{"id":"https://openalex.org/W7225440672","doi":null,"title":"A Hybrid Transformer-BiLSTM Framework with Metaheuristic Feature Optimization for Anomaly Detection in Industrial IoT Networks","display_name":"A Hybrid Transformer-BiLSTM Framework with Metaheuristic Feature Optimization for Anomaly Detection in Industrial IoT Networks","publication_year":2026,"publication_date":"2026-10-03","ids":{"openalex":"https://openalex.org/W7225440672"},"language":"en","primary_location":{"id":"pmh:oai:ojs2.journalmta.com:article/516","doi":null,"is_oa":true,"landing_page_url":"https://journalmta.com/index.php/jmta/article/view/516","pdf_url":"https://journalmta.com/index.php/jmta/article/download/516/406","source":{"id":"https://openalex.org/S7407065557","display_name":"Minimax Theory and its Applications","issn_l":"2199-1421","issn":["2199-1421","2199-1413"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":["dongbi-c","norway-1","poland-70","russia-white-list-3"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2199-1413","raw_type":"info:eu-repo/semantics/article"},"volume":null,"type":"article","is_traditional":true,"indexed_in":[],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://journalmta.com/index.php/jmta/article/download/516/406","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5161107746","display_name":"S. Kokila","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kokila, S.","raw_affiliation_strings":["Research Scholar , Department of Electronics and Communication Engineering , M.A.M.School of Engineering , Tiruchirappalli , India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Research Scholar , Department of Electronics and Communication Engineering , M.A.M.School of Engineering , Tiruchirappalli , India","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5161092057","display_name":"Dr.M. Anand","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Anand, Dr.M.","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5161001564","display_name":"Dr.B. Raja","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Raja, Dr.B.","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5160999957","display_name":"Dr.G.Thiraviya Suyambu","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Suyambu, Dr.G.Thiraviya","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5161069379","display_name":"Dr.F. Jerald","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jerald, Dr.F.","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":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.0,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10400","display_name":"Network Security and Intrusion Detection","score":0.9970999956130981,"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"}},"topics":[{"id":"https://openalex.org/T10400","display_name":"Network Security and Intrusion Detection","score":0.9970999956130981,"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/T11598","display_name":"Internet Traffic Analysis and Secure E-voting","score":0.0005000000237487257,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T12391","display_name":"Artificial Immune Systems Applications","score":0.0003000000142492354,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/industrial-iot-security","display_name":"industrial IoT security","score":0.6000000238418579},{"id":"https://openalex.org/keywords/network-anomaly-detection","display_name":"network anomaly detection","score":0.7039999961853027},{"id":"https://openalex.org/keywords/cyberattack-classification","display_name":"cyberattack classification","score":0.7120000123977661},{"id":"https://openalex.org/keywords/grey-wolf-optimizer","display_name":"grey wolf optimizer","score":0.6520000100135803},{"id":"https://openalex.org/keywords/cuckoo-search-algorithm","display_name":"cuckoo search algorithm","score":0.9779999852180481},{"id":"https://openalex.org/keywords/metaheuristic-feature-selection","display_name":"metaheuristic feature selection","score":0.8700000047683716},{"id":"https://openalex.org/keywords/feature-reduction","display_name":"feature reduction","score":0.6610000133514404},{"id":"https://openalex.org/keywords/class-imbalance","display_name":"class imbalance","score":0.9789999723434448},{"id":"https://openalex.org/keywords/cross-dataset-generalization","display_name":"cross-dataset generalization","score":0.9399999976158142},{"id":"https://openalex.org/keywords/cross-entropy-loss","display_name":"cross-entropy loss","score":0.47099998593330383}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6854000091552734},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5572999715805054},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.5354999899864197},{"id":"https://openalex.org/C106301342","wikidata":"https://www.wikidata.org/wiki/Q4117933","display_name":"Entropy (arrow of time)","level":2,"score":0.522599995136261},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.48350000381469727},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.47999998927116394},{"id":"https://openalex.org/C81860439","wikidata":"https://www.wikidata.org/wiki/Q251212","display_name":"Internet of Things","level":2,"score":0.4781999886035919},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.45989999175071716},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.45680001378059387},{"id":"https://openalex.org/C109718341","wikidata":"https://www.wikidata.org/wiki/Q1385229","display_name":"Metaheuristic","level":2,"score":0.4546999931335449},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.3695000112056732},{"id":"https://openalex.org/C35525427","wikidata":"https://www.wikidata.org/wiki/Q745881","display_name":"Intrusion detection system","level":2,"score":0.3564999997615814},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.3531000018119812},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.35249999165534973},{"id":"https://openalex.org/C2780741293","wikidata":"https://www.wikidata.org/wiki/Q4818019","display_name":"Attack