{"id":"https://openalex.org/W7128828431","doi":"https://doi.org/10.1109/jiot.2026.3664373","title":"X-IoMT: A Cross-Layer IoMT Dataset for Anomaly Detection With FGSM- and PGD-Based Adversarial Augmentation","display_name":"X-IoMT: A Cross-Layer IoMT Dataset for Anomaly Detection With FGSM- and PGD-Based Adversarial Augmentation","publication_year":2026,"publication_date":"2026-02-13","ids":{"openalex":"https://openalex.org/W7128828431","doi":"https://doi.org/10.1109/jiot.2026.3664373"},"language":null,"primary_location":{"id":"doi:10.1109/jiot.2026.3664373","is_oa":true,"landing_page_url":"https://doi.org/10.1109/jiot.2026.3664373","pdf_url":null,"source":{"id":"https://openalex.org/S2480266640","display_name":"IEEE Internet of Things Journal","issn_l":"2327-4662","issn":["2327-4662","2372-2541"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Internet of Things Journal","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://doi.org/10.1109/jiot.2026.3664373","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5125932572","display_name":"Rui P. O. Pinto","orcid":null},"institutions":[{"id":"https://openalex.org/I161321875","display_name":"University of Beira Interior","ror":"https://ror.org/03nf36p02","country_code":"PT","type":"education","lineage":["https://openalex.org/I161321875"]}],"countries":["PT"],"is_corresponding":false,"raw_author_name":"Rui P. O. Pinto","raw_affiliation_strings":["Department of Computer Science, Instituto de Telecomunicações, Universidade da Beira Interior, Covilhã, Portugal"],"raw_orcid":"https://orcid.org/0000-0003-1069-7262","affiliations":[{"raw_affiliation_string":"Department of Computer Science, Instituto de Telecomunicações, Universidade da Beira Interior, Covilhã, Portugal","institution_ids":["https://openalex.org/I161321875"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055050505","display_name":"Bruno M. C. Silva","orcid":"https://orcid.org/0000-0002-5939-8370"},"institutions":[{"id":"https://openalex.org/I161321875","display_name":"University of Beira Interior","ror":"https://ror.org/03nf36p02","country_code":"PT","type":"education","lineage":["https://openalex.org/I161321875"]}],"countries":["PT"],"is_corresponding":false,"raw_author_name":"Bruno M. C. Silva","raw_affiliation_strings":["Department of Computer Science, Instituto de Telecomunicações, Universidade da Beira Interior, Covilhã, Portugal"],"raw_orcid":"https://orcid.org/0000-0002-5939-8370","affiliations":[{"raw_affiliation_string":"Department of Computer Science, Instituto de Telecomunicações, Universidade da Beira Interior, Covilhã, Portugal","institution_ids":["https://openalex.org/I161321875"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5125929752","display_name":"Pedro R. M. In\u00e1cio","orcid":null},"institutions":[{"id":"https://openalex.org/I161321875","display_name":"University of Beira Interior","ror":"https://ror.org/03nf36p02","country_code":"PT","type":"education","lineage":["https://openalex.org/I161321875"]}],"countries":["PT"],"is_corresponding":false,"raw_author_name":"Pedro R. M. In\u00e1cio","raw_affiliation_strings":["Department of Computer Science, Instituto de Telecomunicações, Universidade da Beira Interior, Covilhã, Portugal"],"raw_orcid":"https://orcid.org/0000-0001-8221-0666","affiliations":[{"raw_affiliation_string":"Department of Computer Science, Instituto de Telecomunicações, Universidade da Beira Interior, Covilhã, Portugal","institution_ids":["https://openalex.org/I161321875"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I161321875"],"apc_list":null,"apc_paid":null,"fwci":10.1155,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.96357079,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":"13","issue":"10","first_page":"20797","last_page":"20810"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.6071000099182129,"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"}},"topics":[{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.6071000099182129,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.14579999446868896,"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/T10400","display_name":"Network Security and Intrusion Detection","score":0.050999999046325684,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.7760000228881836},{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.754800021648407},{"id":"https://openalex.org/keywords/benchmarking","display_name":"Benchmarking","score":0.6204000115394592},{"id":"https://openalex.org/keywords/the-internet","display_name":"The Internet","score":0.569100022315979},{"id":"https://openalex.org/keywords/anomaly","display_name":"Anomaly (physics)","score":0.48330000042915344},{"id":"https://openalex.org/keywords/resilience","display_name":"Resilience (materials science)","score":0.46129998564720154}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8348000049591064},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.7760000228881836},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.754800021648407},{"id":"https://openalex.org/C86251818","wikidata":"https://www.wikidata.org/wiki/Q816754","display_name":"Benchmarking","level":2,"score":0.6204000115394592},{"id":"https://openalex.org/C110875604","wikidata":"https://www.wikidata.org/wiki/Q75","display_name":"The