{"id":"https://openalex.org/W4396563574","doi":"https://doi.org/10.54216/fpa.160105","title":"Fusing Deep Learning Techniques for Intrusion Detection in Smart Grids","display_name":"Fusing Deep Learning Techniques for Intrusion Detection in Smart Grids","publication_year":2024,"publication_date":"2024-01-01","ids":{"openalex":"https://openalex.org/W4396563574","doi":"https://doi.org/10.54216/fpa.160105"},"language":"en","primary_location":{"id":"doi:10.54216/fpa.160105","doi":"https://doi.org/10.54216/fpa.160105","is_oa":false,"landing_page_url":"https://doi.org/10.54216/fpa.160105","pdf_url":null,"source":{"id":"https://openalex.org/S4210171581","display_name":"Fusion Practice and Applications","issn_l":"2692-4048","issn":["2692-4048","2770-0070"],"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":["norway-1"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Fusion: Practice and Applications","raw_type":"journal-article"},"volume":null,"type":"article","is_traditional":true,"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/A5071486253","display_name":"R. R.","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"R. R.","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055942511","display_name":"Pusarla Sindhu","orcid":"https://orcid.org/0000-0003-2489-796X","observed_orcids":["https://orcid.org/0000-0003-2489-796X"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sindhu. P.","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113955744","display_name":"Gnanadesigan Naveen Sundar","orcid":"https://orcid.org/0000-0002-4638-7867","observed_orcids":["https://orcid.org/0000-0002-4638-7867"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"G. Naveen Sundar","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":null,"display_name":"R. Venkatesan","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"R. Venkatesan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.7285,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.62230546,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":97},"biblio":{"volume":"16","issue":"1","first_page":"67","last_page":"76"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10917","display_name":"Smart Grid Security and Resilience","score":0.7875999808311462,"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":0.7875999808311462,"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":0.2045000046491623,"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/T13038","display_name":"Internet of Things and AI","score":0.0005000000237487257,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/intrusion-detection","display_name":"intrusion detection","score":0.9739999771118164},{"id":"https://openalex.org/keywords/smart-grid-cybersecurity","display_name":"smart grid cybersecurity","score":0.7549999952316284},{"id":"https://openalex.org/keywords/hybrid-deep-learning","display_name":"hybrid deep learning model","score":0.8180000185966492},{"id":"https://openalex.org/keywords/1d-convolution","display_name":"one-dimensional convolution","score":0.746999979019165},{"id":"https://openalex.org/keywords/gru","display_name":"GRU","score":0.8109999895095825},{"id":"https://openalex.org/keywords/iot-devices","display_name":"IoT devices","score":0.5509999990463257},{"id":"https://openalex.org/keywords/attack-classification","display_name":"attack classification","score":0.7009999752044678},{"id":"https://openalex.org/keywords/critical-infrastructure-security","display_name":"critical infrastructure security","score":0.8050000071525574},{"id":"https://openalex.org/keywords/temporal-dependencies","display_name":"temporal dependencies","score":0.5170000195503235}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7795671224594116},{"id":"https://openalex.org/C35525427","wikidata":"https://www.wikidata.org/wiki/Q745881","display_name":"Intrusion detection system","level":2,"score":0.7192673087120056},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6240018010139465},{"id":"https://openalex.org/C10558101","wikidata":"https://www.wikidata.org/wiki/Q689855","display_name":"Smart grid","level":2,"score":0.6160770058631897},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.550832211971283},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.4910002052783966},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.484264075756073},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4281918406486511},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.3668351471424103},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.15053260326385498},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"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:10.54216/fpa.160105","doi":"https://doi.org/10.54216/fpa.160105","is_oa":false,"landing_page_url":"https://doi.org/10.54216/fpa.160105","pdf_url":null,"source":{"id":"https://openalex.org/S4210171581","display_name":"Fusion Practice and Applications","issn_l":"2692-4048","issn":["2692-4048","2770-0070"],"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":["norway-1"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Fusion: Practice and Applications","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9","score":0.8970999717712402},{"display_name":"Affordable and clean energy","id":"https://metadata.un.org/sdg/7","score":0.75}],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4416065296","https://openalex.org/W4405085404","https://openalex.org/W7166528406","https://openalex.org/W7160855853","https://openalex.org/W6892698897","https://openalex.org/W4399714656","https://openalex.org/W4386223270","https://openalex.org/W7111083929","https://openalex.org/W7163153991","https://openalex.org/W7212005572"],"abstract_inverted_index":{"Smart":[0,48],"grids,":[1],"pivotal":[2],"in":[3,136,153],"modern":[4],"energy":[5],"distribution,":[6],"confront":[7],"a":[8,21,51,93,169,175,181],"mounting":[9],"cybersecurity":[10,190],"threat":[11],"landscape":[12],"due":[13],"to":[14,35,110,146],"their":[15],"increased":[16],"connectivity.":[17],"This":[18,141],"study":[19,57],"introduces":[20],"novel":[22],"hybrid":[23,122,170],"deep":[24,171],"learning":[25,172],"approach":[26,173],"designed":[27],"for":[28,47,60,65,70,161],"robust":[29],"intrusion":[30,97,139,151],"detection,":[31],"addressing":[32,137],"the":[33,37,56,77,111,115,128,147,159],"imperative":[34],"fortify":[36],"security":[38,164,178],"of":[39,85,96,102,130,150,168],"these":[40],"critical":[41],"infrastructures.":[42],"Renamed":[43],"as":[44],"Intrusion":[45],"Detection":[46],"Grid":[49],"Using":[50],"Hybrid":[52],"Deep":[53],"Learning":[54],"Approach,":[55],"amalgamates":[58],"Conv1D":[59],"spatial":[61],"feature":[62],"extraction,":[63],"MaxPooling1D":[64],"dimensionality":[66],"reduction,":[67],"and":[68,91,105,118,132],"GRU":[69],"modeling":[71],"temporal":[72],"dependencies.":[73],"The":[74,120,166,192],"research":[75,142],"leverages":[76],"Edge-IIoTset":[78],"Cyber":[79],"Security":[80],"Dataset,":[81],"encompassing":[82],"diverse":[83],"layers":[84],"emerging":[86],"technologies":[87],"within":[88],"smart":[89,154,186],"grids":[90,155,187],"facilitating":[92],"nuanced":[94],"understanding":[95],"patterns.":[98],"Over":[99],"10":[100],"types":[101],"IoT":[103],"devices":[104],"14":[106],"attack":[107],"categories":[108],"contribute":[109],"dataset's":[112],"richness,":[113],"enhancing":[114],"model's":[116,123],"training":[117],"evaluation.":[119],"proposed":[121,193],"architecture":[124],"is":[125],"detailed,":[126],"emphasizing":[127],"synergy":[129],"convolutional":[131],"recurrent":[133],"neural":[134],"networks":[135],"complex":[138],"scenarios.":[140],"not":[143],"only":[144],"contributes":[145],"evolving":[148,189],"field":[149],"detection":[152],"but":[156],"also":[157],"sets":[158],"stage":[160],"creating":[162],"adaptive":[163],"systems.":[165],"convergence":[167],"with":[174],"comprehensive":[176],"cyber":[177],"dataset":[179],"marks":[180],"significant":[182],"stride":[183],"towards":[184],"fortifying":[185],"against":[188],"threats.":[191],"model":[194],"achieves":[195],"98.20":[196],"percentage.":[197]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":3}],"updated_date":"2026-11-07T11:25:07.637180","created_date":"2024-05-02T00:00:00"}
