{"id":"https://openalex.org/W3119031357","doi":"https://doi.org/10.1109/mce.2020.3048926","title":"FedLearnSP: Preserving Privacy and Security Using Federated Learning and Edge Computing","display_name":"FedLearnSP: Preserving Privacy and Security Using Federated Learning and Edge Computing","publication_year":2021,"publication_date":"2021-01-05","ids":{"openalex":"https://openalex.org/W3119031357","doi":"https://doi.org/10.1109/mce.2020.3048926","mag":"3119031357"},"language":"en","primary_location":{"id":"doi:10.1109/mce.2020.3048926","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mce.2020.3048926","pdf_url":null,"source":{"id":"https://openalex.org/S2483040032","display_name":"IEEE Consumer Electronics Magazine","issn_l":"2162-2248","issn":["2162-2248","2162-2256"],"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Consumer Electronics Magazine","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://figshare.com/articles/journal_contribution/FedLearnSP_Preserving_Privacy_and_Security_using_Federated_Learning_and_Edge_Computing/20678571","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5075334970","display_name":"Aaisha Makkar","orcid":"https://orcid.org/0000-0001-7203-6553"},"institutions":[{"id":"https://openalex.org/I101407740","display_name":"Chandigarh University","ror":"https://ror.org/05t4pvx35","country_code":"IN","type":"education","lineage":["https://openalex.org/I101407740"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Aaisha Makkar","raw_affiliation_strings":["Chandigarh University, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chandigarh University, India","institution_ids":["https://openalex.org/I101407740"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5018257276","display_name":"Uttam Ghosh","orcid":"https://orcid.org/0000-0003-1698-8888"},"institutions":[{"id":"https://openalex.org/I200719446","display_name":"Vanderbilt University","ror":"https://ror.org/02vm5rt34","country_code":"US","type":"education","lineage":["https://openalex.org/I200719446"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Uttam Ghosh","raw_affiliation_strings":["Vanderbilt University, USA"],"raw_orcid":"https://orcid.org/0000-0003-1698-8888","affiliations":[{"raw_affiliation_string":"Vanderbilt University, USA","institution_ids":["https://openalex.org/I200719446"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046343080","display_name":"Danda B. Rawat","orcid":"https://orcid.org/0000-0003-3638-3464"},"institutions":[{"id":"https://openalex.org/I137853757","display_name":"Howard University","ror":"https://ror.org/05gt1vc06","country_code":"US","type":"education","lineage":["https://openalex.org/I137853757"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Danda B. Rawat","raw_affiliation_strings":["Howard University, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Howard University, USA","institution_ids":["https://openalex.org/I137853757"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5019489166","display_name":"Jemal Abawajy","orcid":"https://orcid.org/0000-0001-8962-1222"},"institutions":[{"id":"https://openalex.org/I149704539","display_name":"Deakin University","ror":"https://ror.org/02czsnj07","country_code":"AU","type":"education","lineage":["https://openalex.org/I149704539"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Jemal H. Abawajy","raw_affiliation_strings":["Deakin University, Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Deakin University, Australia","institution_ids":["https://openalex.org/I149704539"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":4.3675,"has_fulltext":false,"cited_by_count":42,"citation_normalized_percentile":{"value":0.95050576,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":99},"biblio":{"volume":"11","issue":"2","first_page":"21","last_page":"27"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9998999834060669,"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":0.9998999834060669,"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/T11598","display_name":"Internet Traffic Analysis and Secure E-voting","score":0.9987000226974487,"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":0.9887999892234802,"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/computer-science","display_name":"Computer science","score":0.8741350173950195},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.6403580904006958},{"id":"https://openalex.org/keywords/overhead","display_name":"Overhead (engineering)","score":0.5995325446128845},{"id":"https://openalex.org/keywords/obstacle","display_name":"Obstacle","score":0.47829777002334595},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4353542923927307},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3965269923210144},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.3727399706840515},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.22122415900230408}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8741350173950195},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.6403580904006958},{"id":"https://openalex.org/C2779960059","wikidata":"https://www.wikidata.org/wiki/Q7113681","display_name":"Overhead (engineering)","level":2,"score":0.5995325446128845},{"id":"https://openalex.org/C2776650193","wikidata":"https://www.wikidata.org/wiki/Q264661","display_name":"Obstacle","level":2,"score":0.47829777002334595},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4353542923927307},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3965269923210144},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.3727399706840515},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.22122415900230408},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/mce.2020.3048926","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mce.2020.3048926","pdf_url":null,"source":{"id":"https://openalex.org/S2483040032","display_name":"IEEE