{"id":"https://openalex.org/W4414110935","doi":"https://doi.org/10.1109/tifs.2025.3607257","title":"Stealthy and Effective Clean-Label Backdoor Attack via Adaptive Frequency-Domain Suppression and Trigger Combination","display_name":"Stealthy and Effective Clean-Label Backdoor Attack via Adaptive Frequency-Domain Suppression and Trigger Combination","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4414110935","doi":"https://doi.org/10.1109/tifs.2025.3607257"},"language":"en","primary_location":{"id":"doi:10.1109/tifs.2025.3607257","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tifs.2025.3607257","pdf_url":null,"source":{"id":"https://openalex.org/S61310614","display_name":"IEEE Transactions on Information Forensics and Security","issn_l":"1556-6013","issn":["1556-6013","1556-6021"],"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 Transactions on Information Forensics and Security","raw_type":"journal-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/A5063090253","display_name":"Chaoying Yuan","orcid":"https://orcid.org/0000-0001-8825-976X"},"institutions":[{"id":"https://openalex.org/I4210136246","display_name":"China Telecom (China)","ror":"https://ror.org/03jgnzt20","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210136246"]},{"id":"https://openalex.org/I4387153335","display_name":"China Telecom","ror":"https://ror.org/05p67dv18","country_code":null,"type":"company","lineage":["https://openalex.org/I4387153335"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Chaoying Yuan","raw_affiliation_strings":["China Telecom Research Institute, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0001-8825-976X","affiliations":[{"raw_affiliation_string":"China Telecom Research Institute, Shanghai, China","institution_ids":["https://openalex.org/I4210136246","https://openalex.org/I4387153335"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5067310940","display_name":"Jingpeng Bai","orcid":null},"institutions":[{"id":"https://openalex.org/I4210136246","display_name":"China Telecom (China)","ror":"https://ror.org/03jgnzt20","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210136246"]},{"id":"https://openalex.org/I4387153335","display_name":"China Telecom","ror":"https://ror.org/05p67dv18","country_code":null,"type":"company","lineage":["https://openalex.org/I4387153335"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jingpeng Bai","raw_affiliation_strings":["China Telecom Research Institute, Guangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"China Telecom Research Institute, Guangzhou, China","institution_ids":["https://openalex.org/I4210136246","https://openalex.org/I4387153335"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088985361","display_name":"Shumei Yuan","orcid":null},"institutions":[{"id":"https://openalex.org/I4210136246","display_name":"China Telecom (China)","ror":"https://ror.org/03jgnzt20","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210136246"]},{"id":"https://openalex.org/I4387153335","display_name":"China Telecom","ror":"https://ror.org/05p67dv18","country_code":null,"type":"company","lineage":["https://openalex.org/I4387153335"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shumei Yuan","raw_affiliation_strings":["China Telecom Research Institute, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"China Telecom Research Institute, Shanghai, China","institution_ids":["https://openalex.org/I4210136246","https://openalex.org/I4387153335"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5021527965","display_name":"Wei Ni","orcid":"https://orcid.org/0000-0003-0780-4637"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ni Wei","raw_affiliation_strings":["School of Communication Science and Engineering, Fudan University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Communication Science and Engineering, Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5063090253"],"corresponding_institution_ids":["https://openalex.org/I4210136246","https://openalex.org/I4387153335"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.28039728,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"20","issue":null,"first_page":"11295","last_page":"11310"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11241","display_name":"Advanced Malware Detection Techniques","score":0.9161999821662903,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T11241","display_name":"Advanced Malware Detection Techniques","score":0.9161999821662903,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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":0.9965999722480774},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.5990999937057495},{"id":"https://openalex.org/keywords/novelty","display_name":"Novelty","score":0.48240000009536743},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.3962000012397766},{"id":"https://openalex.org/keywords/affine-transformation","display_name":"Affine transformation","score":0.31349998712539673}],"concepts":[{"id":"https://openalex.org/C2781045450","wikidata":"https://www.wikidata.org/wiki/Q254569","display_name":"Backdoor","level":2,"score":0.9965999722480774},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8116999864578247},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.5990999937057495},{"id":"https://openalex.org/C2778738651","wikidata":"https://www.wikidata.org/wiki/Q16546687","display_name":"Novelty","level":2,"score":0.48240000009536743},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3962000012397766},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.3450999855995178},{"id":"https://openalex.org/C92757383","wikidata":"https://www.wikidata.org/wiki/Q382497","display_name":"Affine