{"id":"W3216949739","doi":"10.1109/lwc.2021.3130169","title":"Exploiting RIS for Limiting Information Leakage to Active Eavesdropper in Cell-Free Massive MIMO","year":2021,"lang":"en","type":"article","venue":"IEEE Wireless Communications Letters","topic":"Advanced Wireless Communication Technologies","field":"Engineering","cited_by":42,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Robustness (evolution); Secrecy; Spoofing attack; Boosting (machine learning); Information leakage; Limiting; MIMO; Telecommunications link; Computer network; Distributed computing; Computer security; Engineering; Channel (broadcasting); Artificial intelligence","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0001760731,0.0002657643,0.0003132033,0.000423706,0.0003111782,0.0001017155,0.002037061,0.0001438977,0.000005555501],"category_scores_gemma":[0.000315412,0.0003416704,0.0001003332,0.0008385769,0.0001217005,0.0007782809,0.000637876,0.0006098104,0.00004319974],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004111954,"about_ca_system_score_gemma":0.00003956478,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002324819,"about_ca_topic_score_gemma":0.0001584235,"domain_scores_codex":[0.9984149,0.0001044273,0.0006352941,0.0002194649,0.0001769864,0.000448954],"domain_scores_gemma":[0.9954375,0.0007607389,0.0001601266,0.003373956,0.0001949099,0.00007278265],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00002882074,0.0001519654,0.0004463829,0.0002718344,0.00009341788,0.000006394704,0.008089265,0.4130983,0.4021701,0.005072681,0.005038417,0.1655325],"study_design_scores_gemma":[0.002194229,0.00003995413,0.00121163,0.0005498872,0.00003192069,0.00001068673,0.02143317,0.1663602,0.7797223,0.0008994135,0.02621821,0.001328414],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6329221,0.0004477932,0.3442827,0.01730042,0.0002328365,0.0009752982,0.0001582679,0.001225276,0.00245528],"genre_scores_gemma":[0.8988909,0.000584533,0.09821999,0.0009852452,0.00002333832,0.001075651,0.0001459944,0.00005986862,0.0000144516],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3775523,"threshold_uncertainty_score":0.9999036,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0215606033871614,"score_gpt":0.2482985295876757,"score_spread":0.2267379262005143,"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."}}