022,"lang":"en","type":"article","venue":"ACM Transactions on Architecture and Code Optimization","topic":"Security and Verification in Computing","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Huawei Technologies (Canada)","funders":"Australian Research Council; University of New South Wales","keywords":"Computer science; x86; Spec#; Operating system; Call stack; Software; Backward compatibility; Embedded system; Stack (abstract data type); Programming language","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":[0.0008051678,0.0007790398,0.0004182004,0.0006355997,0.0007632247,0.001191126,0.001355997,0.00053046,0.004650044],"category_scores_gemma":[0.002231286,0.0006088362,0.0004290626,0.0006111466,0.001030713,0.003261217,0.001714574,0.001128643,0.001164115],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001081846,"about_ca_system_score_gemma":0.001548772,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002230522,"about_ca_topic_score_gemma":0.002124442,"domain_scores_codex":[0.9990861,0.0001494826,0.00008257097,0.0001380511,0.0002796669,0.0002640986],"domain_scores_gemma":[0.9985598,0.00024883,0.0001693963,0.0007053986,0.0002505518,0.00006606329],"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":[0.003586116,0.0004224014,0.01504587,0.001168092,0.0001644886,0.0009555906,0.001887173,0.06078528,0.2418045,0.1694725,0.02620722,0.4785008],"study_design_scores_gemma":[0.0003398223,0.001606469,0.005128109,0.0003203773,0.00026084,0.000898593,0.0005077283,0.2933356,0.496707,0.05835138,0.1423594,0.0001848833],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3997771,0.002552242,0.5369815,0.0006144834,0.0002223803,0.0003456404,0.0003597764,0.03414208,0.02500486],"genre_scores_gemma":[0.8805251,0.0005836547,0.1090073,0.0002680221,0.00003510907,0.0001509975,0.0003492846,0.001211233,0.007869374],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004650044,"threshold_uncertainty_score":0.01555598,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02701125114130588,"score_gpt":0.2751519209897549,"score_spread":0.2481406698484491,"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."}}