{"id":"https://openalex.org/W7138835194","doi":"https://doi.org/10.1109/globecom59602.2025.11431666","title":"Clean-Label Data Poisoning Attack based on Representation-Conditioned Data Generation","display_name":"Clean-Label Data Poisoning Attack based on Representation-Conditioned Data Generation","publication_year":2025,"publication_date":"2025-12-08","ids":{"openalex":"https://openalex.org/W7138835194","doi":"https://doi.org/10.1109/globecom59602.2025.11431666"},"language":null,"primary_location":{"id":"doi:10.1109/globecom59602.2025.11431666","is_oa":false,"landing_page_url":"https://doi.org/10.1109/globecom59602.2025.11431666","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"GLOBECOM 2025 - 2025 IEEE Global Communications Conference","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/A5100444337","display_name":"Wen Zhang","orcid":"https://orcid.org/0000-0001-5166-0736"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Wenbo Zhang","raw_affiliation_strings":["University of Electronic Science and Technology of China,School of Computer Science and Engineering,Chengdu,China"],"affiliations":[{"raw_affiliation_string":"University of Electronic Science and Technology of China,School of Computer Science and Engineering,Chengdu,China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129804027","display_name":"Xiong Li","orcid":null},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiong Li","raw_affiliation_strings":["University of Electronic Science and Technology of China,School of Computer Science and Engineering,Chengdu,China"],"affiliations":[{"raw_affiliation_string":"University of Electronic Science and Technology of China,School of Computer Science and Engineering,Chengdu,China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130020368","display_name":"Jiguo Yu","orcid":null},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiguo Yu","raw_affiliation_strings":["University of Electronic Science and Technology of China,School of Computer Science and Engineering,Chengdu,China"],"affiliations":[{"raw_affiliation_string":"University of Electronic Science and Technology of China,School of Computer Science and Engineering,Chengdu,China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130147971","display_name":"Vijayakumar P","orcid":null},"institutions":[{"id":"https://openalex.org/I122964287","display_name":"National Institute of Technology Tiruchirappalli","ror":"https://ror.org/047x65e68","country_code":"IN","type":"education","lineage":["https://openalex.org/I122964287"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Vijayakumar P","raw_affiliation_strings":["J.J. College of Engineering and Technology,Department of Information Technology,Tiruchirappalli,Tamil Nadu,India"],"affiliations":[{"raw_affiliation_string":"J.J. College of Engineering and Technology,Department of Information Technology,Tiruchirappalli,Tamil Nadu,India","institution_ids":["https://openalex.org/I122964287"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5051195514","display_name":"Mohammad S. Obaidat","orcid":"https://orcid.org/0000-0002-1569-9657"},"institutions":[{"id":"https://openalex.org/I114972647","display_name":"University of Jordan","ror":"https://ror.org/05k89ew48","country_code":"JO","type":"education","lineage":["https://openalex.org/I114972647"]}],"countries":["JO"],"is_corresponding":false,"raw_author_name":"Mohammad S. Obaidat","raw_affiliation_strings":["The University of Jordan,King Abdullah II School of Information Technology,Amman,Jordan"],"affiliations":[{"raw_affiliation_string":"The University of Jordan,King Abdullah II School of Information Technology,Amman,Jordan","institution_ids":["https://openalex.org/I114972647"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5123049954","display_name":"Xiaosong Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaosong Zhang","raw_affiliation_strings":["University of Electronic Science and Technology of China,School of Computer Science and Engineering,Chengdu,China"],"affiliations":[{"raw_affiliation_string":"University of Electronic Science and Technology of China,School of Computer Science and Engineering,Chengdu,China","institution_ids":["https://openalex.org/I150229711"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5100444337"],"corresponding_institution_ids":["https://openalex.org/I150229711"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.88084749,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1519","last_page":"1524"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.7565000057220459,"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":0.7565000057220459,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.0625,"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/T12262","display_name":"Hate Speech and Cyberbullying Detection","score":0.03590000048279762,"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/consistency","display_name":"Consistency (knowledge bases)","score":0.5800999999046326},{"id":"https://openalex.org/keywords/scheme","display_name":"Scheme (mathematics)","score":0.49480000138282776},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.48730000853538513},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.4607999920845032},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.4562999904155731},{"id":"https://openalex.org/keywords/constraint","display_name":"Constraint (computer-aided design)","score":0.44830000400543213},{"id":"https://openalex.org/keywords/data-integrity","display_name":"Data integrity","score":0.4156999886035919},{"id":"https://openalex.org/keywords/vulnerability","display_name":"Vulnerability (computing)","score":0.3765000104904175},{"id":"https://openalex.org/keywords/data-loss","display_name":"Data