{"id":"https://openalex.org/W7164422440","doi":"https://doi.org/10.48550/arxiv.2606.12263","title":"VOID: Defeating Unauthorized Mimicry in Latent Diffusion Models","display_name":"VOID: Defeating Unauthorized Mimicry in Latent Diffusion Models","publication_year":2026,"publication_date":"2026-06-10","ids":{"openalex":"https://openalex.org/W7164422440","doi":"https://doi.org/10.48550/arxiv.2606.12263"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.12263","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.12263","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2606.12263","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5108624372","display_name":"Chunlin Qiu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Qiu, Chunlin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138469041","display_name":"Ang Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Ang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138397222","display_name":"Tianxiao Huang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Huang, Tianxiao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138481650","display_name":"Ruilin Gan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gan, Ruilin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138406903","display_name":"Yunjie Ge","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ge, Yunjie","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138415896","display_name":"Shenyi Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Shenyi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043471850","display_name":"Huayi Duan","orcid":"https://orcid.org/0000-0002-1162-2337"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Duan, Huayi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138460653","display_name":"Lingchen Zhao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhao, Lingchen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138435823","display_name":"Chao Shen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shen, Chao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5138479927","display_name":"Qian Wang (32718)","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Qian","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.8026999831199646,"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":0.8026999831199646,"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":0.12729999423027039,"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/T11448","display_name":"Face recognition and analysis","score":0.016300000250339508,"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/mimicry","display_name":"Mimicry","score":0.8392999768257141},{"id":"https://openalex.org/keywords/encoding","display_name":"Encoding (memory)","score":0.3619000017642975},{"id":"https://openalex.org/keywords/mechanism","display_name":"Mechanism (biology)","score":0.31060001254081726},{"id":"https://openalex.org/keywords/visualization","display_name":"Visualization","score":0.26330000162124634},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.24799999594688416}],"concepts":[{"id":"https://openalex.org/C7863114","wikidata":"https://www.wikidata.org/wiki/Q192627","display_name":"Mimicry","level":2,"score":0.8392999768257141},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6223000288009644},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.44350001215934753},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.3619000017642975},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.31520000100135803},{"id":"https://openalex.org/C89611455","wikidata":"https://www.wikidata.org/wiki/Q6804646","display_name":"Mechanism (biology)","level":2,"score":0.31060001254081726},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.27649998664855957},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.26330000162124634},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.24799999594688416},{"id":"https://openalex.org/C2779772531","wikidata":"https://www.wikidata.org/wiki/Q19689164","display_name":"Void (composites)","level":2,"score":0.22609999775886536}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.12263","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.12263","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2606.12263","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.12263","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","score":0.8004422783851624,"id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"While":[0],"Latent":[1],"Diffusion":[2],"Models":[3],"(LDMs)":[4],"have":[5],"revolutionized":[6],"visual":[7,145],"synthesis,":[8],"they":[9],"are":[10],"increasingly":[11],"exploited":[12],"for":[13],"unauthorized":[14,132],"mimicry":[15,169],"of":[16,144,157,163],"individuals.":[17],"Existing":[18],"defenses":[19,166],"inject":[20],"deceptive":[21,44],"perturbations":[22,40,62,153],"to":[23,67,104,117,151,154,189,198],"steer":[24],"the":[25,54,70,91,100,113,119,135,142,181,195],"generated":[26],"images":[27,71],"toward":[28],"irrelevant":[29],"targets.":[30],"However,":[31],"this":[32,81],"approach":[33],"hinges":[34],"on":[35,171],"an":[36,47,85,106],"ungrounded":[37],"assumption:":[38],"subtle":[39],"can":[41],"maintain":[42],"their":[43],"efficacy":[45],"throughout":[46],"LDM's":[48,86],"extensive":[49],"generation":[50],"process.":[51],"In":[52],"reality,":[53],"model's":[55,120],"innate":[56],"restoration":[57,121],"mechanism":[58],"will":[59],"remove":[60],"such":[61],"and":[63,110],"cause":[64],"individual":[65],"identities":[66],"re-emerge":[68],"in":[69,94,125],"generated.":[72],"We":[73],"propose":[74],"VOID,":[75],"a":[76,126,191],"defense":[77,197],"framework":[78],"that":[79,129],"overcomes":[80],"conundrum":[82],"by":[83],"manipulating":[84],"intrinsic":[87],"stochasticity.":[88],"VOID":[89,148],"perturbs":[90],"diffusion":[92],"pipeline":[93],"two":[95],"novel":[96],"ways:":[97],"1)":[98],"amplifying":[99],"latent":[101],"encoding":[102],"errors":[103],"shatter":[105],"image's":[107],"semantic":[108,127],"structure,":[109],"2)":[111],"counteracting":[112],"target":[114],"guidance":[115],"signals":[116],"suppress":[118],"capabilities.":[122],"This":[123],"results":[124],"corruption":[128],"thwarts":[130],"any":[131],"mimicry.":[133],"Notably,":[134],"security":[136],"gain":[137],"does":[138],"not":[139],"come":[140],"at":[141],"price":[143],"utility,":[146],"as":[147],"simultaneously":[149],"manages":[150],"confine":[152],"human-imperceptible":[155],"regions":[156],"protected":[158],"images.":[159],"Our":[160],"comprehensive":[161],"evaluation":[162],"24":[164],"state-of-the-art":[165],"against":[167],"10":[168],"attacks":[170],"5":[172],"datasets":[173],"demonstrates":[174],"VOID's":[175],"unprecedented":[176],"protection":[177],"power:":[178],"it":[179],"increases":[180],"average":[182],"Frechet":[183],"Inception":[184],"Distance":[185],"(FID)":[186],"from":[187],"113":[188],"365,":[190],"223%":[192],"improvement":[193],"over":[194],"strongest":[196],"date.":[199]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-06-12T00:00:00"}
