{"id":"https://openalex.org/W7135067554","doi":"https://doi.org/10.1016/j.iotcps.2026.03.002","title":"AOA-SMA-EGRUAttNet: A hybrid feature selection and dual-stream attention-based intrusion detection framework for IIoT systems","display_name":"AOA-SMA-EGRUAttNet: A hybrid feature selection and dual-stream attention-based intrusion detection framework for IIoT systems","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W7135067554","doi":"https://doi.org/10.1016/j.iotcps.2026.03.002"},"language":"en","primary_location":{"id":"doi:10.1016/j.iotcps.2026.03.002","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.iotcps.2026.03.002","pdf_url":null,"source":{"id":"https://openalex.org/S4210180977","display_name":"Internet of Things and Cyber-Physical Systems","issn_l":"2667-3452","issn":["2667-3452"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Internet of Things and Cyber-Physical Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://doi.org/10.1016/j.iotcps.2026.03.002","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5062565743","display_name":"Yousef Sanjalawe","orcid":"https://orcid.org/0000-0002-4442-1865"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yousef Sanjalawe","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0002-4442-1865","affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004065267","display_name":"F.M.A. Salam","orcid":"https://orcid.org/0000-0002-1025-7868"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Salam Fraihat","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0002-1025-7868","affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Salam Al-E'mari","orcid":"https://orcid.org/0000-0002-2134-4158"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Salam Al-E'mari","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0002-2134-4158","affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5024473397","display_name":"Sharif Naser Makhadmeh","orcid":"https://orcid.org/0000-0002-2894-7998"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sharif Naser Makhadmeh","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.70710444,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"5","issue":null,"first_page":"143","last_page":"164"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10400","display_name":"Network Security and Intrusion Detection","score":0.6970000267028809,"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":0.6970000267028809,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.09700000286102295,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.013399999588727951,"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/feature-selection","display_name":"Feature selection","score":0.6072999835014343},{"id":"https://openalex.org/keywords/intrusion-detection-system","display_name":"Intrusion detection system","score":0.545799970626831},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.49869999289512634},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.46129998564720154},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3522999882698059}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6251999735832214},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.6072999835014343},{"id":"https://openalex.org/C35525427","wikidata":"https://www.wikidata.org/wiki/Q745881","display_name":"Intrusion detection system","level":2,"score":0.545799970626831},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.49869999289512634},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.49079999327659607},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.46129998564720154},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4350000023841858},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3522999882698059},{"id":"https://openalex.org/C137524506","wikidata":"https://www.wikidata.org/wiki/Q2247688","display_name":"Anomaly-based intrusion detection system","level":3,"score":0.32429999113082886},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.2987000048160553},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.29249998927116394},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.2727000117301941}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1016/j.iotcps.2026.03.002","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.iotcps.2026.03.002","pdf_url":null,"source":{"id":"https://openalex.org/S4210180977","display_name":"Internet of Things and Cyber-Physical Systems","issn_l":"2667-3452","issn":["2667-3452"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Internet of Things and Cyber-Physical Systems","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:8f75c21b10aa4ea5aff18a90fe0e6057","is_oa":true,"landing_page_url":"https://doaj.org/article/8f75c21b10aa4ea5aff18a90fe0e6057","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Internet of Things and Cyber-Physical Systems, Vol 5, Iss , Pp 143-164 (2025)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1016/j.iotcps.2026.03.002","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.iotcps.2026.03.002","pdf_url":null,"source":{"id":"https://openalex.org/S4210180977","display_name":"Internet of Things and Cyber-Physical Systems","issn_l":"2667-3452","issn":["2667-3452"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Internet of Things and Cyber-Physical Systems","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.4130585491657257,"id":"https://metadata.un.org/sdg/13","display_name":"Climate action"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":35,"referenced_works":["https://openalex.org/W2940895343","https://openalex.org/W2980185226","https://openalex.org/W2995370638","https://openalex.org/W3014974411","https://openalex.org/W3090396243","https://openalex.org/W3157768705","https://openalex.org/W3158451290","https://openalex.org/W3191884578","https://openalex.org/W3194959494","https://openalex.org/W3202603325","https://openalex.org/W4206931805","https://openalex.org/W4212879646","https://openalex.org/W4220818970","https://openalex.org/W4226319939","https://openalex.org/W4311632513","https://openalex.org/W4315783030","https://openalex.org/W4366133297","https://openalex.org/W4379209010","https://openalex.org/W4379620056","https://openalex.org/W4381952972","https://openalex.org/W4385636702","https://openalex.org/W4386608804","https://openalex.org/W4388638017","https://openalex.org/W4393115034","https://openalex.org/W4394685829","https://openalex.org/W4396656153","https://openalex.org/W4400574640","https://openalex.org/W4403209235","https://openalex.org/W4403678775","https://openalex.org/W4407597636","https://openalex.org/W4407937271","https://openalex.org/W4408546398","https://openalex.org/W4408733119","https://openalex.org/W4409205049","https://openalex.org/W4410362691"],"related_works":[],"abstract_inverted_index":{"The":[0,85,108],"rapid":[1],"expansion":[2],"of":[3,7,97,202,219],"the":[4,37,91,111,140,171,198,216],"Industrial":[5],"Internet":[6],"Things":[8],"(IIoT)":[9],"has":[10],"introduced":[11],"unprecedented":[12],"opportunities":[13],"for":[14,121,226],"smart":[15],"industrial":[16,220],"automation.":[17],"Yet,":[18],"it":[19],"also":[20],"exposes":[21],"critical":[22,232],"systems":[23,230],"to":[24,48,79,89,181],"various":[25],"sophisticated":[26],"cyber":[27],"threats.":[28],"Traditional":[29],"Intrusion":[30],"Detection":[31],"Systems":[32],"(IDS)":[33],"often":[34],"struggle":[35],"with":[36],"complexity,":[38],"heterogeneity,":[39],"and":[40,53,75,83,94,104,116,132,153,167,183,194,200,210],"class":[41],"imbalance":[42],"inherent":[43],"in":[44,178,231],"IIoT":[45,162],"environments,":[46],"leading":[47],"high":[49],"false":[50],"alarm":[51],"rates":[52],"suboptimal":[54],"generalization.":[55],"This":[56,205],"paper":[57,206],"addresses":[58],"these":[59],"limitations":[60],"by":[61],"proposing":[62],"a":[63,145,208,223],"novel":[64],"hybrid":[65,122],"intrusion":[66],"detection":[67,81,229],"framework,":[68],"AOA-SMA-EGRUAttNet,":[69],"that":[70,170,214],"unites":[71],"advanced":[72],"feature":[73,123,190],"selection":[74],"dual-stream":[76,147],"deep":[77],"learning":[78],"enhance":[80],"accuracy":[82,179],"interpretability.":[84],"core":[86],"motivation":[87],"is":[88],"improve":[90],"computational":[92],"efficiency":[93],"classification":[95,129],"robustness":[96,201],"IDS":[98,212],"models":[99],"through":[100],"targeted":[101],"dimensionality":[102],"reduction":[103],"context-aware":[105],"temporal":[106],"learning.":[107],"framework":[109],"integrates":[110],"Archimedes":[112],"Optimization":[113],"Algorithm":[114,119],"(AOA)":[115],"Slime":[117],"Mould":[118],"(SMA)":[120],"selection,":[124],"optimizing":[125],"subsets":[126],"based":[127],"on":[128],"relevance,":[130],"redundancy,":[131],"processing":[133],"cost.":[134],"Selected":[135],"features":[136],"are":[137],"fed":[138],"into":[139],"Enhanced":[141],"GRU-Attention":[142],"Network":[143],"(E-GRUAttNet),":[144],"lightweight":[146],"model":[148],"combining":[149],"gated":[150],"recurrent":[151],"units":[152],"parallel":[154],"attention":[155],"mechanisms.":[156],"Experimental":[157],"evaluation":[158],"across":[159],"four":[160],"benchmark":[161],"datasets:":[163],"CICAPT-IIoT,":[164],"Edge-IIoTset,":[165],"X-IIoTID,":[166],"WUSTL-IIoT-2021,":[168],"demonstrates":[169],"proposed":[172],"method":[173],"consistently":[174],"outperforms":[175],"state-of-the-art":[176],"baselines":[177],"(up":[180],"98.9%)":[182],"macro-F1":[184],"score,":[185],"while":[186],"achieving":[187],"over":[188],"55%":[189],"reduction.":[191],"Ablation":[192],"studies":[193],"statistical":[195],"analyses":[196],"confirm":[197],"significance":[199],"each":[203],"component.":[204],"contributes":[207],"scalable":[209],"interpretable":[211],"architecture":[213],"meets":[215],"evolving":[217],"demands":[218],"cybersecurity,":[221],"providing":[222],"strong":[224],"foundation":[225],"future":[227],"adaptive":[228],"infrastructures.":[233]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-03-13T00:00:00"}