Internet","level":2,"score":0.569100022315979},{"id":"https://openalex.org/C12997251","wikidata":"https://www.wikidata.org/wiki/Q567560","display_name":"Anomaly (physics)","level":2,"score":0.48330000042915344},{"id":"https://openalex.org/C2779585090","wikidata":"https://www.wikidata.org/wiki/Q3457762","display_name":"Resilience (materials science)","level":2,"score":0.46129998564720154},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4487999975681305},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4438999891281128},{"id":"https://openalex.org/C35525427","wikidata":"https://www.wikidata.org/wiki/Q745881","display_name":"Intrusion detection system","level":2,"score":0.4097000062465668},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.37310001254081726},{"id":"https://openalex.org/C153258448","wikidata":"https://www.wikidata.org/wiki/Q1199743","display_name":"Gradient descent","level":3,"score":0.30570000410079956},{"id":"https://openalex.org/C2778403875","wikidata":"https://www.wikidata.org/wiki/Q20312394","display_name":"Adversarial machine learning","level":3,"score":0.287200003862381},{"id":"https://openalex.org/C182590292","wikidata":"https://www.wikidata.org/wiki/Q989632","display_name":"Network security","level":2,"score":0.27489998936653137},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.2694000005722046},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.2689000070095062},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.26840001344680786}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/jiot.2026.3664373","is_oa":true,"landing_page_url":"https://doi.org/10.1109/jiot.2026.3664373","pdf_url":null,"source":{"id":"https://openalex.org/S2480266640","display_name":"IEEE Internet of Things Journal","issn_l":"2327-4662","issn":["2327-4662","2372-2541"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Internet of Things Journal","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1109/jiot.2026.3664373","is_oa":true,"landing_page_url":"https://doi.org/10.1109/jiot.2026.3664373","pdf_url":null,"source":{"id":"https://openalex.org/S2480266640","display_name":"IEEE Internet of Things Journal","issn_l":"2327-4662","issn":["2327-4662","2372-2541"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Internet of Things Journal","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"With":[0],"the":[1,5,40,81,90,96,102,178,181,187],"growing":[2],"adoption":[3],"of":[4,7,26,83,92,180,189],"Internet":[6,91],"Medical":[8],"Things":[9,93],"(IoMT),":[10],"concerns":[11],"around":[12],"security,":[13],"reliability,":[14],"and":[15,105,119,127,141,157,170,192],"anomaly":[16,28,84,160],"detection":[17,29,85,136,161],"across":[18],"heterogeneous":[19],"system":[20],"layers":[21],"are":[22,47],"increasing.":[23],"The":[24],"essence":[25],"contemporary":[27],"lies":[30],"in":[31,86,163],"Machine":[32],"Learning":[33],"(ML),":[34],"training":[35],"models":[36,162],"on":[37,135,142],"datasets":[38,46],"for":[39,155],"desired":[41],"functionality.":[42],"Nonetheless,":[43],"currently":[44],"available":[45,76],"mostly":[48],"insufficiently":[49],"supported":[50],"with":[51,130,166,177],"multi-layer":[52],"analysis,":[53],"as":[54],"they":[55],"usually":[56],"target":[57],"a":[58,63,74],"single":[59],"architectural":[60],"layer":[61],"or":[62],"narrow":[64],"attack":[65,168],"type.":[66],"To":[67],"close":[68],"this":[69],"gap,":[70],"we":[71],"offer":[72],"X-IoMT,":[73],"publicly":[75],"dataset":[77],"designed":[78],"to":[79,185],"enable":[80],"research":[82],"IoMT":[87,164,194],"environments.":[88],"In":[89],"(IoT)":[94],"architecture,":[95],"X-IoMT":[97,149],"data":[98],"embodies":[99],"anomalies":[100],"from":[101],"perception,":[103],"network,":[104],"application":[106],"layers.":[107],"Besides,":[108],"it":[109],"incorporates":[110],"adversarial":[111,132,172],"perturbations":[112],"by":[113],"Fast":[114],"Gradient":[115,121],"Sign":[116],"Method":[117],"(FGSM)":[118],"Projected":[120],"Descent":[122],"(PGD)":[123],"under":[124,138],"both":[125,134],"L2":[126],"L\u221e":[128],"norms":[129],"extra":[131,171],"augmentation:":[133],"performance":[137],"common":[139],"attacks":[140],"resilience":[143],"against":[144],"adversarially":[145],"manipulated":[146],"samples.":[147],"Thus,":[148],"could":[150],"be":[151],"an":[152],"important":[153],"tool":[154],"evaluating":[156],"benchmarking":[158],"reliable":[159,191],"scenarios":[165],"cross-layer":[167],"coverage":[169],"augmentation.":[173],"This":[174],"paper":[175],"contributes":[176],"presentation":[179],"dataset,":[182],"inherently":[183],"aiming":[184],"support":[186],"advancement":[188],"more":[190],"secure":[193],"systems.":[195]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-07-17T09:13:05.818461","created_date":"2026-02-14T00:00:00"}