loss","score":0.3698999881744385}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6985999941825867},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.5800999999046326},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.49480000138282776},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.48730000853538513},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.487199991941452},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4609000086784363},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.4607999920845032},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.4562999904155731},{"id":"https://openalex.org/C2776036281","wikidata":"https://www.wikidata.org/wiki/Q48769818","display_name":"Constraint (computer-aided design)","level":2,"score":0.44830000400543213},{"id":"https://openalex.org/C33762810","wikidata":"https://www.wikidata.org/wiki/Q461671","display_name":"Data integrity","level":2,"score":0.4156999886035919},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.40720000863075256},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.38749998807907104},{"id":"https://openalex.org/C95713431","wikidata":"https://www.wikidata.org/wiki/Q631425","display_name":"Vulnerability (computing)","level":2,"score":0.3765000104904175},{"id":"https://openalex.org/C193519340","wikidata":"https://www.wikidata.org/wiki/Q891179","display_name":"Data loss","level":2,"score":0.3698999881744385},{"id":"https://openalex.org/C92446256","wikidata":"https://www.wikidata.org/wiki/Q3306762","display_name":"Data validation","level":2,"score":0.3635999858379364},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.3546999990940094},{"id":"https://openalex.org/C2164484","wikidata":"https://www.wikidata.org/wiki/Q5170150","display_name":"Core (optical fiber)","level":2,"score":0.3540000021457672},{"id":"https://openalex.org/C93361087","wikidata":"https://www.wikidata.org/wiki/Q4426698","display_name":"Data consistency","level":2,"score":0.3125999867916107},{"id":"https://openalex.org/C2779803651","wikidata":"https://www.wikidata.org/wiki/Q5282088","display_name":"Discriminator","level":3,"score":0.2980000078678131},{"id":"https://openalex.org/C2776145971","wikidata":"https://www.wikidata.org/wiki/Q30673951","display_name":"Labeled data","level":2,"score":0.29100000858306885},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.28360000252723694},{"id":"https://openalex.org/C65856478","wikidata":"https://www.wikidata.org/wiki/Q3991682","display_name":"Attack model","level":2,"score":0.2824999988079071},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.2734000086784363},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.26579999923706055},{"id":"https://openalex.org/C163985040","wikidata":"https://www.wikidata.org/wiki/Q1172399","display_name":"Data acquisition","level":2,"score":0.2522999942302704},{"id":"https://openalex.org/C138958017","wikidata":"https://www.wikidata.org/wiki/Q190087","display_name":"Data type","level":2,"score":0.251800000667572}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/globecom59602.2025.11431666","is_oa":false,"landing_page_url":"https://doi.org/10.1109/globecom59602.2025.11431666","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"GLOBECOM 2025 - 2025 IEEE Global Communications Conference","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W2985913519","https://openalex.org/W3084847664","https://openalex.org/W3087391814","https://openalex.org/W3145450063","https://openalex.org/W3180355996","https://openalex.org/W3217417806","https://openalex.org/W4283819233","https://openalex.org/W4386071584","https://openalex.org/W4387882840","https://openalex.org/W4388867373","https://openalex.org/W4415795348"],"related_works":[],"abstract_inverted_index":{"The":[0,106],"growing":[1],"demand":[2],"for":[3],"large-scale":[4],"training":[5,40],"data":[6,16,23,27,96,103,129],"in":[7,65,82,145,166,176],"deep":[8,117],"learning":[9,168],"has":[10],"promoted":[11],"the":[12,20,39,49,53,127,171],"use":[13],"of":[14,22,52,173],"open":[15,113],"collection,":[17],"thereby":[18],"increasing":[19],"risk":[21],"poisoning":[24,28,97],"attacks.":[25],"Clean-label":[26],"attacks":[29,175],"aim":[30],"to":[31,45],"compromise":[32],"models":[33],"by":[34,155,164],"injecting":[35],"malicious":[36],"samples":[37,54,125,137,153],"into":[38],"set,":[41],"while":[42,141],"being":[43],"constrained":[44],"maintain":[46],"consistency":[47],"between":[48],"visual":[50],"features":[51],"and":[55,80,84,121,147,160,169],"their":[56,116],"assigned":[57],"labels.":[58],"Though":[59],"this":[60,90],"constraint":[61],"enhances":[62],"attack":[63,98],"feasibility":[64],"real-world":[66],"settings,":[67],"it":[68],"also":[69],"introduces":[70],"significant":[71],"technical":[72],"challenges,":[73],"such":[74],"as":[75,119],"reliance":[76],"on":[77,101],"white-box":[78],"assumptions":[79],"limitations":[81],"stealth":[83,159],"effectiveness.":[85],"To":[86],"address":[87],"these":[88],"limitations,":[89],"paper":[91],"proposes":[92],"a":[93],"novel":[94],"clean-label":[95],"scheme":[99,107],"based":[100],"representation-conditioned":[102],"generation":[104,130],"(CPRCG).":[105],"identifies":[108],"\"natural":[109],"poisoned":[110],"data\"":[111],"from":[112],"datasets,":[114],"extracts":[115],"representations":[118],"constraints,":[120],"generates":[122],"numerous":[123],"new":[124],"using":[126],"conditional":[128],"model":[131],"MAsked":[132],"Generative":[133],"Encoder":[134],"(MAGE).":[135],"These":[136],"preserve":[138],"core":[139],"similarities":[140],"introducing":[142],"random":[143],"variations":[144],"form":[146],"behavior.":[148],"Experimental":[149],"results":[150],"show":[151],"that":[152],"generated":[154],"CPRCG":[156],"achieve":[157],"high":[158],"diversity,":[161],"outperforming":[162],"MetaPoison":[163],"4.1%":[165],"centralized":[167],"approaching":[170],"effectiveness":[172],"dirty-label":[174],"federated":[177],"learning.":[178]},"counts_by_year":[],"updated_date":"2026-03-20T20:54:20.808490","created_date":"2026-03-20T00:00:00"}