Consumer Electronics Magazine","issn_l":"2162-2248","issn":["2162-2248","2162-2256"],"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Consumer Electronics Magazine","raw_type":"journal-article"},{"id":"pmh:oai:dro.deakin.edu.au:DU:30147535","is_oa":false,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4306401102","display_name":"Own your potential (DEAKIN)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I149704539","host_organization_name":"Deakin University","host_organization_lineage":["https://openalex.org/I149704539"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Journal Article"},{"id":"pmh:oai:figshare.com:article/20678571","is_oa":true,"landing_page_url":"https://figshare.com/articles/journal_contribution/FedLearnSP_Preserving_Privacy_and_Security_using_Federated_Learning_and_Edge_Computing/20678571","pdf_url":null,"source":{"id":"https://openalex.org/S4377196282","display_name":"Figshare","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210132348","host_organization_name":"Figshare (United Kingdom)","host_organization_lineage":["https://openalex.org/I4210132348"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Text"}],"best_oa_location":{"id":"pmh:oai:figshare.com:article/20678571","is_oa":true,"landing_page_url":"https://figshare.com/articles/journal_contribution/FedLearnSP_Preserving_Privacy_and_Security_using_Federated_Learning_and_Edge_Computing/20678571","pdf_url":null,"source":{"id":"https://openalex.org/S4377196282","display_name":"Figshare","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210132348","host_organization_name":"Figshare (United Kingdom)","host_organization_lineage":["https://openalex.org/I4210132348"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Text"},"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16","score":0.4399999976158142}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W2886073571","https://openalex.org/W2900120080","https://openalex.org/W2946930197","https://openalex.org/W2950012677","https://openalex.org/W2971484358","https://openalex.org/W3014538993","https://openalex.org/W3021026170","https://openalex.org/W3036941175","https://openalex.org/W6754708055","https://openalex.org/W6755988804","https://openalex.org/W6763393573"],"related_works":["https://openalex.org/W2364921833","https://openalex.org/W2302028273","https://openalex.org/W1525643724","https://openalex.org/W2961085424","https://openalex.org/W2067938758","https://openalex.org/W2382623646","https://openalex.org/W3087771547","https://openalex.org/W2333420780","https://openalex.org/W2375199418","https://openalex.org/W3120511008"],"abstract_inverted_index":{"Enormous":[0],"amount":[1],"of":[2,12,87,96,105,173],"information":[3],"is":[4,27,41,80],"processed":[5],"at":[6,60],"different":[7,13,138],"websites,":[8],"on":[9],"a":[10,28,46],"number":[11],"AI":[14,122],"tools":[15],"and":[16,35,63,130,143,149],"in":[17,137],"multiple":[18],"data":[19,22,56,76,146],"silos.":[20],"Sharing":[21],"between":[23],"various":[24],"sources,":[25,57],"this":[26],"significant":[29,195],"obstacle,":[30],"due":[31],"to":[32,54,83,93,108,124,170],"administrative,":[33],"organizational,":[34],"security":[36],"considerations.":[37],"One":[38],"possible":[39],"solution":[40,72],"federated":[42,106],"machine":[43,51],"learning":[44,52,107,134],"(FML),":[45],"system":[47],"that":[48,156,179],"simultaneously":[49],"sends":[50],"algorithms":[53],"all":[55],"trains":[58],"models":[59],"each":[61],"source,":[62],"aggregates":[64],"the":[65,75,81,85,94,103,132,162,167,177,188,191],"learned":[66],"models.":[67],"This":[68,78],"technique":[69],"ensures":[70],"consumer-influenced":[71],"by":[73,113],"processing":[74],"locally.":[77],"work":[79],"first":[82],"investigate":[84],"applicability":[86],"Internet":[88],"attack":[89],"detection":[90],"through":[91],"FML,":[92],"best":[95],"our":[97],"knowledge.":[98],"Our":[99,152],"primary":[100],"contributions":[101],"include":[102],"application":[104],"satisfy":[109],"customer":[110,145],"search":[111],"queries":[112],"detecting":[114],"malicious":[115],"spam":[116,197],"images,":[117,174],"which":[118],"may":[119,180],"lead":[120],"these":[121],"systems":[123],"retrieve":[125],"irrelevant":[126],"information.":[127],"We":[128],"assess":[129],"analyze":[131],"FML-entangled":[133],"output":[135],"comprehensively":[136],"ways":[139],"adjustments":[140],"including":[141,166],"balanced":[142],"imbalanced":[144],"distribution,":[147],"scalability,":[148],"overhead":[150],"communication.":[151],"measuring":[153],"results":[154],"show":[155],"FML":[157],"suits":[158],"practical":[159],"scenarios,":[160],"where":[161],"variable":[163],"image":[164,196],"size,":[165],"animation":[168],"ratio":[169],"legitimate":[171],"samples":[172],"present":[175],"among":[176],"advertisements":[178],"distract":[181],"consumer":[182],"from":[183],"fetching":[184],"relevant":[185],"results.":[186],"With":[187],"evaluated":[189],"results,":[190],"state-of-the-art":[192],"FedLearnSP":[193],"proved":[194],"detection.":[198]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":7},{"year":2023,"cited_by_count":12},{"year":2022,"cited_by_count":8},{"year":2021,"cited_by_count":5}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
