{"id":"https://openalex.org/W4308089865","doi":"https://doi.org/10.1109/secon55815.2022.9918550","title":"Assisting Backdoor Federated Learning with Whole Population Knowledge Alignment in Mobile Edge Computing","display_name":"Assisting Backdoor Federated Learning with Whole Population Knowledge Alignment in Mobile Edge Computing","publication_year":2022,"publication_date":"2022-09-20","ids":{"openalex":"https://openalex.org/W4308089865","doi":"https://doi.org/10.1109/secon55815.2022.9918550"},"language":"en","primary_location":{"id":"doi:10.1109/secon55815.2022.9918550","is_oa":false,"landing_page_url":"https://doi.org/10.1109/secon55815.2022.9918550","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 19th Annual IEEE International Conference on Sensing, Communication, and Networking (SECON)","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/A5100365651","display_name":"Tian Liu","orcid":"https://orcid.org/0000-0002-4587-4399"},"institutions":[{"id":"https://openalex.org/I82497590","display_name":"Auburn University","ror":"https://ror.org/02v80fc35","country_code":"US","type":"education","lineage":["https://openalex.org/I82497590"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Tian Liu","raw_affiliation_strings":["Auburn University,Department of Computer Science and Software Engineering,Auburn,AL,USA,36849"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Auburn University,Department of Computer Science and Software Engineering,Auburn,AL,USA,36849","institution_ids":["https://openalex.org/I82497590"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5045980180","display_name":"Xueyang Hu","orcid":"https://orcid.org/0000-0001-5229-6462"},"institutions":[{"id":"https://openalex.org/I82497590","display_name":"Auburn University","ror":"https://ror.org/02v80fc35","country_code":"US","type":"education","lineage":["https://openalex.org/I82497590"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xueyang Hu","raw_affiliation_strings":["Auburn University,Department of Computer Science and Software Engineering,Auburn,AL,USA,36849"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Auburn University,Department of Computer Science and Software Engineering,Auburn,AL,USA,36849","institution_ids":["https://openalex.org/I82497590"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5037017610","display_name":"Tao Shu","orcid":"https://orcid.org/0000-0002-0173-2559"},"institutions":[{"id":"https://openalex.org/I82497590","display_name":"Auburn University","ror":"https://ror.org/02v80fc35","country_code":"US","type":"education","lineage":["https://openalex.org/I82497590"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Tao Shu","raw_affiliation_strings":["Auburn University,Department of Computer Science and Software Engineering,Auburn,AL,USA,36849"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Auburn University,Department of Computer Science and Software Engineering,Auburn,AL,USA,36849","institution_ids":["https://openalex.org/I82497590"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I82497590"],"apc_list":null,"apc_paid":null,"fwci":0.5551,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.72706916,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"416","last_page":"424"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9993000030517578,"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":0.9993000030517578,"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":0.989300012588501,"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/backdoor","display_name":"Backdoor","score":0.9989784359931946},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.671954870223999},{"id":"https://openalex.org/keywords/population","display_name":"Population","score":0.5112166404724121},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5027403831481934},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.49962663650512695},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.48984286189079285},{"id":"https://openalex.org/keywords/one-shot","display_name":"One shot","score":0.4718344807624817},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.28712397813796997},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.17342305183410645},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.06738615036010742}],"concepts":[{"id":"https://openalex.org/C2781045450","wikidata":"https://www.wikidata.org/wiki/Q254569","display_name":"Backdoor","level":2,"score":0.9989784359931946},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.671954870223999},{"id":"https://openalex.org/C2908647359","wikidata":"https://www.wikidata.org/wiki/Q2625603","display_name":"Population","level":2,"score":0.5112166404724121},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5027403831481934},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.49962663650512695},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.48984286189079285},{"id":"https://openalex.org/C2992734406","wikidata":"https://www.wikidata.org/wiki/Q413267","display_name":"One