{"id":"https://openalex.org/W4405181141","doi":"https://doi.org/10.1145/3658644.3670306","title":"Organic or Diffused: Can We Distinguish Human Art from AI-generated Images?","display_name":"Organic or Diffused: Can We Distinguish Human Art from AI-generated Images?","publication_year":2024,"publication_date":"2024-12-02","ids":{"openalex":"https://openalex.org/W4405181141","doi":"https://doi.org/10.1145/3658644.3670306"},"language":"en","primary_location":{"id":"doi:10.1145/3658644.3670306","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3658644.3670306","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3658644.3670306","source":null,"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2024 on ACM SIGSAC Conference on Computer and Communications Security","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3658644.3670306","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5093876076","display_name":"Anna Yoo Jeong Ha","orcid":"https://orcid.org/0009-0008-5551-7847"},"institutions":[{"id":"https://openalex.org/I39422238","display_name":"University of Illinois Chicago","ror":"https://ror.org/02mpq6x41","country_code":"US","type":"education","lineage":["https://openalex.org/I39422238"]},{"id":"https://openalex.org/I40347166","display_name":"University of Chicago","ror":"https://ror.org/024mw5h28","country_code":"US","type":"education","lineage":["https://openalex.org/I40347166"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Anna Yoo Jeong Ha","raw_affiliation_strings":["University of Chicago, Chicago, IL, USA"],"affiliations":[{"raw_affiliation_string":"University of Chicago, Chicago, IL, USA","institution_ids":["https://openalex.org/I40347166","https://openalex.org/I39422238"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006517171","display_name":"Josephine Passananti","orcid":"https://orcid.org/0000-0002-5705-8209"},"institutions":[{"id":"https://openalex.org/I39422238","display_name":"University of Illinois Chicago","ror":"https://ror.org/02mpq6x41","country_code":"US","type":"education","lineage":["https://openalex.org/I39422238"]},{"id":"https://openalex.org/I40347166","display_name":"University of Chicago","ror":"https://ror.org/024mw5h28","country_code":"US","type":"education","lineage":["https://openalex.org/I40347166"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Josephine Passananti","raw_affiliation_strings":["University of Chicago, Chicago, IL, USA"],"affiliations":[{"raw_affiliation_string":"University of Chicago, Chicago, IL, USA","institution_ids":["https://openalex.org/I40347166","https://openalex.org/I39422238"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061419124","display_name":"Ronik Bhaskar","orcid":"https://orcid.org/0009-0002-7524-9292"},"institutions":[{"id":"https://openalex.org/I39422238","display_name":"University of Illinois Chicago","ror":"https://ror.org/02mpq6x41","country_code":"US","type":"education","lineage":["https://openalex.org/I39422238"]},{"id":"https://openalex.org/I40347166","display_name":"University of Chicago","ror":"https://ror.org/024mw5h28","country_code":"US","type":"education","lineage":["https://openalex.org/I40347166"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ronik Bhaskar","raw_affiliation_strings":["University of Chicago, Chicago, IL, USA"],"affiliations":[{"raw_affiliation_string":"University of Chicago, Chicago, IL, USA","institution_ids":["https://openalex.org/I40347166","https://openalex.org/I39422238"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076606321","display_name":"Shawn Shan","orcid":"https://orcid.org/0009-0005-4324-7817"},"institutions":[{"id":"https://openalex.org/I39422238","display_name":"University of Illinois Chicago","ror":"https://ror.org/02mpq6x41","country_code":"US","type":"education","lineage":["https://openalex.org/I39422238"]},{"id":"https://openalex.org/I40347166","display_name":"University of Chicago","ror":"https://ror.org/024mw5h28","country_code":"US","type":"education","lineage":["https://openalex.org/I40347166"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shawn Shan","raw_affiliation_strings":["University of Chicago, Chicago, IL, USA"],"affiliations":[{"raw_affiliation_string":"University of Chicago, Chicago, IL, USA","institution_ids":["https://openalex.org/I40347166","https://openalex.org/I39422238"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5093876077","display_name":"Reid Southen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Reid Southen","raw_affiliation_strings":["Concept Artist, Detroit, MI, USA"],"affiliations":[{"raw_affiliation_string":"Concept Artist, Detroit, MI, USA","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5111456411","display_name":"Haitao Zheng","orcid":"https://orcid.org/0000-0002-5918-2940"},"institutions":[{"id":"https://openalex.org/I39422238","display_name":"University of Illinois Chicago","ror":"https://ror.org/02mpq6x41","country_code":"US","type":"education","lineage":["https://openalex.org/I39422238"]},{"id":"https://openalex.org/I40347166","display_name":"University of Chicago","ror":"https://ror.org/024mw5h28","country_code":"US","type":"education","lineage":["https://openalex.org/I40347166"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Haitao Zheng","raw_affiliation_strings":["University of Chicago, Chicago, IL, USA"],"affiliations":[{"raw_affiliation_string":"University of Chicago, Chicago, IL, USA","institution_ids":["https://openalex.org/I40347166","https://openalex.org/I39422238"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5108248360","display_name":"Ben Y. Zhao","orcid":"https://orcid.org/0009-0003-8909-0494"},"institutions":[{"id":"https://openalex.org/I39422238","display_name":"University of Illinois Chicago","ror":"https://ror.org/02mpq6x41","country_code":"US","type":"education","lineage":["https://openalex.org/I39422238"]},{"id":"https://openalex.org/I40347166","display_name":"University of