{"id":"W1998406674","doi":"10.1109/globalsip.2014.7032111","title":"Cyber attack detection in PMU measurements via the expectation-maximization algorithm","year":2014,"lang":"en","type":"article","venue":"","topic":"Power System Optimization and Stability","field":"Engineering","cited_by":30,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Phasor measurement unit; Computer science; Electric power system; Phasor; Expectation–maximization algorithm; Identification (biology); Maximization; Units of measurement; Cyber-attack; Algorithm; Power (physics); Real-time computing; Data mining; Maximum likelihood; Mathematical optimization; Computer security; 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":[0.0003258143,0.00008691617,0.00008508922,0.00005840984,0.00005118642,0.0000297486,0.00007118534,0.00004909565,0.0001369995],"category_scores_gemma":[0.00005045352,0.00006717035,0.00002487738,0.0002389618,0.00001028051,0.0001410274,0.0000072843,0.00006133782,0.00005347222],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009801031,"about_ca_system_score_gemma":0.000004171422,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003322989,"about_ca_topic_score_gemma":0.0005026344,"domain_scores_codex":[0.9992952,0.00008803752,0.0002180336,0.0001146497,0.0001645989,0.0001195206],"domain_scores_gemma":[0.9996731,0.00003659717,0.000022182,0.0001798859,0.00005946177,0.00002877009],"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":[0.000006096855,0.00005090564,0.005915074,0.00003443252,0.00002961911,2.268133e-7,0.001986574,0.9027904,0.001424318,0.00003923896,0.0005544035,0.08716866],"study_design_scores_gemma":[0.0002381517,0.000007678605,0.01185252,0.000004955074,0.000002990855,0.000001027247,0.00006777638,0.9839594,0.002617186,0.00002849319,0.001128088,0.00009173418],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.008416544,0.00001645924,0.9787594,0.00004428979,0.000419111,0.0001956452,5.411487e-7,0.0001887922,0.01195921],"genre_scores_gemma":[0.9969404,0.00000263417,0.002845725,0.00004395556,0.00001970607,0.00003573007,0.000005559174,0.00001395315,0.00009231221],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9885239,"threshold_uncertainty_score":0.2739127,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01752512332048843,"score_gpt":0.2239417161685492,"score_spread":0.2064165928480608,"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."}}