shot","level":2,"score":0.4718344807624817},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.28712397813796997},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.17342305183410645},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.06738615036010742},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0},{"id":"https://openalex.org/C99454951","wikidata":"https://www.wikidata.org/wiki/Q932068","display_name":"Environmental health","level":1,"score":0.0},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/secon55815.2022.9918550","is_oa":false,"landing_page_url":"https://doi.org/10.1109/secon55815.2022.9918550","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 19th Annual IEEE International Conference on Sensing, Communication, and Networking (SECON)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6899999976158142,"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":40,"referenced_works":["https://openalex.org/W190008395","https://openalex.org/W2051267297","https://openalex.org/W2061570747","https://openalex.org/W2106313770","https://openalex.org/W2473418344","https://openalex.org/W2591882872","https://openalex.org/W2752689052","https://openalex.org/W2804073516","https://openalex.org/W2807006176","https://openalex.org/W2810065831","https://openalex.org/W2897830718","https://openalex.org/W2903389359","https://openalex.org/W2913318911","https://openalex.org/W2936608441","https://openalex.org/W2962835266","https://openalex.org/W2963456518","https://openalex.org/W2967119243","https://openalex.org/W2980189717","https://openalex.org/W3003426262","https://openalex.org/W3100779497","https://openalex.org/W3106047871","https://openalex.org/W4287670603","https://openalex.org/W4287977550","https://openalex.org/W4288055034","https://openalex.org/W4289276743","https://openalex.org/W6728757088","https://openalex.org/W6743821447","https://openalex.org/W6748786018","https://openalex.org/W6748805329","https://openalex.org/W6752029299","https://openalex.org/W6752600739","https://openalex.org/W6756226953","https://openalex.org/W6756699189","https://openalex.org/W6769363912","https://openalex.org/W6771533808","https://openalex.org/W6772265129","https://openalex.org/W6773366154","https://openalex.org/W6780640148","https://openalex.org/W6803014478","https://openalex.org/W6840877907"],"related_works":["https://openalex.org/W2188112492","https://openalex.org/W2800394942","https://openalex.org/W3184896852","https://openalex.org/W2565902605","https://openalex.org/W2944849713","https://openalex.org/W4200062291","https://openalex.org/W2081647779","https://openalex.org/W3044223678","https://openalex.org/W2774423163","https://openalex.org/W1607472309"],"abstract_inverted_index":{"The":[0],"development":[1],"of":[2,5,12,45,71,118],"the":[3,10,38,42,51,65,69,72,76,81,92,110,114,119,138,144,147,155,172],"Internet":[4],"Things":[6],"(IoT)":[7],"combined":[8],"with":[9],"emergence":[11],"federated":[13],"learning":[14],"(FL)":[15],"makes":[16],"it":[17],"possible":[18],"for":[19,137],"mobile":[20],"edge":[21],"computing":[22],"(MEC)":[23],"to":[24,41,55,161],"gain":[25],"insight":[26],"from":[27,143],"physically":[28],"separated":[29],"data":[30],"without":[31,67],"violating":[32],"privacy":[33],"or":[34],"burdening":[35],"communication":[36],"and":[37,116,183],"server.":[39],"Due":[40],"distributed":[43],"nature":[44],"MEC,":[46],"researchers":[47],"have":[48],"uncovered":[49],"that":[50,103,171],"FL":[52,66,104],"is":[53,85,158],"vulnerable":[54],"backdoor":[56,78,95,130,140,150,156,174,177],"attacks,":[57],"which":[58,132],"aim":[59],"at":[60],"injecting":[61],"a":[62,128,134],"subtask":[63],"into":[64],"corrupting":[68],"performance":[70],"main":[73],"task.":[74],"However,":[75],"single-shot":[77,94],"attack":[79,96],"in":[80,179,190],"early":[82],"training":[83],"stage":[84],"weak.":[86],"In":[87],"this":[88,124],"paper,":[89],"we":[90,126],"strengthen":[91],"early-injected":[93],"by":[97,164],"using":[98],"information":[99],"leakage.":[100],"We":[101],"show":[102,170],"convergence":[105],"can":[106],"be":[107,162],"expedited":[108],"if":[109],"client's":[111],"dataset":[112],"mimics":[113],"distribution":[115],"gradients":[117],"whole":[120],"population.":[121],"Based":[122],"on":[123],"observation,":[125],"propose":[127],"two-phase":[129],"attack,":[131],"includes":[133],"preliminary":[135,145],"phase":[136],"subsequent":[139],"attack.":[141],"Benefiting":[142],"phase,":[146],"later":[148],"injected":[149],"achieves":[151],"better":[152],"effectiveness,":[153],"as":[154],"effect":[157],"less":[159],"likely":[160],"diluted":[163],"normal":[165],"model":[166],"updates.":[167],"Numerical":[168],"experiments":[169],"proposed":[173],"outperforms":[175],"existing":[176],"attacks":[178],"both":[180],"success":[181],"rate":[182],"longevity,":[184],"even":[185],"when":[186],"defense":[187],"mechanisms":[188],"are":[189],"place.":[191]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1}],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-10T00:00:00"}