{"id":"https://openalex.org/W4411950020","doi":"https://doi.org/10.1109/iwcmc65282.2025.11059533","title":"Adversary-Resilient Clustered Federated Learning for Secure AI-Driven Healthcare Data Analytics","display_name":"Adversary-Resilient Clustered Federated Learning for Secure AI-Driven Healthcare Data Analytics","publication_year":2025,"publication_date":"2025-05-12","ids":{"openalex":"https://openalex.org/W4411950020","doi":"https://doi.org/10.1109/iwcmc65282.2025.11059533"},"language":"en","primary_location":{"id":"doi:10.1109/iwcmc65282.2025.11059533","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iwcmc65282.2025.11059533","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 International Wireless Communications and Mobile Computing (IWCMC)","raw_type":"proceedings-article"},"type":"article","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/A5034852927","display_name":"Abdullah Melhem","orcid":"https://orcid.org/0009-0000-5221-1430"},"institutions":[{"id":"https://openalex.org/I25041050","display_name":"Augusta University","ror":"https://ror.org/012mef835","country_code":"US","type":"education","lineage":["https://openalex.org/I25041050"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Abdullah Melhem","raw_affiliation_strings":["Augusta University,School of Computer and Cyber Sciences,Augusta,GA,USA,30912"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Augusta University,School of Computer and Cyber Sciences,Augusta,GA,USA,30912","institution_ids":["https://openalex.org/I25041050"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5060546610","display_name":"Ahmed Aleroud","orcid":"https://orcid.org/0000-0003-4337-1488"},"institutions":[{"id":"https://openalex.org/I25041050","display_name":"Augusta University","ror":"https://ror.org/012mef835","country_code":"US","type":"education","lineage":["https://openalex.org/I25041050"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ahmed Aleroud","raw_affiliation_strings":["Augusta University,School of Computer and Cyber Sciences,Augusta,GA,USA,30912"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Augusta University,School of Computer and Cyber Sciences,Augusta,GA,USA,30912","institution_ids":["https://openalex.org/I25041050"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025816011","display_name":"Abdullah Al Mamun","orcid":"https://orcid.org/0000-0002-9713-742X"},"institutions":[{"id":"https://openalex.org/I25041050","display_name":"Augusta University","ror":"https://ror.org/012mef835","country_code":"US","type":"education","lineage":["https://openalex.org/I25041050"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Abdullah Al-mamun","raw_affiliation_strings":["Augusta University,School of Computer and Cyber Sciences,Augusta,GA,USA,30912"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Augusta University,School of Computer and Cyber Sciences,Augusta,GA,USA,30912","institution_ids":["https://openalex.org/I25041050"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065573453","display_name":"George Karabatis","orcid":"https://orcid.org/0000-0002-2208-0801"},"institutions":[{"id":"https://openalex.org/I79272384","display_name":"University of Maryland, Baltimore County","ror":"https://ror.org/02qskvh78","country_code":"US","type":"education","lineage":["https://openalex.org/I79272384"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"George Karabatis","raw_affiliation_strings":["University of Maryland, Baltimore County (UMBC),Department of Information Systems,Baltimore,MD,USA,21250"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Maryland, Baltimore County (UMBC),Department of Information Systems,Baltimore,MD,USA,21250","institution_ids":["https://openalex.org/I79272384"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5053163516","display_name":"Mohamed I. Ibrahem","orcid":"https://orcid.org/0000-0002-8000-4161"},"institutions":[{"id":"https://openalex.org/I25041050","display_name":"Augusta University","ror":"https://ror.org/012mef835","country_code":"US","type":"education","lineage":["https://openalex.org/I25041050"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mohamed I. Ibrahem","raw_affiliation_strings":["Augusta University,School of Computer and Cyber Sciences,Augusta,GA,USA,30912"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Augusta University,School of Computer and Cyber Sciences,Augusta,GA,USA,30912","institution_ids":["https://openalex.org/I25041050"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"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":0.06926003,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"630","last_page":"636"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9983000159263611,"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/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9983000159263611,"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/adversary","display_name":"Adversary","score":0.752129077911377},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7267758846282959},{"id":"https://openalex.org/keywords/analytics","display_name":"Analytics","score":0.574339747428894},{"id":"https://openalex.org/keywords/health-care","display_name":"Health