{"id":"https://openalex.org/W7171559581","doi":"https://doi.org/10.1145/3807503.3819377","title":"Adversarially Robust Federated Learning for IoMT-based Physiological Condition Monitoring: A Benchmark Dataset and ML-Aided Aggregation Framework","display_name":"Adversarially Robust Federated Learning for IoMT-based Physiological Condition Monitoring: A Benchmark Dataset and ML-Aided Aggregation Framework","publication_year":2026,"publication_date":"2026-06-30","ids":{"openalex":"https://openalex.org/W7171559581","doi":"https://doi.org/10.1145/3807503.3819377"},"language":null,"primary_location":{"id":"doi:10.1145/3807503.3819377","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3807503.3819377","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 17th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1145/3807503.3819377","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5143818943","display_name":"Kim Andy Ysteb\u00f8","orcid":"https://orcid.org/0009-0009-2007-3382"},"institutions":[{"id":"https://openalex.org/I2800207870","display_name":"H\u00f8yskolen Kristiania","ror":"https://ror.org/03gss5916","country_code":"NO","type":"education","lineage":["https://openalex.org/I2800207870"]}],"countries":["NO"],"is_corresponding":false,"raw_author_name":"Kim Andy Ysteb\u00f8","raw_affiliation_strings":["Kristiania University of Applied Sciences, Bergen, Norway"],"raw_orcid":"https://orcid.org/0009-0009-2007-3382","affiliations":[{"raw_affiliation_string":"Kristiania University of Applied Sciences, Bergen, Norway","institution_ids":["https://openalex.org/I2800207870"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5143830282","display_name":"Carl-Eirik Dahl Johnsen","orcid":"https://orcid.org/0009-0001-3190-4876"},"institutions":[{"id":"https://openalex.org/I2800207870","display_name":"H\u00f8yskolen Kristiania","ror":"https://ror.org/03gss5916","country_code":"NO","type":"education","lineage":["https://openalex.org/I2800207870"]}],"countries":["NO"],"is_corresponding":false,"raw_author_name":"Carl-Eirik Dahl Johnsen","raw_affiliation_strings":["Kristiania University of Applied Sciences, Bergen, Norway"],"raw_orcid":"https://orcid.org/0009-0001-3190-4876","affiliations":[{"raw_affiliation_string":"Kristiania University of Applied Sciences, Bergen, Norway","institution_ids":["https://openalex.org/I2800207870"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5143759215","display_name":"Lars-Even Stubberud Andersen","orcid":"https://orcid.org/0009-0002-8958-3355"},"institutions":[{"id":"https://openalex.org/I2800207870","display_name":"H\u00f8yskolen Kristiania","ror":"https://ror.org/03gss5916","country_code":"NO","type":"education","lineage":["https://openalex.org/I2800207870"]}],"countries":["NO"],"is_corresponding":false,"raw_author_name":"Lars-Even Stubberud Andersen","raw_affiliation_strings":["Kristiania University of Applied Sciences, Bergen, Norway"],"raw_orcid":"https://orcid.org/0009-0002-8958-3355","affiliations":[{"raw_affiliation_string":"Kristiania University of Applied Sciences, Bergen, Norway","institution_ids":["https://openalex.org/I2800207870"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058802025","display_name":"Bithi Banik","orcid":null},"institutions":[{"id":"https://openalex.org/I2800207870","display_name":"H\u00f8yskolen Kristiania","ror":"https://ror.org/03gss5916","country_code":"NO","type":"education","lineage":["https://openalex.org/I2800207870"]}],"countries":["NO"],"is_corresponding":false,"raw_author_name":"Bithi Banik","raw_affiliation_strings":["Kristiania University of Applied Sciences, Bergen, Norway"],"raw_orcid":"https://orcid.org/0009-0002-6891-9999","affiliations":[{"raw_affiliation_string":"Kristiania University of Applied Sciences, Bergen, Norway","institution_ids":["https://openalex.org/I2800207870"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102720588","display_name":"Debasish Ghose","orcid":"https://orcid.org/0000-0001-6310-2192"},"institutions":[{"id":"https://openalex.org/I2800207870","display_name":"H\u00f8yskolen Kristiania","ror":"https://ror.org/03gss5916","country_code":"NO","type":"education","lineage":["https://openalex.org/I2800207870"]}],"countries":["NO"],"is_corresponding":false,"raw_author_name":"Debasish Ghose","raw_affiliation_strings":["Kristiania University of Applied Sciences, Bergen, Norway"],"raw_orcid":"https://orcid.org/0000-0001-6310-2192","affiliations":[{"raw_affiliation_string":"Kristiania University of Applied Sciences, Bergen, Norway","institution_ids":["https://openalex.org/I2800207870"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I2800207870"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":null,"topics":[],"keywords":[{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5795999765396118},{"id":"https://openalex.org/keywords/federated-learning","display_name":"Federated