{"id":"W4410395021","doi":"10.1109/qcnc64685.2025.00084","title":"Cascade Error Correction Attack; Exploiting Implicit and Side Channel Information Leakage","year":2025,"lang":"en","type":"article","venue":"","topic":"Cryptographic Implementations and Security","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Queen's University; Queen's University Belfast; UK Research and Innovation; Government of the United Kingdom","keywords":"Side channel attack; Computer science; Cascade; Leakage (economics); Information leakage; Channel (broadcasting); Computer security; Computer network; Cryptography; Engineering","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001742743,0.0000758132,0.00007558866,0.0002342993,0.0002491316,0.0002224442,0.0001383722,0.00003306863,0.000007645153],"category_scores_gemma":[0.00002756171,0.00007210815,0.00002819533,0.0004740653,0.00001667932,0.001293152,0.0001387878,0.00007578783,0.000007547089],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002210603,"about_ca_system_score_gemma":0.00002462591,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003488557,"about_ca_topic_score_gemma":0.0002486356,"domain_scores_codex":[0.9993796,0.00001956335,0.0002119426,0.0001347274,0.00009543906,0.0001586635],"domain_scores_gemma":[0.9996325,0.00005847867,0.00005422224,0.0001604888,0.00005911403,0.00003521344],"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":[0.00001043848,0.000056976,0.002260282,0.00008013584,0.00004681694,0.000002441437,0.01133466,0.0001969631,0.000843143,0.3468197,0.01722379,0.6211247],"study_design_scores_gemma":[0.001176566,0.000108449,0.05402587,0.00005960145,0.00001875172,0.00005005317,0.008937353,0.8983641,0.005173301,0.009190497,0.02247293,0.0004225055],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1359789,0.00001947405,0.8512202,0.001002516,0.0004753637,0.0001551956,0.000001836579,0.0001514408,0.01099508],"genre_scores_gemma":[0.9940308,0.0000161539,0.00471378,0.001045751,0.0000162504,0.00002445589,0.000008868325,0.000001695561,0.0001421966],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8981671,"threshold_uncertainty_score":0.2940485,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02181531629193163,"score_gpt":0.2991980154108788,"score_spread":0.2773826991189471,"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."}}