{"id":"https://openalex.org/W7167711363","doi":"https://doi.org/10.48550/arxiv.2607.05996","title":"Unlearnable Faces: Privacy Protection Surviving Extraction Pipeline","display_name":"Unlearnable Faces: Privacy Protection Surviving Extraction Pipeline","publication_year":2026,"publication_date":"2026-07-07","ids":{"openalex":"https://openalex.org/W7167711363","doi":"https://doi.org/10.48550/arxiv.2607.05996"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2607.05996","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.05996","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","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.2607.05996","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5121526875","display_name":"Byunghoon Oh","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Oh, Byunghoon","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5140297760","display_name":"Sunghwan Park","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Park, Sunghwan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5140265731","display_name":"Jaewoo Lee","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lee, Jaewoo","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/T11448","display_name":"Face recognition and analysis","score":0.7439000010490417,"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":0.7439000010490417,"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/T10828","display_name":"Biometric Identification and Security","score":0.10840000212192535,"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"}},{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.03689999878406525,"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/robustness","display_name":"Robustness (evolution)","score":0.7290999889373779},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5141000151634216},{"id":"https://openalex.org/keywords/privacy-protection","display_name":"Privacy protection","score":0.40560001134872437},{"id":"https://openalex.org/keywords/train","display_name":"Train","score":0.3849000036716461},{"id":"https://openalex.org/keywords/differentiable-function","display_name":"Differentiable function","score":0.38260000944137573},{"id":"https://openalex.org/keywords/facial-recognition-system","display_name":"Facial recognition system","score":0.3815999925136566},{"id":"https://openalex.org/keywords/face","display_name":"Face (sociological concept)","score":0.3582000136375427}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7379999756813049},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.7290999889373779},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5141000151634216},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.43309998512268066},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.41609999537467957},{"id":"https://openalex.org/C3017597292","wikidata":"https://www.wikidata.org/wiki/Q25052250","display_name":"Privacy protection","level":2,"score":0.40560001134872437},{"id":"https://openalex.org/C190839683","wikidata":"https://www.wikidata.org/wiki/Q2448197","display_name":"Train","level":2,"score":0.3849000036716461},{"id":"https://openalex.org/C202615002","wikidata":"https://www.wikidata.org/wiki/Q783507","display_name":"Differentiable function","level":2,"score":0.38260000944137573},{"id":"https://openalex.org/C31510193","wikidata":"https://www.wikidata.org/wiki/Q1192553","display_name":"Facial recognition system","level":3,"score":0.3815999925136566},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.3582000136375427},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.30730000138282776},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.30230000615119934},{"id":"https://openalex.org/C189950617","wikidata":"https://www.wikidata.org/wiki/Q937228","display_name":"Property (philosophy)","level":2,"score":0.3000999987125397},{"id":"https://openalex.org/C77714075","wikidata":"https://www.wikidata.org/wiki/Q5452017","display_name":"Firewall (physics)","level":5,"score":0.2847999930381775},{"id":"https://openalex.org/C4641261","wikidata":"https://www.wikidata.org/wiki/Q11681085","display_name":"Face detection","level":4,"score":0.2694000005722046},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.26429998874664307},{"id":"https://openalex.org/C4725764","wikidata":"https://www.wikidata.org/wiki/Q844704","display_name":"Extraction (chemistry)","level":2,"score":0.263700008392334},{"id":"https://openalex.org/C123201435","wikidata":"https://www.wikidata.org/wiki/Q456632","display_name":"Information privacy","level":2,"score":0.25920000672340393}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2607.05996","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.05996","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2607.05996","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.05996","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Unlearnable":[0],"examples":[1],"keep":[2],"publicly":[3],"shared":[4,37],"photos":[5,26],"from":[6],"being":[7],"learned":[8],"by":[9],"unauthorized":[10],"face-recognition":[11],"models.":[12],"An":[13],"imperceptible":[14,159],"perturbation,":[15],"added":[16],"before":[17],"sharing,":[18],"makes":[19],"any":[20,114],"model":[21,88],"trained":[22],"on":[23,28,35,43,151],"the":[24,36,40,44,52,59,67,70,75,78,90,96,99,109,131,144],"protected":[25],"fail":[27],"clean":[29],"faces.":[30],"The":[31],"perturbation":[32,76],"is":[33,105,117],"crafted":[34],"image,":[38],"however":[39],"attacker":[41,133,145],"trains":[42],"face":[45,80],"it":[46,84,125],"extracts,":[47],"cropped":[48],"and":[49,55,82,121,163],"resized":[50],"to":[51,77],"recognizer":[53],"input,":[54],"under":[56,148],"this":[57,103],"extraction":[58,68,100,150],"protection":[60,155],"collapses.":[61],"We":[62],"propose":[63],"LPID,":[64],"which":[65],"builds":[66],"into":[69],"unlearnable-example":[71],"objective.":[72],"LPID":[73,116,129],"confines":[74],"extracted":[79],"region":[81],"optimizes":[83],"through":[85],"a":[86,106],"differentiable":[87],"of":[89,108,113,135],"extraction,":[91],"concentrating":[92],"its":[93],"energy":[94],"in":[95,138],"frequency":[97],"band":[98],"preserves.":[101],"Because":[102],"robustness":[104],"property":[107],"transform":[110],"rather":[111],"than":[112],"identity,":[115],"re-optimized":[118],"per":[119],"album":[120],"protects":[122],"even":[123],"users":[124],"has":[126],"never":[127],"seen.":[128],"attains":[130],"lowest":[132],"accuracy":[134],"all":[136],"methods":[137],"every":[139],"setting":[140],"we":[141],"evaluate,":[142],"holding":[143],"below":[146],"$10\\%$":[147],"crop+resize":[149],"identities":[152],"unseen":[153],"at":[154,160],"time,":[156],"while":[157],"remaining":[158],"$32.7$\\,dB":[161],"PSNR":[162],"$0.161$":[164],"LPIPS.":[165]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-07-09T00:00:00"}
