{"id":"https://openalex.org/W4391422715","doi":"https://doi.org/10.1109/ias54024.2023.10406934","title":"Data-Driven Based FDIAs Detection and Sensitive Feature Identification for Cyberattack Defending of Renewable Energy","display_name":"Data-Driven Based FDIAs Detection and Sensitive Feature Identification for Cyberattack Defending of Renewable Energy","publication_year":2023,"publication_date":"2023-10-29","ids":{"openalex":"https://openalex.org/W4391422715","doi":"https://doi.org/10.1109/ias54024.2023.10406934"},"language":"en","primary_location":{"id":"doi:10.1109/ias54024.2023.10406934","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/ias54024.2023.10406934","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE Industry Applications Society Annual Meeting (IAS)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5037711773","display_name":"Yidian Gao","orcid":"https://orcid.org/0000-0002-5979-2677"},"institutions":[{"id":"https://openalex.org/I154099455","display_name":"Shandong University","ror":"https://ror.org/0207yh398","country_code":"CN","type":"education","lineage":["https://openalex.org/I154099455"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yidian Gao","raw_affiliation_strings":["School of Electrical Engineering, Shandong University,Jinan,China","School of Electrical Engineering, Shandong University, Jinan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electrical Engineering, Shandong University,Jinan,China","institution_ids":["https://openalex.org/I154099455"]},{"raw_affiliation_string":"School of Electrical Engineering, Shandong University, Jinan, China","institution_ids":["https://openalex.org/I154099455"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078457934","display_name":"Kaiqi Sun","orcid":"https://orcid.org/0000-0002-5992-0309"},"institutions":[{"id":"https://openalex.org/I16609230","display_name":"Hunan University","ror":"https://ror.org/05htk5m33","country_code":"CN","type":"education","lineage":["https://openalex.org/I16609230"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kaiqi Sun","raw_affiliation_strings":["Hunan University,Department of Electrical &#x0026; Electronic Engineering,Hunan,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hunan University,Department of Electrical &#x0026; Electronic Engineering,Hunan,China","institution_ids":["https://openalex.org/I16609230"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5056837698","display_name":"Wei Qiu","orcid":"https://orcid.org/0000-0003-3348-1659"},"institutions":[{"id":"https://openalex.org/I153473198","display_name":"North China Electric Power University","ror":"https://ror.org/04qr5t414","country_code":"CN","type":"education","lineage":["https://openalex.org/I153473198"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Qiu","raw_affiliation_strings":["School of Electrical &#x0026; Electronic Engineering, North China Electric Power University,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electrical &#x0026; Electronic Engineering, North China Electric Power University,Beijing,China","institution_ids":["https://openalex.org/I153473198"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050395122","display_name":"Zhaohao Ding","orcid":"https://orcid.org/0000-0002-7085-260X"},"institutions":[{"id":"https://openalex.org/I154099455","display_name":"Shandong University","ror":"https://ror.org/0207yh398","country_code":"CN","type":"education","lineage":["https://openalex.org/I154099455"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhaohao Ding","raw_affiliation_strings":["School of Electrical Engineering, Shandong University,Jinan,China","School of Electrical Engineering, Shandong University, Jinan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electrical Engineering, Shandong University,Jinan,China","institution_ids":["https://openalex.org/I154099455"]},{"raw_affiliation_string":"School of Electrical Engineering, Shandong University, Jinan, China","institution_ids":["https://openalex.org/I154099455"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100633721","display_name":"Ke\u2010Jun Li","orcid":"https://orcid.org/0000-0002-7255-9044"},"institutions":[{"id":"https://openalex.org/I154099455","display_name":"Shandong University","ror":"https://ror.org/0207yh398","country_code":"CN","type":"education","lineage":["https://openalex.org/I154099455"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ke-Jun Li","raw_affiliation_strings":["School of Electrical Engineering, Shandong University,Jinan,China","School of Electrical Engineering, Shandong University, Jinan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electrical Engineering, Shandong