transformation","level":2,"score":0.31349998712539673},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.30649998784065247},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3010999858379364},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.26570001244544983}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tifs.2025.3607257","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tifs.2025.3607257","pdf_url":null,"source":{"id":"https://openalex.org/S61310614","display_name":"IEEE Transactions on Information Forensics and Security","issn_l":"1556-6013","issn":["1556-6013","1556-6021"],"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 Transactions on Information Forensics and Security","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G5359232621","display_name":null,"funder_award_id":"2025ZD1301500","funder_id":"https://openalex.org/F4320329860","funder_display_name":"National Science and Technology Major Project"}],"funders":[{"id":"https://openalex.org/F4320329860","display_name":"National Science and Technology Major Project","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":44,"referenced_works":["https://openalex.org/W1964859077","https://openalex.org/W2064076387","https://openalex.org/W2807363941","https://openalex.org/W2934843808","https://openalex.org/W2942091739","https://openalex.org/W2962785568","https://openalex.org/W2990270730","https://openalex.org/W2996800219","https://openalex.org/W3012113073","https://openalex.org/W3035595647","https://openalex.org/W3042368254","https://openalex.org/W3083185154","https://openalex.org/W3107337211","https://openalex.org/W3114686421","https://openalex.org/W3162804012","https://openalex.org/W3185070214","https://openalex.org/W3188772578","https://openalex.org/W4214537185","https://openalex.org/W4214680449","https://openalex.org/W4225928697","https://openalex.org/W4285196615","https://openalex.org/W4294982857","https://openalex.org/W4312280786","https://openalex.org/W4312568672","https://openalex.org/W4312569687","https://openalex.org/W4322486547","https://openalex.org/W4323655037","https://openalex.org/W4360995553","https://openalex.org/W4377142631","https://openalex.org/W4383503656","https://openalex.org/W4385453555","https://openalex.org/W4385569687","https://openalex.org/W4386113250","https://openalex.org/W4387068365","https://openalex.org/W4387385625","https://openalex.org/W4388145338","https://openalex.org/W4388867373","https://openalex.org/W4390577972","https://openalex.org/W4391667254","https://openalex.org/W4394597832","https://openalex.org/W4398757423","https://openalex.org/W4403183301","https://openalex.org/W4408520017","https://openalex.org/W4409374173"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W4320031223","https://openalex.org/W4200629851","https://openalex.org/W4281902577","https://openalex.org/W4309417370","https://openalex.org/W4292107232","https://openalex.org/W3009072493","https://openalex.org/W4401407399"],"abstract_inverted_index":{"Deep":[0],"Neural":[1],"Networks":[2],"(DNNs)":[3],"remain":[4],"vulnerable":[5],"to":[6,44,127,134,144],"backdoor":[7,30,39,59,173],"attacks.":[8,31],"These":[9],"attacks":[10,40,174],"are":[11,132,142],"pernicious":[12],"when":[13],"attackers":[14],"inject":[15],"a":[16,56,87,168],"trigger":[17,110,156],"into":[18],"the":[19,91,95,101,146,152,162,191],"input":[20],"data":[21],"without":[22],"altering":[23],"its":[24],"ground-truth":[25],"label,":[26],"known":[27],"as":[28],"clean-label":[29,38,58],"The":[32],"effectiveness":[33],"and":[34,51,84,108,120,139,148,183,201],"stealth":[35,71],"of":[36,90,97,118,151,161],"existing":[37],"rely":[41],"on":[42,79],"access":[43],"global":[45],"training":[46],"data,":[47,86],"making":[48],"them":[49],"resource-intensive":[50],"impractical.":[52],"This":[53],"paper":[54],"introduces":[55],"novel":[57],"attack":[60,64,93,166],"that":[61],"achieves":[62,167],"high":[63],"success":[65],"rates":[66],"(ASR)":[67],"while":[68,175],"maintaining":[69,176],"exceptional":[70],"under":[72],"realistic":[73],"constraints.":[74],"Unlike":[75],"prior":[76],"approaches":[77],"focused":[78],"spatial":[80,147],"differences":[81],"between":[82],"clean":[83],"poisoned":[85],"key":[88],"novelty":[89],"new":[92],"is":[94],"suppression":[96],"high-frequency":[98],"components":[99],"in":[100],"frequency":[102,149],"domain,":[103],"which":[104],"minimizes":[105],"human-detectable":[106],"contrasts":[107],"enhances":[109],"imperceptibility.":[111],"Moreover,":[112],"we":[113],"employ":[114],"an":[115],"affine":[116],"combination":[117],"static":[119,153],"adaptive":[121],"triggers,":[122,154],"effectively":[123],"balancing":[124],"their":[125],"strengths":[126],"maximize":[128],"ASR.":[129],"Surrogate":[130],"models":[131,141,182],"designed":[133],"simulate":[135],"victim":[136,163],"model":[137],"behavior":[138],"auxiliary":[140],"applied":[143],"extract":[145],"features":[150],"enabling":[155],"design":[157],"with":[158],"minimal":[159],"knowledge":[160],"model.":[164],"Our":[165],"higher":[169,177],"ASR":[170],"than":[171],"state-of-the-art":[172],"benign":[178],"accuracy":[179],"across":[180],"various":[181],"datasets.":[184],"It":[185],"also":[186],"demonstrates":[187],"strong":[188],"resistance":[189],"against":[190],"latest":[192],"defense":[193],"mechanisms,":[194],"including":[195],"STRIP,":[196],"SentiNet,":[197],"neural":[198],"cleanse,":[199],"fine-pruning,":[200],"ANP.":[202]},"counts_by_year":[],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}