{"id":"https://openalex.org/W7125905342","doi":"https://doi.org/10.1109/smc58881.2025.11343710","title":"CLEAR: A Clean-Label Backdoor Attack via Representation-Guided Trigger Embedding","display_name":"CLEAR: A Clean-Label Backdoor Attack via Representation-Guided Trigger Embedding","publication_year":2025,"publication_date":"2025-10-05","ids":{"openalex":"https://openalex.org/W7125905342","doi":"https://doi.org/10.1109/smc58881.2025.11343710"},"language":null,"primary_location":{"id":"doi:10.1109/smc58881.2025.11343710","is_oa":false,"landing_page_url":"https://doi.org/10.1109/smc58881.2025.11343710","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Systems, Man, and Cybernetics (SMC)","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/A5124144177","display_name":"Zhan Wu","orcid":null},"institutions":[{"id":"https://openalex.org/I36399199","display_name":"Nanjing University of Science and Technology","ror":"https://ror.org/00xp9wg62","country_code":"CN","type":"education","lineage":["https://openalex.org/I36399199"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zhan Wu","raw_affiliation_strings":["Nanjing University of Science and Technology,School of Cyber Science and Engineering,Nanjing,China,210094"],"affiliations":[{"raw_affiliation_string":"Nanjing University of Science and Technology,School of Cyber Science and Engineering,Nanjing,China,210094","institution_ids":["https://openalex.org/I36399199"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124137460","display_name":"Haipeng Li","orcid":null},"institutions":[{"id":"https://openalex.org/I36399199","display_name":"Nanjing University of Science and Technology","ror":"https://ror.org/00xp9wg62","country_code":"CN","type":"education","lineage":["https://openalex.org/I36399199"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haipeng Li","raw_affiliation_strings":["Nanjing University of Science and Technology,School of Cyber Science and Engineering,Nanjing,China,210094"],"affiliations":[{"raw_affiliation_string":"Nanjing University of Science and Technology,School of Cyber Science and Engineering,Nanjing,China,210094","institution_ids":["https://openalex.org/I36399199"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037583123","display_name":"D. Wu","orcid":null},"institutions":[{"id":"https://openalex.org/I36399199","display_name":"Nanjing University of Science and Technology","ror":"https://ror.org/00xp9wg62","country_code":"CN","type":"education","lineage":["https://openalex.org/I36399199"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Di Wu","raw_affiliation_strings":["Nanjing University of Science and Technology,School of Cyber Science and Engineering,Nanjing,China,210094"],"affiliations":[{"raw_affiliation_string":"Nanjing University of Science and Technology,School of Cyber Science and Engineering,Nanjing,China,210094","institution_ids":["https://openalex.org/I36399199"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5121220181","display_name":"Shuchao Pang","orcid":null},"institutions":[{"id":"https://openalex.org/I36399199","display_name":"Nanjing University of Science and Technology","ror":"https://ror.org/00xp9wg62","country_code":"CN","type":"education","lineage":["https://openalex.org/I36399199"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuchao Pang","raw_affiliation_strings":["Nanjing University of Science and Technology,School of Cyber Science and Engineering,Nanjing,China,210094"],"affiliations":[{"raw_affiliation_string":"Nanjing University of Science and Technology,School of Cyber Science and Engineering,Nanjing,China,210094","institution_ids":["https://openalex.org/I36399199"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5124144177"],"corresponding_institution_ids":["https://openalex.org/I36399199"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.87677953,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"5534","last_page":"5539"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9632999897003174,"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":0.9632999897003174,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.011300000362098217,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.004699999932199717,"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":0.9674999713897705},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.6294999718666077},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.6284999847412109},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.569599986076355},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.5264999866485596},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4666000008583069},{"id":"https://openalex.org/keywords/decision-boundary","display_name":"Decision boundary","score":0.3930000066757202},{"id":"https://openalex.org/keywords/boundary","display_name":"Boundary (topology)","score":0.37380000948905945}],"concepts":[{"id":"https://openalex.org/C2781045450","wikidata":"https://www.wikidata.org/wiki/Q254569","display_name":"Backdoor","level":2,"score":0.9674999713897705},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6327999830245972},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6294999718666077},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.6284999847412109},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5849000215530396},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.569599986076355},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.5264999866485596},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4666000008583069},{"id":"https://openalex.org/C42023084","wikidata":"https://www.wikidata.org/wiki/Q5249231","display_name":"Decision boundary","level":3,"score":0.3930000066757202},{"id":"https://openalex.org/C62354387","wikidata":"https://www.wikidata.org/wiki/Q875399","display_name":"Boundary (topology)","level":2,"score":0.37380000948905945},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.3646000027656555},{"id":"https://openalex.org/C89611455","wikidata":"https://www.wikidata.org/wiki/Q6804646","display_name":"Mechanism (biology)","level":2,"score":0.36000001430511475},{"id":"https://openalex.org/C142575187","wikidata":"https://www.wikidata.org/wiki/Q3358290","display_name":"Pyramid (geometry)","level":2,"score":0.35409998893737793},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.33500000834465027},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.33059999346733093},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.3172999918460846},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.3131999969482422},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.28519999980926514},{"id":"https://openalex.org/C112313634","wikidata":"https://www.wikidata.org/wiki/Q7886648","display_name":"Complement (music)","level":5,"score":0.26030001044273376},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2540999948978424}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/smc58881.2025.11343710","is_oa":false,"landing_page_url":"https://doi.org/10.1109/smc58881.2025.11343710","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Systems, Man, and Cybernetics (SMC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W2067713319","https://openalex.org/W2565639579","https://openalex.org/W2807363941","https://openalex.org/W2871166210","https://openalex.org/W2934843808","https://openalex.org/W2942091739","https://openalex.org/W2985913519","https://openalex.org/W2990270730","https://openalex.org/W3138516171","https://openalex.org/W3212981375","https://openalex.org/W4309374440","https://openalex.org/W4319964781","https://openalex.org/W4323655037","https://openalex.org/W4385245566","https://openalex.org/W4386076525","https://openalex.org/W4386299120","https://openalex.org/W4402727057","https://openalex.org/W4403582619","https://openalex.org/W4406367281","https://openalex.org/W4409365868"],"related_works":[],"abstract_inverted_index":{"Recent":[0],"studies":[1],"have":[2],"shown":[3],"that":[4,195],"although":[5],"DNNs":[6],"perform":[7],"well":[8],"on":[9,162,186],"visual":[10],"tasks,":[11],"they":[12],"are":[13],"still":[14],"vulnerable":[15],"to":[16,127,146],"clean-label":[17,62],"backdoor":[18,63],"attacks.":[19],"As":[20],"poisoned":[21,123],"samples":[22,94,101,156],"come":[23],"from":[24,96,108],"the":[25,28,37,40,43,49,76,88,97,113,117,122,128,158],"target":[26,44,81,98,129],"class,":[27],"model":[29,143],"learns":[30],"both":[31],"original":[32,110],"and":[33,42,46,80,165,188,192],"trigger":[34,41],"features,":[35],"weakening":[36],"association":[38],"between":[39,78],"label":[45],"thereby":[47],"reducing":[48],"attack":[50,64],"success":[51],"rate":[52],"(ASR).":[53],"To":[54],"address":[55],"this":[56],"issue,":[57],"we":[58],"propose":[59],"a":[60,141,173,180],"novel":[61],"framework,":[65],"named":[66],"CLEAR,":[67],"i.e.,":[68],"Clean-Label":[69],"Embedding":[70],"Attack":[71],"with":[72,144,179,190],"Representation-Guidance,":[73],"which":[74],"strengthens":[75],"correlation":[77],"triggers":[79,167],"labels":[82],"while":[83,116,200],"maintaining":[84,201],"high":[85],"stealth.":[86,203],"Specifically,":[87],"\"benign-label":[89],"push\"":[90],"mechanism":[91,120],"perturbs":[92],"clean":[93],"selected":[95],"class":[99,111,130],"(the":[100],"designated":[102],"for":[103],"poisoning),":[104],"pushing":[105],"them":[106],"away":[107],"their":[109],"in":[112],"feature":[114],"space,":[115],"\"target-label":[118],"pull\"":[119],"pulls":[121],"sample":[124],"representations":[125],"closer":[126],"through":[131],"saliency-guided":[132],"embedding.":[133],"CLEAR":[134,196],"consists":[135],"of":[136],"three":[137],"key":[138],"components:":[139],"integrating":[140],"diffusion":[142],"PGD":[145],"generate":[147],"natural":[148],"but":[149],"semantically":[150],"perturbed":[151],"adversarial":[152],"samples;":[153],"selecting":[154],"backdoor-susceptible":[155],"near":[157],"decision":[159],"boundary":[160],"based":[161],"classification":[163],"loss":[164],"embedding":[166],"into":[168],"high-saliency":[169],"regions":[170],"identified":[171],"using":[172],"Feature":[174],"Pyramid":[175],"Network":[176],"(FPN)":[177],"combined":[178],"local":[181],"self-attention":[182],"mechanism.":[183],"Experimental":[184],"results":[185],"CIFAR10":[187],"GTSRB":[189],"ResNet18":[191],"VGG16":[193],"demonstrate":[194],"generally":[197],"improves":[198],"ASR":[199],"strong":[202]},"counts_by_year":[],"updated_date":"2026-02-23T20:09:44.859080","created_date":"2026-01-29T00:00:00"}