University,Jinan,China","institution_ids":["https://openalex.org/I154099455"]},{"raw_affiliation_string":"School of Electrical Engineering, Shandong University, Jinan, China","institution_ids":["https://openalex.org/I154099455"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100445687","display_name":"Yahui Li","orcid":"https://orcid.org/0000-0002-7094-4053"},"institutions":[{"id":"https://openalex.org/I154099455","display_name":"Shandong University","ror":"https://ror.org/0207yh398","country_code":"CN","type":"education","lineage":["https://openalex.org/I154099455"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yahui Li","raw_affiliation_strings":["School of Electrical Engineering, Shandong University,Jinan,China","School of Electrical Engineering, Shandong University, Jinan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electrical Engineering, Shandong University,Jinan,China","institution_ids":["https://openalex.org/I154099455"]},{"raw_affiliation_string":"School of Electrical Engineering, Shandong University, Jinan, China","institution_ids":["https://openalex.org/I154099455"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5037711773"],"corresponding_institution_ids":["https://openalex.org/I154099455"],"apc_list":null,"apc_paid":null,"fwci":0.1778,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.5244785,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"7"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10917","display_name":"Smart Grid Security and Resilience","score":1.0,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10917","display_name":"Smart Grid Security and Resilience","score":1.0,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10400","display_name":"Network Security and Intrusion Detection","score":0.9976000189781189,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11241","display_name":"Advanced Malware Detection Techniques","score":0.9925000071525574,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8009530305862427},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.6612731218338013},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.5962251424789429},{"id":"https://openalex.org/keywords/smart-grid","display_name":"Smart grid","score":0.5221726894378662},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.5175168514251709},{"id":"https://openalex.org/keywords/softmax-function","display_name":"Softmax function","score":0.5015342235565186},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.49196168780326843},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.4667741656303406},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4342951774597168},{"id":"https://openalex.org/keywords/curse-of-dimensionality","display_name":"Curse of dimensionality","score":0.42713651061058044},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3869740664958954},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.34609830379486084},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.2734805941581726},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.10506319999694824}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8009530305862427},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.6612731218338013},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.5962251424789429},{"id":"https://openalex.org/C10558101","wikidata":"https://www.wikidata.org/wiki/Q689855","display_name":"Smart grid","level":2,"score":0.5221726894378662},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.5175168514251709},{"id":"https://openalex.org/C188441871","wikidata":"https://www.wikidata.org/wiki/Q7554146","display_name":"Softmax function","level":3,"score":0.5015342235565186},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.49196168780326843},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.4667741656303406},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4342951774597168},{"id":"https://openalex.org/C111030470","wikidata":"https://www.wikidata.org/wiki/Q1430460","display_name":"Curse of dimensionality","level":2,"score":0.42713651061058044},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3869740664958954},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.34609830379486084},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.2734805941581726},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.10506319999694824},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ias54024.2023.10406934","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/ias54024.2023.10406934","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE Industry Applications Society Annual Meeting (IAS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/7","display_name":"Affordable