patterns","level":3,"score":0.33219999074935913},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.32919999957084656},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.32420000433921814},{"id":"https://openalex.org/C152745839","wikidata":"https://www.wikidata.org/wiki/Q5438153","display_name":"Fault detection and isolation","level":3,"score":0.3190000057220459},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.29789999127388},{"id":"https://openalex.org/C182590292","wikidata":"https://www.wikidata.org/wiki/Q989632","display_name":"Network security","level":2,"score":0.27309998869895935},{"id":"https://openalex.org/C167981619","wikidata":"https://www.wikidata.org/wiki/Q1685498","display_name":"Cross entropy","level":3,"score":0.26019999384880066}],"mesh":[],"locations_count":1,"locations":[{"id":"pmh:oai:ojs2.journalmta.com:article/516","doi":null,"is_oa":true,"landing_page_url":"https://journalmta.com/index.php/jmta/article/view/516","pdf_url":"https://journalmta.com/index.php/jmta/article/download/516/406","source":{"id":"https://openalex.org/S7407065557","display_name":"Minimax Theory and its Applications","issn_l":"2199-1421","issn":["2199-1421","2199-1413"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":["dongbi-c","norway-1","poland-70","russia-white-list-3"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2199-1413","raw_type":"info:eu-repo/semantics/article"}],"best_oa_location":{"id":"pmh:oai:ojs2.journalmta.com:article/516","doi":null,"is_oa":true,"landing_page_url":"https://journalmta.com/index.php/jmta/article/view/516","pdf_url":"https://journalmta.com/index.php/jmta/article/download/516/406","source":{"id":"https://openalex.org/S7407065557","display_name":"Minimax Theory and its Applications","issn_l":"2199-1421","issn":["2199-1421","2199-1413"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":["dongbi-c","norway-1","poland-70","russia-white-list-3"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2199-1413","raw_type":"info:eu-repo/semantics/article"},"sustainable_development_goals":[{"score":0.5378999710083008,"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure"}],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7225440672.pdf","grobid_xml":"https://content.openalex.org/works/W7225440672.grobid-xml"},"referenced_works_count":23,"referenced_works":["https://openalex.org/W2017337590","https://openalex.org/W2038194220","https://openalex.org/W2064675550","https://openalex.org/W2112796928","https://openalex.org/W2122111042","https://openalex.org/W2148143831","https://openalex.org/W2320204756","https://openalex.org/W2911964244","https://openalex.org/W2919115771","https://openalex.org/W2958285686","https://openalex.org/W2959428502","https://openalex.org/W2999309192","https://openalex.org/W3009422166","https://openalex.org/W3194730353","https://openalex.org/W4226319939","https://openalex.org/W4239510810","https://openalex.org/W4252684946","https://openalex.org/W4294691681","https://openalex.org/W4309836412","https://openalex.org/W4313654696","https://openalex.org/W4410991886","https://openalex.org/W4411450060","https://openalex.org/W7128736771"],"related_works":["https://openalex.org/W4312597218","https://openalex.org/W7202366531","https://openalex.org/W7081934024","https://openalex.org/W7118194948","https://openalex.org/W4408563962","https://openalex.org/W7128736771","https://openalex.org/W7103902443","https://openalex.org/W4319430764","https://openalex.org/W7172249776","https://openalex.org/W4396609033"],"abstract_inverted_index":{"Industrial":[0],"Internet":[1],"of":[2,110,170,173,196],"Things":[3],"(IIoT)":[4],"networks":[5,21,38],"are":[6,22,70,83,127,194],"primary":[7],"constituents":[8],"in":[9,67,85,138],"several":[10],"industries":[11],"such":[12,43,149],"as":[13,150],"Manufacturing,":[14],"Energy,":[15],"Transportation":[16],"and":[17,64,105,117,129,144,180,184],"Process":[18],"Control.":[19],"These":[20,81],"targeted":[23],"by":[24,40,89],"cyber":[25],"attacks,":[26],"which":[27,59,123],"cause":[28],"internal":[29],"security":[30],"lapses":[31],"to":[32,49,51,55,61,77,162,186],"the":[33,36,125,131,164],"country.":[34],"Traditionally,":[35],"IIoT":[37],"suffered":[39],"three":[41],"limitations":[42],"as,":[44],"inadequate":[45],"feature":[46,93,168],"selection,":[47],"failure":[48],"adapt":[50],"traffic":[52],"dependencies,":[53],"inability":[54],"distinguish":[56,187],"attack":[57,72,111,174],"classes":[58,112,175],"appears":[60],"be":[62],"closer":[63],"identical":[65],"but":[66],"reality":[68],"they":[69],"different":[71],"classes,":[73],"could":[74],"not":[75],"able":[76],"address":[78],"class":[79,132],"imbalance.":[80,133],"bottlenecks":[82],"addressed":[84],"this":[86,139,197],"research":[87,140],"work":[88],"proposing":[90],"(i)":[91],"hybrid":[92],"optimizer(Hybrid":[94],"Grey":[95],"Snake\u2014Cuckoo":[96],"Search":[97],"(HGS-CS)":[98],"metaheuristic":[99],"optimizer),":[100],"(ii).":[101],"Combined":[102],"Multi":[103,119],"Transformer":[104],"LSTM":[106],"approach":[107],"for":[108],"detection":[109],"with":[113,176,190],"much":[114],"better":[115],"accuracy":[116,179],"(iii)":[118],"Dataset,":[120],"cross":[121,181],"entropy":[122],"enables":[124],"migrations":[126],"easier":[128],"reduces":[130],"Three":[134],"datasets":[135],"were":[136,160],"used":[137,161],"are,":[141],"X-IIoTID,":[142],"Edge-IIoTset,":[143],"WUSTL-IIoT-2021.":[145],"Multiple":[146],"performance":[147],"parameters":[148],"F1":[151],"Score,":[152],"Accuracy,":[153],"AUC-ROC,":[154],"Matthews":[155],"Correlation":[156],"Coefficient":[157],"(MCC)":[158],"etc.,":[159],"test":[163],"proposed":[165],"system.":[166],"The":[167],"reduction":[169],"54.2%,":[171],"Detection":[172],"near":[177],"perfect":[178],"dataset":[182],"generalization":[183],"ability":[185],"multiple":[188],"attacks":[189],"good":[191],"t-SNE":[192],"scores":[193],"contributions":[195],"research.":[198]},"counts_by_year":[],"updated_date":"2026-11-08T12:12:28.789561","created_date":"2026-11-07T00:00:00"}