{"id":"https://openalex.org/W4400536026","doi":"https://doi.org/10.1145/3677380","title":"Exploiting Backdoors of Face Synthesis Detection with Natural Triggers","display_name":"Exploiting Backdoors of Face Synthesis Detection with Natural Triggers","publication_year":2024,"publication_date":"2024-07-11","ids":{"openalex":"https://openalex.org/W4400536026","doi":"https://doi.org/10.1145/3677380"},"language":"en","primary_location":{"id":"doi:10.1145/3677380","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3677380","pdf_url":null,"source":{"id":"https://openalex.org/S19610489","display_name":"ACM Transactions on Multimedia Computing Communications and Applications","issn_l":"1551-6857","issn":["1551-6857","1551-6865"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Multimedia Computing, Communications, and Applications","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/A5081765472","display_name":"Xiaoxuan Han","orcid":null},"institutions":[{"id":"https://openalex.org/I4210100255","display_name":"Beijing Academy of Artificial Intelligence","ror":"https://ror.org/016a74861","country_code":"CN","type":"other","lineage":["https://openalex.org/I4210100255"]},{"id":"https://openalex.org/I4210112150","display_name":"Institute of Automation","ror":"https://ror.org/022c3hy66","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]},{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaoxuan Han","raw_affiliation_strings":["NLPR &amp; MAIS, Institute of Automation, Chinese Academy of Sciences, Beijing, China and School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China","School of Artificial Intelligence, University of Chinese Academy of Sciences; NLPR &amp; MAIS, Institute of Automation, Chinese Academy of Sciences, China"],"raw_orcid":"https://orcid.org/0009-0008-9526-3351","affiliations":[{"raw_affiliation_string":"NLPR &amp; MAIS, Institute of Automation, Chinese Academy of Sciences, Beijing, China and School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210100255","https://openalex.org/I4210112150"]},{"raw_affiliation_string":"School of Artificial Intelligence, University of Chinese Academy of Sciences; NLPR &amp; MAIS, Institute of Automation, Chinese Academy of Sciences, China","institution_ids":["https://openalex.org/I4210112150","https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101649664","display_name":"Songlin Yang","orcid":"https://orcid.org/0000-0003-3403-376X"},"institutions":[{"id":"https://openalex.org/I4210100255","display_name":"Beijing Academy of Artificial Intelligence","ror":"https://ror.org/016a74861","country_code":"CN","type":"other","lineage":["https://openalex.org/I4210100255"]},{"id":"https://openalex.org/I4210112150","display_name":"Institute of Automation","ror":"https://ror.org/022c3hy66","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]},{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Songlin Yang","raw_affiliation_strings":["NLPR &amp; MAIS, Institute of Automation, Chinese Academy of Sciences, Beijing, China and School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China","School of Artificial Intelligence, University of Chinese Academy of Sciences; NLPR &amp; MAIS, Institute of Automation, Chinese Academy of Sciences, China"],"raw_orcid":"https://orcid.org/0000-0003-3403-376X","affiliations":[{"raw_affiliation_string":"NLPR &amp; MAIS, Institute of Automation, Chinese Academy of Sciences, Beijing, China and School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210100255","https://openalex.org/I4210112150"]},{"raw_affiliation_string":"School of Artificial Intelligence, University of Chinese Academy of Sciences; NLPR &amp; MAIS, Institute of Automation, Chinese Academy of Sciences, China","institution_ids":["https://openalex.org/I4210112150","https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100757829","display_name":"Wei Wang","orcid":"https://orcid.org/0000-0002-8598-0831"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210112150","display_name":"Institute of Automation","ror":"https://ror.org/022c3hy66","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Wang","raw_affiliation_strings":["NLPR &amp; MAIS, Institute of Automation, Chinese Academy of Sciences, Beijing, China","NLPR &amp; MAIS, Institute of Automation, Chinese Academy of Sciences, China"],"raw_orcid":"https://orcid.org/0000-0002-8598-0831","affiliations":[{"raw_affiliation_string":"NLPR &amp; MAIS, Institute of Automation, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210112150"]},{"raw_affiliation_string":"NLPR &amp; MAIS, Institute of Automation, Chinese Academy of Sciences, China","institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053180123","display_name":"Ziwen He","orcid":"https://orcid.org/0000-0002-1019-3884"},"institutions":[{"id":"https://openalex.org/I200845125","display_name":"Nanjing