{"id":"https://openalex.org/W4229336043","doi":"https://doi.org/10.1145/3531146.3533128","title":"Subverting Fair Image Search with Generative Adversarial Perturbations","display_name":"Subverting Fair Image Search with Generative Adversarial Perturbations","publication_year":2022,"publication_date":"2022-06-20","ids":{"openalex":"https://openalex.org/W4229336043","doi":"https://doi.org/10.1145/3531146.3533128"},"language":"en","primary_location":{"id":"doi:10.1145/3531146.3533128","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3531146.3533128","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3531146.3533128","source":{"id":"https://openalex.org/S4363608463","display_name":"2022 ACM Conference on Fairness, Accountability, and Transparency","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 ACM Conference on Fairness Accountability and Transparency","raw_type":"proceedings-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3531146.3533128","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101463080","display_name":"Avijit Ghosh","orcid":"https://orcid.org/0000-0002-8540-3698"},"institutions":[{"id":"https://openalex.org/I12912129","display_name":"Northeastern University","ror":"https://ror.org/04t5xt781","country_code":"US","type":"education","lineage":["https://openalex.org/I12912129"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Avijit Ghosh","raw_affiliation_strings":["Khoury College of Computer Sciences, Northeastern University, USA"],"affiliations":[{"raw_affiliation_string":"Khoury College of Computer Sciences, Northeastern University, USA","institution_ids":["https://openalex.org/I12912129"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054655342","display_name":"Matthew Jagielski","orcid":"https://orcid.org/0000-0002-9749-0696"},"institutions":[{"id":"https://openalex.org/I1291425158","display_name":"Google (United States)","ror":"https://ror.org/00njsd438","country_code":"US","type":"company","lineage":["https://openalex.org/I1291425158","https://openalex.org/I4210128969"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Matthew Jagielski","raw_affiliation_strings":["Google Brain, USA"],"affiliations":[{"raw_affiliation_string":"Google Brain, USA","institution_ids":["https://openalex.org/I1291425158"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5072703507","display_name":"Christo Wilson","orcid":"https://orcid.org/0000-0002-5268-004X"},"institutions":[{"id":"https://openalex.org/I12912129","display_name":"Northeastern University","ror":"https://ror.org/04t5xt781","country_code":"US","type":"education","lineage":["https://openalex.org/I12912129"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Christo Wilson","raw_affiliation_strings":["Khoury College of Computer Sciences, Northeastern University, USA"],"affiliations":[{"raw_affiliation_string":"Khoury College of Computer Sciences, Northeastern University, USA","institution_ids":["https://openalex.org/I12912129"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5101463080"],"corresponding_institution_ids":["https://openalex.org/I12912129"],"apc_list":null,"apc_paid":null,"fwci":0.9392,"has_fulltext":true,"cited_by_count":9,"citation_normalized_percentile":{"value":0.75961844,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"637","last_page":"650"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9962999820709229,"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":0.9962999820709229,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9671000242233276,"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/T10883","display_name":"Ethics and Social Impacts of AI","score":0.9528999924659729,"subfield":{"id":"https://openalex.org/subfields/3311","display_name":"Safety Research"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.8474708795547485},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.718058705329895},{"id":"https://openalex.org/keywords/adversary","display_name":"Adversary","score":0.7093727588653564},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6973072290420532},{"id":"https://openalex.org/keywords/ranking","display_name":"Ranking (information retrieval)","score":0.6233352422714233},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.5288541913032532},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.5229631066322327},{"id":"https://openalex.org/keywords/rank","display_name":"Rank (graph theory)","score":0.456781268119812},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4331769645214081},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.4280659854412079},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.40548208355903625},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.20728886127471924},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.16630062460899353}],"concepts":[{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.8474708795547485},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.718058705329895},{"id":"https://openalex.org/C41065033","wikidata":"https://www.wikidata.org/wiki/Q2825412","display_name":"Adversary","level":2,"score":0.7093727588653564},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6973072290420532},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.6233352422714233},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.5288541913032532},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.5229631066322327},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.456781268119812},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4331769645214081},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.4280659854412079},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.40548208355903625},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.20728886127471924},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.16630062460899353},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"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/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3531146.3533128","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3531146.3533128","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3531146.3533128","source":{"id":"https://openalex.org/S4363608463","display_name":"2022 ACM Conference on Fairness, Accountability, and Transparency","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 ACM Conference on Fairness Accountability and Transparency","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2205.02414","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2205.02414","pdf_url":"https://arxiv.org/pdf/2205.02414","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"doi:10.1145/3531146.3533128","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3531146.3533128","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3531146.3533128","source":{"id":"https://openalex.org/S4363608463","display_name":"2022 