care","score":0.544559895992279},{"id":"https://openalex.org/keywords/data-analysis","display_name":"Data analysis","score":0.45032232999801636},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.4199880361557007},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.34715187549591064},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.17678579688072205}],"concepts":[{"id":"https://openalex.org/C41065033","wikidata":"https://www.wikidata.org/wiki/Q2825412","display_name":"Adversary","level":2,"score":0.752129077911377},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7267758846282959},{"id":"https://openalex.org/C79158427","wikidata":"https://www.wikidata.org/wiki/Q485396","display_name":"Analytics","level":2,"score":0.574339747428894},{"id":"https://openalex.org/C160735492","wikidata":"https://www.wikidata.org/wiki/Q31207","display_name":"Health care","level":2,"score":0.544559895992279},{"id":"https://openalex.org/C175801342","wikidata":"https://www.wikidata.org/wiki/Q1988917","display_name":"Data analysis","level":2,"score":0.45032232999801636},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.4199880361557007},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.34715187549591064},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.17678579688072205},{"id":"https://openalex.org/C50522688","wikidata":"https://www.wikidata.org/wiki/Q189833","display_name":"Economic growth","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iwcmc65282.2025.11059533","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iwcmc65282.2025.11059533","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 International Wireless Communications and Mobile Computing (IWCMC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W2148143831","https://openalex.org/W2607219512","https://openalex.org/W2979637109","https://openalex.org/W3036791758","https://openalex.org/W4290948380","https://openalex.org/W4313524863","https://openalex.org/W4319023769","https://openalex.org/W4366250293","https://openalex.org/W4377717231","https://openalex.org/W4379468355","https://openalex.org/W4384948739","https://openalex.org/W4389292332","https://openalex.org/W4390906206","https://openalex.org/W4394585290","https://openalex.org/W4400351510","https://openalex.org/W4400526840","https://openalex.org/W4403407837","https://openalex.org/W4403826461","https://openalex.org/W4405014304","https://openalex.org/W4405845641","https://openalex.org/W4408146343","https://openalex.org/W6728757088"],"related_works":["https://openalex.org/W4387985143","https://openalex.org/W4362599004","https://openalex.org/W2808242528","https://openalex.org/W1567638270","https://openalex.org/W4226266853","https://openalex.org/W4210252074","https://openalex.org/W3092201768","https://openalex.org/W2796632413","https://openalex.org/W2740083192","https://openalex.org/W2794907032"],"abstract_inverted_index":{"The":[0],"healthcare":[1,93],"sector":[2],"consistently":[3],"handles":[4],"vast":[5],"amounts":[6],"of":[7,68,77,100,137,165],"sensitive":[8],"data,":[9,28],"which":[10],"must":[11],"always":[12],"be":[13],"kept":[14],"secure":[15],"and":[16,57,86,96,145,160],"private.":[17],"Unlike":[18],"classical":[19,155],"machine":[20],"learning":[21,30,38],"(ML)":[22],"models":[23,45,72],"that":[24,118,151],"require":[25],"centralizing":[26],"all":[27],"federated":[29],"(FL)":[31],"addresses":[32,105],"privacy":[33,95],"concerns":[34],"by":[35,107,124,140],"enabling":[36],"collaborative":[37],"without":[39],"sharing":[40],"raw":[41],"data.":[42],"However,":[43],"FL":[44,88,101,110,156,167],"are":[46],"subject":[47],"to":[48,91,120],"limitations":[49],"when":[50],"managing":[51],"diverse":[52],"datasets":[53],"from":[54,127],"pervasive":[55],"sources":[56],"encounter":[58],"challenges":[59],"such":[60],"as":[61],"adversarial":[62,138],"threats;":[63],"in":[64,158],"addition,":[65],"the":[66,69,75,78,98,109,131,135,166],"generalizability":[67],"resulting":[70],"global":[71],"may":[73],"limit":[74],"effectiveness":[76],"analysis.":[79],"This":[80,103],"paper":[81],"presents":[82],"a":[83,114],"novel":[84],"decentralized":[85],"cluster-based":[87,143],"framework":[89,104],"designed":[90],"enhance":[92],"data":[94],"strengthen":[97],"security":[99,161],"processes.":[102],"vulnerabilities":[106],"decentralizing":[108],"models.":[111],"It":[112],"includes":[113],"weighted":[115],"voting":[116],"mechanism":[117],"aims":[119],"improve":[121],"analytics":[122],"accuracy":[123,159],"aggregating":[125],"decisions":[126],"multiple":[128],"clusters.":[129],"Additionally,":[130],"proposed":[132],"approach":[133,153],"reduces":[134],"risk":[136],"attacks":[139],"employing":[141],"both":[142],"strategies":[144],"feature-squeezing":[146],"(FS).":[147],"Experimental":[148],"results":[149],"show":[150],"our":[152],"surpasses":[154],"methods":[157],"at":[162],"various":[163],"stages":[164],"process.":[168]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}