University of Information Science and Technology","ror":"https://ror.org/02y0rxk19","country_code":"CN","type":"education","lineage":["https://openalex.org/I200845125"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ziwen He","raw_affiliation_strings":["Nanjing University of Information Science and Technology, Nanjing, China","Nanjing University of Information Science and Technology, China"],"raw_orcid":"https://orcid.org/0000-0002-1019-3884","affiliations":[{"raw_affiliation_string":"Nanjing University of Information Science and Technology, Nanjing, China","institution_ids":["https://openalex.org/I200845125"]},{"raw_affiliation_string":"Nanjing University of Information Science and Technology, China","institution_ids":["https://openalex.org/I200845125"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5017743261","display_name":"Jing Dong","orcid":"https://orcid.org/0000-0002-2763-7832"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210112150","display_name":"Institute of Automation","ror":"https://ror.org/022c3hy66","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jing Dong","raw_affiliation_strings":["NLPR &amp; MAIS, Institute of Automation, Chinese Academy of Sciences, Beijing, China","NLPR &amp; MAIS, Institute of Automation, Chinese Academy of Sciences, China"],"raw_orcid":"https://orcid.org/0000-0002-2763-7832","affiliations":[{"raw_affiliation_string":"NLPR &amp; MAIS, Institute of Automation, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210112150"]},{"raw_affiliation_string":"NLPR &amp; MAIS, Institute of Automation, Chinese Academy of Sciences, China","institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.329,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.51918391,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":97},"biblio":{"volume":"21","issue":"2","first_page":"1","last_page":"24"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11448","display_name":"Face recognition and analysis","score":0.9998000264167786,"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"}},"topics":[{"id":"https://openalex.org/T11448","display_name":"Face recognition and analysis","score":0.9998000264167786,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.9994000196456909,"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/T12357","display_name":"Digital Media Forensic Detection","score":0.9991999864578247,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/backdoor","display_name":"Backdoor","score":0.9982571601867676},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7189379334449768},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5420539975166321},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.43206387758255005},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.431867778301239},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.4179967939853668},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.40545380115509033}],"concepts":[{"id":"https://openalex.org/C2781045450","wikidata":"https://www.wikidata.org/wiki/Q254569","display_name":"Backdoor","level":2,"score":0.9982571601867676},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7189379334449768},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5420539975166321},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.43206387758255005},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.431867778301239},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.4179967939853668},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.40545380115509033},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3677380","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3677380","pdf_url":null,"source":{"id":"https://openalex.org/S19610489","display_name":"ACM Transactions on Multimedia Computing Communications and Applications","issn_l":"1551-6857","issn":["1551-6857","1551-6865"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Multimedia Computing, Communications, and Applications","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities","score":0.6700000166893005}],"awards":[{"id":"https://openalex.org/G3451019941","display_name":null,"funder_award_id":"62372452","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":49,"referenced_works":["https://openalex.org/W1530404542","https://openalex.org/W1834627138","https://openalex.org/W2103559027","https://openalex.org/W2243397390","https://openalex.org/W2341528187","https://openalex.org/W2531409750","https://openalex.org/W2543927648","https://openalex.org/W2560674852","https://openalex.org/W2616247523","https://openalex.org/W2620971809","https://openalex.org/W2747329762","https://openalex.org/W2891145043","https://openalex.org/W2934843808","https://openalex.org/W2942091739","https://openalex.org/W2962770929","https://openalex.org/W2963720850","https://openalex.org/W2982058372","