learning","score":0.46230000257492065},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.3262999951839447},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.2800000011920929},{"id":"https://openalex.org/keywords/work","display_name":"Work (physics)","score":0.2750000059604645}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6819000244140625},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5795999765396118},{"id":"https://openalex.org/C2992525071","wikidata":"https://www.wikidata.org/wiki/Q50818671","display_name":"Federated learning","level":2,"score":0.46230000257492065},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.42480000853538513},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.39570000767707825},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3472000062465668},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.3262999951839447},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.2800000011920929},{"id":"https://openalex.org/C18762648","wikidata":"https://www.wikidata.org/wiki/Q42213","display_name":"Work (physics)","level":2,"score":0.2750000059604645},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.2612999975681305},{"id":"https://openalex.org/C82578977","wikidata":"https://www.wikidata.org/wiki/Q16773055","display_name":"Data aggregator","level":3,"score":0.25999999046325684}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3807503.3819377","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3807503.3819377","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 17th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3807503.3819377","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3807503.3819377","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 17th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W123295786","https://openalex.org/W2026891775","https://openalex.org/W2894771803","https://openalex.org/W4321372210","https://openalex.org/W4381185174","https://openalex.org/W4381795629","https://openalex.org/W4385763933","https://openalex.org/W4391883794","https://openalex.org/W4413180015","https://openalex.org/W4415481070","https://openalex.org/W7114901802","https://openalex.org/W7143414165"],"related_works":[],"abstract_inverted_index":{"Federated":[0],"learning":[1],"(FL)":[2],"is":[3],"increasingly":[4],"employed":[5],"in":[6,154],"Internet":[7,135],"of":[8,22,79,114,136],"Medical":[9],"Things":[10,137],"(IoMT)":[11],"systems":[12],"to":[13,34,43,120,126,151],"enable":[14],"collaborative":[15],"model":[16,37,89,115,175],"training":[17],"while":[18],"preserving":[19],"the":[20,145,159],"privacy":[21],"sensitive":[23],"physiological":[24],"data.":[25],"Despite":[26],"its":[27],"advantages,":[28],"IoMT-oriented":[29],"FL":[30],"remains":[31],"highly":[32],"vulnerable":[33],"data":[35],"poisoning,":[36,38],"and":[39,49,111,123,173],"Byzantine":[40],"attacks":[41],"due":[42],"device":[44],"heterogeneity,":[45],"limited":[46],"computational":[47],"resources,":[48],"open":[50],"client":[51,105],"participation,":[52],"challenges":[53],"that":[54,101,144],"existing":[55,166],"robust":[56,167],"aggregation":[57,99,162,168],"techniques":[58],"do":[59],"not":[60],"fully":[61],"address.":[62],"In":[63],"this":[64,92],"work,":[65],"we":[66,94],"introduce":[67],"a":[68,96,103],"benchmark":[69],"dataset":[70],"specifically":[71],"tailored":[72],"for":[73],"IoMT":[74],"environments,":[75],"enabling":[76],"systematic":[77],"evaluation":[78],"adversarial":[80,118,181],"behaviors":[81],"through":[82],"high-dimensional":[83],"feature":[84],"representations":[85],"derived":[86],"from":[87],"client-side":[88],"updates.":[90],"Using":[91],"benchmark,":[93],"propose":[95],"machine-learning":[97],"(ML)-assisted":[98],"framework":[100,163],"incorporates":[102],"malicious":[104],"detection":[106,147],"module":[107,148],"based":[108],"on":[109,132],"geometric":[110],"statistical":[112],"properties":[113],"weights,":[116],"allowing":[117],"updates":[119],"be":[121],"identified":[122],"filtered":[124],"prior":[125],"global":[127],"aggregation.":[128],"Extensive":[129],"experiments":[130],"conducted":[131],"ten":[133],"resource-constrained":[134],"devices,":[138],"i.e.,":[139],"Raspberry":[140],"Pi":[141],"platforms,":[142],"demonstrate":[143],"proposed":[146,160],"achieves":[149],"up":[150],"99%":[152],"accuracy":[153,176],"multi-class":[155],"attack":[156],"identification.":[157],"Furthermore,":[158],"ML-assisted":[161],"consistently":[164],"outperforms":[165],"methods,":[169],"exhibiting":[170],"faster":[171],"convergence":[172],"sustained":[174],"across":[177],"communication":[178],"rounds":[179],"under":[180],"conditions.":[182]},"counts_by_year":[],"updated_date":"2026-07-30T17:31:21.811387","created_date":"2026-07-29T00:00:00"}