ACM Conference on Fairness, Accountability, and Transparency","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 ACM Conference on Fairness Accountability and Transparency","raw_type":"proceedings-article"},"sustainable_development_goals":[{"score":0.5600000023841858,"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions"}],"awards":[{"id":"https://openalex.org/G3335104637","display_name":null,"funder_award_id":"IIS-1553088","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G4214760960","display_name":"CAREER: Towards Methodologies and Tools for Conducting Algorithm Audits","funder_award_id":"1553088","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G5341829433","display_name":null,"funder_award_id":"IIS-1910064 and IIS-1553088","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G6249844146","display_name":"CHS: Small: Auditing Critical Dependencies Between Online Media Platforms","funder_award_id":"1910064","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G6894402473","display_name":null,"funder_award_id":"Fellowship","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4229336043.pdf","grobid_xml":"https://content.openalex.org/works/W4229336043.grobid-xml"},"referenced_works_count":107,"referenced_works":["https://openalex.org/W111324831","https://openalex.org/W639708223","https://openalex.org/W1673923490","https://openalex.org/W1731081199","https://openalex.org/W1806853995","https://openalex.org/W1819662813","https://openalex.org/W1861492603","https://openalex.org/W1945616565","https://openalex.org/W1961345416","https://openalex.org/W2025824923","https://openalex.org/W2069870183","https://openalex.org/W2097117768","https://openalex.org/W2099774288","https://openalex.org/W2145287260","https://openalex.org/W2194775991","https://openalex.org/W2243397390","https://openalex.org/W2543927648","https://openalex.org/W2570685808","https://openalex.org/W2612637113","https://openalex.org/W2622808887","https://openalex.org/W2704480242","https://openalex.org/W2769358515","https://openalex.org/W2787991113","https://openalex.org/W2788284633","https://openalex.org/W2788481061","https://openalex.org/W2790025105","https://openalex.org/W2798868970","https://openalex.org/W2804197927","https://openalex.org/W2810611310","https://openalex.org/W2886189420","https://openalex.org/W2898081668","https://openalex.org/W2912638141","https://openalex.org/W2914147668","https://openalex.org/W2915934162","https://openalex.org/W2916360674","https://openalex.org/W2917779306","https://openalex.org/W2936687512","https://openalex.org/W2946280906","https://openalex.org/W2950018712","https://openalex.org/W2950104108","https://openalex.org/W2950173087","https://openalex.org/W2962977061","https://openalex.org/W2963143631","https://openalex.org/W2963184668","https://openalex.org/W2963189767","https://openalex.org/W2963389226","https://openalex.org/W2963855547","https://openalex.org/W2963857521","https://openalex.org/W2964183365","https://openalex.org/W2964247748","https://openalex.org/W2964283260","https://openalex.org/W2966715458","https://openalex.org/W2974817986","https://openalex.org/W2984942115","https://openalex.org/W2986074609","https://openalex.org/W2995363645","https://openalex.org/W2997335426","https://openalex.org/W3001807593","https://openalex.org/W3012903288","https://openalex.org/W3028722847","https://openalex.org/W3029264758","https://openalex.org/W3033211022","https://openalex.org/W3035729345","https://openalex.org/W3035765133","https://openalex.org/W3046957164","https://openalex.org/W3048991518","https://openalex.org/W3082511295","https://openalex.org/W3091588028","https://openalex.org/W3094231124","https://openalex.org/W3094984771","https://openalex.org/W3102092462","https://openalex.org/W3102518922","https://openalex.org/W3103340107","https://openalex.org/W3103891807","https://openalex.org/W3105035347","https://openalex.org/W3106489865","https://openalex.org/W3109275961","https://openalex.org/W3109496323","https://openalex.org/W3120485916","https://openalex.org/W3133759846","https://openalex.org/W3134501548","https://openalex.org/W3134548480","https://openalex.org/W3135773605","https://openalex.org/W3138773240","https://openalex.org/W3139017368","https://openalex.org/W3154833091","https://openalex.org/W3158897490","https://openalex.org/W3162205072","https://openalex.org/W3172872502","https://openalex.org/W3172963091","https://openalex.org/W3174380182","https://openalex.org/W3214399478","https://openalex.org/W4205941772","https://openalex.org/W4210631930","https://openalex.org/W4211047985","https://openalex.org/W4211122380","https://openalex.org/W4224988721","https://openalex.org/W4287121648","https://openalex.org/W4287393742","https://openalex.org/W4287753323","https://openalex.org/W4288083799","https://openalex.org/W4288363925","https://openalex.org/W4294241863","https://openalex.org/W4294517337","https://openalex.org/W4298140072","https://openalex.org/W4298377035","https://openalex.org/W6638208828"],"related_works":["https://openalex.org/W2502115930","https://openalex.org/W2482350142","https://openalex.org/W4246396837","https://openalex.org/W4320018150","https://openalex.org/W4239582170","https://openalex.org/W2918664383","https://openalex.org/W106056076","https://openalex.org/W4320855730","https://openalex.org/W2135200719","https://openalex.org/W3160516639"],"abstract_inverted_index":{"In":[0],"this":[1,53],"work":[2],"we":[3,55,62],"explore":[4],"the":[5,11,37,46,93,100],"intersection":[6],"fairness":[7],"and":[8,64],"robustness":[9],"in":[10,60],"context":[12],"of":[13,26,102],"ranking:":[14],"when":[15],"a":[16,57,67,81],"ranking":[17,38],"model":[18,39,47,86],"has":[19],"been":[20,77],"calibrated":[21],"to":[22,35,45,91,97],"achieve":[23],"some":[24],"definition":[25],"fairness,":[27],"is":[28],"it":[29],"possible":[30],"for":[31],"an":[32,107],"external":[33],"adversary":[34],"make":[36],"behave":[40],"unfairly":[41,98],"without":[42],"having":[43],"access":[44],"or":[48],"training":[49],"data?":[50],"To":[51],"investigate":[52],"question,":[54],"present":[56],"case":[58],"study":[59],"which":[61],"develop":[63],"then":[65],"attack":[66],"state-of-the-art,":[68],"fairness-aware":[69],"image":[70],"search":[71],"engine":[72],"using":[73,80],"images":[74,103],"that":[75],"have":[76],"maliciously":[78],"modified":[79],"Generative":[82],"Adversarial":[83],"Perturbation":[84],"(GAP)":[85],"[75].":[87],"These":[88],"perturbations":[89],"attempt":[90],"cause":[92],"fair":[94],"re-ranking":[95],"algorithm":[96],"boost":[99],"rank":[101],"containing":[104],"people":[105],"from":[106],"adversary-selected":[108],"subpopulation.":[109]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":3}],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2025-10-10T00:00:00"}