https://openalex.org/W2998718632","https://openalex.org/W3012113073","https://openalex.org/W3034431451","https://openalex.org/W3034577585","https://openalex.org/W3034864980","https://openalex.org/W3038930935","https://openalex.org/W3083246145","https://openalex.org/W3094728142","https://openalex.org/W3101998545","https://openalex.org/W3102564565","https://openalex.org/W3106646114","https://openalex.org/W3118479706","https://openalex.org/W3174656926","https://openalex.org/W3174814557","https://openalex.org/W3176241004","https://openalex.org/W3194230325","https://openalex.org/W4206230075","https://openalex.org/W4214809420","https://openalex.org/W4231258501","https://openalex.org/W4242753176","https://openalex.org/W4243272515","https://openalex.org/W4280579728","https://openalex.org/W4286588289","https://openalex.org/W4286696412","https://openalex.org/W4297811796","https://openalex.org/W4313127140","https://openalex.org/W4361003656","https://openalex.org/W4365451524","https://openalex.org/W4382119155","https://openalex.org/W4387968060","https://openalex.org/W4392552355","https://openalex.org/W6600175266"],"related_works":["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/W4386080799","https://openalex.org/W3140988292","https://openalex.org/W4317672133","https://openalex.org/W4380075502"],"abstract_inverted_index":{"Deep":[0],"neural":[1],"networks":[2],"have":[3],"enhanced":[4],"face":[5,77],"synthesis":[6,78],"detection":[7,79,107,141,147],"in":[8,85,129],"discriminating":[9],"Artificial":[10],"Intelligence":[11],"Generated":[12],"Content":[13],"(AIGC).":[14],"However,":[15],"their":[16],"security":[17],"is":[18,195],"threatened":[19],"by":[20,113,255],"the":[21,55,86,111,115,125,130,138,146,150,156,174],"injection":[22],"of":[23,281],"carefully":[24],"crafted":[25],"triggers":[26,60,84,168],"during":[27],"model":[28,108,229],"training":[29],"(i.e.,":[30],"backdoor":[31,35,59,74,92,167,201,249],"attacks).":[32],"Although":[33],"existing":[34,198,248],"defenses":[36,250],"and":[37,109,159,181,187,232,278],"manual":[38],"data":[39,283],"selection":[40],"are":[41,184],"able":[42],"to":[43,133,144,173,221],"mitigate":[44],"those":[45],"using":[46],"human-eye-sensitive":[47,270],"triggers,":[48,68],"such":[49,91],"as":[50],"patches":[51],"or":[52],"adversarial":[53],"noises,":[54],"more":[56,185],"challenging":[57],"natural":[58,67,83,186],"remain":[61],"insufficiently":[62],"researched.":[63],"To":[64],"further":[65],"investigate":[66],"we":[69,103,123,153],"propose":[70],"a":[71,105,260,272,279],"novel":[72],"analysis-by-synthesis":[73],"attack":[75,213],"against":[76],"models,":[80],"which":[81,183],"embeds":[82],"latent":[87],"space.":[88],"We":[89],"study":[90,274],"vulnerability":[93],"from":[94,140,271],"two":[95],"perspectives:":[96],"(1)":[97,206],"Model":[98],"Discrimination":[99],"(Optimization-Based":[100],"Trigger)":[101],":":[102,210,241,267],"adopt":[104],"substitute":[106],"find":[110],"trigger":[112,163],"minimizing":[114],"cross-entropy":[116],"loss;":[117],"(2)":[118,238],"Data":[119],"Distribution":[120],"(Custom":[121],"Trigger):":[122],"manipulate":[124],"uncommon":[126],"facial":[127],"attributes":[128],"long-tailed":[131],"distribution":[132],"generate":[134],"poisoned":[135,176],"samples":[136,177],"without":[137],"supervision":[139],"models.":[142],"Furthermore,":[143],"evaluate":[145],"models":[148],"toward":[149],"latest":[151],"AIGC,":[152],"utilize":[154],"both":[155],"state-of-the-art":[157],"StyleGAN":[158],"Stable":[160],"Diffusion":[161],"for":[162],"generation.":[164],"Finally,":[165],"these":[166],"introduce":[169],"specific":[170],"semantic":[171],"features":[172],"generated":[175],"(e.g.,":[178,251],"skin":[179],"textures":[180],"smile),":[182],"robust.":[188],"Extensive":[189],"experiments":[190],"show":[191],"that":[192],"our":[193],"method":[194],"superior":[196,243],"over":[197,256],"pixel":[199],"space":[200],"attacks":[202],"on":[203],"three":[204],"levels:":[205],"Attack":[207],"Success":[208],"Rate":[209],"achieving":[211],"an":[212],"success":[214],"rate":[215],"exceeding":[216],"99":[217],"\\(\\%\\)":[218,228,235,258],",":[219],"comparable":[220],"baseline":[222,253],"methods,":[223],"with":[224,247,275],"less":[225,269],"than":[226],"0.1":[227],"accuracy":[230],"drop":[231],"under":[233],"3":[234],"poisoning":[236],"rate;":[237],"Backdoor":[239],"Defense":[240],"showing":[242],"robustness":[244],"when":[245],"faced":[246],"surpassing":[252],"methods":[254],"30":[257],"after":[259],"15":[261],"\\({}^{\\circ}\\)":[262],"rotation);":[263],"(3)":[264],"Human":[265],"Inspection":[266],"being":[268],"user":[273],"46":[276],"participants":[277],"collection":[280],"2,300":[282],"points.":[284]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1}],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2025-10-10T00:00:00"}
