{"id":"W4309091762","doi":"10.3390/math10214097","title":"Detection and Mitigation of GNSS Spoofing Attacks in Maritime Environments Using a Genetic Algorithm","year":2022,"lang":"en","type":"article","venue":"Mathematics","topic":"Maritime Navigation and Safety","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"Wilfrid Laurier University","funders":"Korea Institute of Energy Technology Evaluation and Planning","keywords":"GNSS applications; Spoofing attack; Computer science; Real-time computing; Satellite system; Mean squared error; GNSS augmentation; Genetic algorithm; MATLAB; Algorithm; Global Positioning System; Data mining; Computer security; Telecommunications; Machine learning; Statistics; 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":[],"consensus_categories":[],"category_scores_codex":[0.0001301952,0.00006420276,0.0001058753,0.00007477612,0.00004481051,0.000006894793,0.00003687298,0.00002743616,0.0001113248],"category_scores_gemma":[0.000006965233,0.00008126219,0.00001691287,0.0001080888,0.00001484473,0.00003750599,0.0000388546,0.00009423203,0.000001585026],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008372562,"about_ca_system_score_gemma":0.000003414094,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008984089,"about_ca_topic_score_gemma":0.000001882467,"domain_scores_codex":[0.9994637,0.00002036204,0.0002261726,0.00006870776,0.0001347861,0.00008625948],"domain_scores_gemma":[0.9998299,0.0000283088,0.00003805243,0.00008001921,0.000003535366,0.00002020836],"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":[0.00001056851,0.0003838904,0.003226851,0.001365709,0.00008497813,0.00003426716,0.007464371,0.6144363,0.175971,0.0003062534,0.00002815437,0.1966877],"study_design_scores_gemma":[0.0002296109,0.00001500827,0.002671127,0.00002332064,0.000009723351,0.00002544073,0.0002136127,0.9906036,0.005053623,0.0009158948,0.000156573,0.00008250777],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7634451,0.00008997358,0.2358294,0.000005740879,0.00005814271,0.000159509,0.00001345781,0.00002351329,0.0003751663],"genre_scores_gemma":[0.9474848,0.00001490022,0.05241212,0.000006620328,0.000009932795,0.00001420917,0.000005317714,0.00001728437,0.00003483145],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3761673,"threshold_uncertainty_score":0.3313776,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00875031906668659,"score_gpt":0.2074323502647753,"score_spread":0.1986820311980887,"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."}}