and clean energy","score":0.7200000286102295}],"awards":[{"id":"https://openalex.org/G2526863840","display_name":null,"funder_award_id":"52207119","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7637561847","display_name":null,"funder_award_id":"ZR2022QE117","funder_id":"https://openalex.org/F4320324174","funder_display_name":"Natural Science Foundation of Shandong Province"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320324174","display_name":"Natural Science Foundation of Shandong Province","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W1979654427","https://openalex.org/W2071821151","https://openalex.org/W2550453031","https://openalex.org/W2586525912","https://openalex.org/W2765523472","https://openalex.org/W2968286741","https://openalex.org/W2993388523","https://openalex.org/W3027095575","https://openalex.org/W3043746430","https://openalex.org/W3113057209","https://openalex.org/W3134285550","https://openalex.org/W3161160973","https://openalex.org/W3163714250","https://openalex.org/W3197686036","https://openalex.org/W3201571347","https://openalex.org/W3215256866","https://openalex.org/W4205864460","https://openalex.org/W4226482139","https://openalex.org/W4229447903","https://openalex.org/W4290997507"],"related_works":["https://openalex.org/W3107204728","https://openalex.org/W4287591324","https://openalex.org/W3108503355","https://openalex.org/W4226420367","https://openalex.org/W2962876041","https://openalex.org/W3090555870","https://openalex.org/W3022820045","https://openalex.org/W2801655600","https://openalex.org/W3005627584","https://openalex.org/W1980222719"],"abstract_inverted_index":{"With":[0],"the":[1,9,20,28,36,39,44,76,90,94,113,127,135,140,159,165,169,189,193,220,225,234,246,251,254],"continuous":[2],"increase":[3],"of":[4,38,80,129,161,191,224,237,253],"renewable":[5,24],"energy":[6],"integration":[7],"into":[8],"power":[10,29,56],"grid,":[11],"cyber-physical":[12,55],"systems":[13,57],"play":[14],"an":[15,200],"increasingly":[16],"significant":[17],"role":[18],"in":[19,54,63],"smart":[21],"grid.":[22],"Most":[23],"energies":[25],"connect":[26],"to":[27,88,157,179,182,199,205,218,259],"system":[30],"with":[31],"grid-connected":[32],"converters":[33],"(GCCs).":[34],"However,":[35],"control":[37],"GCCs":[40],"unavoidably":[41],"relied":[42],"on":[43,50,75,108,117,139,146,211,230],"communication-based":[45],"signal,":[46],"which":[47,175,256],"increases":[48],"pressure":[49],"data":[51,82,98,232],"interaction":[52],"security":[53],"(CPPS).":[58],"To":[59,187],"address":[60],"this":[61,64],"issue,":[62],"paper,":[65],"a":[66,143],"novel":[67],"importance":[68,201],"index":[69,202],"and":[70,78,112,132,150,203,222],"its":[71],"defining":[72,96,141],"method":[73,115,248],"based":[74,107,116,145,229],"F1-score":[77],"probability":[79],"false":[81],"injection":[83],"attacks":[84],"(FDIAs)":[85],"are":[86,239,257],"proposed":[87,95,156,226,247],"filter":[89],"sensitive":[91,194],"feature.":[92],"In":[93,216],"method,":[97,142,227],"preprocessing":[99],"is":[100,155,171,196],"achieved":[101],"by":[102,173,209],"local":[103],"outlier":[104],"factor":[105],"(LOF)":[106],"k-maxmin":[109],"clustering":[110],"algorithm":[111],"imputation":[114],"random":[118],"forest":[119],"(RF).":[120],"The":[121,241],"principle":[122],"component":[123],"analysis":[124],"(PCA)":[125],"reduces":[126],"dimensionality":[128],"multi-dimensional":[130],"features":[131,178],"further":[133],"filters":[134],"redundant":[136],"information.":[137],"Based":[138],"methodology":[144],"convolutional":[147],"neural":[148],"networks":[149],"support":[151],"vector":[152],"machine":[153],"(CNN-SVM)":[154],"detect":[158],"types":[160,190],"cyberattacks.":[162,260],"Different":[163],"from":[164,233],"traditional":[166],"CNN":[167],"classifier,":[168],"softmax":[170],"replaced":[172],"SVM,":[174],"maps":[176],"various":[177],"different":[180],"hyperplanes":[181],"achieve":[183],"more":[184],"accurate":[185],"classification.":[186],"analyze":[188],"features,":[192],"feature":[195,214],"defined":[197],"according":[198],"used":[204],"strengthen":[206],"cyber":[207],"defenses":[208],"focusing":[210],"monitoring":[212],"such":[213],"data.":[215],"order":[217],"verify":[219],"effectiveness":[221],"feasibility":[223],"experiments":[228],"real":[231],"eastern":[235],"province":[236],"China":[238],"adopted.":[240],"experiment":[242],"results":[243],"indicate":[244],"that":[245],"could":[249],"find":[250],"weaknesses":[252],"dataset,":[255],"immunity":[258]},"counts_by_year":[{"year":2024,"cited_by_count":1}],"updated_date":"2026-05-05T08:41:31.759640","created_date":"2025-10-10T00:00:00"}