Chicago","ror":"https://ror.org/024mw5h28","country_code":"US","type":"education","lineage":["https://openalex.org/I40347166"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ben Y. Zhao","raw_affiliation_strings":["University of Chicago, Chicago, IL, USA"],"affiliations":[{"raw_affiliation_string":"University of Chicago, Chicago, IL, USA","institution_ids":["https://openalex.org/I40347166","https://openalex.org/I39422238"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5093876076"],"corresponding_institution_ids":["https://openalex.org/I39422238","https://openalex.org/I40347166"],"apc_list":null,"apc_paid":null,"fwci":4.2378,"has_fulltext":false,"cited_by_count":17,"citation_normalized_percentile":{"value":0.95438867,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"4822","last_page":"4836"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.9994999766349792,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.9994999766349792,"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/T12650","display_name":"Aesthetic Perception and Analysis","score":0.9969000220298767,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10481","display_name":"Computer Graphics and Visualization Techniques","score":0.9666000008583069,"subfield":{"id":"https://openalex.org/subfields/1704","display_name":"Computer Graphics and Computer-Aided Design"},"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/computer-science","display_name":"Computer science","score":0.7073221802711487},{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.6844226121902466},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.662063717842102},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.622941255569458},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6206779479980469},{"id":"https://openalex.org/keywords/generative-adversarial-network","display_name":"Generative adversarial network","score":0.46479031443595886},{"id":"https://openalex.org/keywords/false-positive-paradox","display_name":"False positive paradox","score":0.46275565028190613},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.44288474321365356},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.43131914734840393},{"id":"https://openalex.org/keywords/generative-model","display_name":"Generative model","score":0.42408961057662964},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3740147352218628},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.3397148847579956}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7073221802711487},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.6844226121902466},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.662063717842102},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.622941255569458},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6206779479980469},{"id":"https://openalex.org/C2988773926","wikidata":"https://www.wikidata.org/wiki/Q25104379","display_name":"Generative adversarial network","level":3,"score":0.46479031443595886},{"id":"https://openalex.org/C64869954","wikidata":"https://www.wikidata.org/wiki/Q1859747","display_name":"False positive paradox","level":2,"score":0.46275565028190613},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.44288474321365356},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.43131914734840393},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.42408961057662964},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3740147352218628},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.3397148847579956},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","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/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/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3658644.3670306","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3658644.3670306","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3658644.3670306","source":null,"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2024 on ACM SIGSAC Conference on Computer and Communications Security","raw_type":"proceedings-article"},{"id":"pmh:oai:uchicago.tind.io:14241","is_oa":false,"landing_page_url":"http://knowledge.uchicago.edu/record/14241","pdf_url":null,"source":{"id":"https://openalex.org/S4306402460","display_name":"Knowledge@UChicago (University of Chicago)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I40347166","host_organization_name":"University of Chicago","host_organization_lineage":["https://openalex.org/I40347166"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://knowledge.uchicago.edu/record/14241","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.1145/3658644.3670306","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3658644.3670306","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3658644.3670306","source":null,"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2024 on ACM SIGSAC Conference on Computer and Communications Security","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4405181141.pdf"},"referenced_works_count":8,"referenced_works":["https://openalex.org/W1996845962","https://openalex.org/W2150566941","https://openalex.org/W2769536523","https://openalex.org/W3034577585","https://openalex.org/W3035574324","https://openalex.org/W3118608800","https://openalex.org/W4388858946","https://openalex.org/W4389370799"],"related_works":["https://openalex.org/W4365211920","https://openalex.org/W3014948380","https://openalex.org/W4391584540","https://openalex.org/W2888032422","https://openalex.org/W4380551139","https://openalex.org/W4317695495","https://openalex.org/W4395044357","https://openalex.org/W2996316059","https://openalex.org/W4287117424","https://openalex.org/W4387506531"],"abstract_inverted_index":{"The":[0],"advent":[1],"of":[2,112,218,227],"generative":[3,131,152],"AI":[4,13,53,91],"images":[5,15,149],"has":[6],"completely":[7],"disrupted":[8],"the":[9,224],"art":[10,18,46,89,143],"world.":[11],"Distinguishing":[12],"generated":[14],"from":[16,90,150],"human":[17,45,88,142,164,219],"is":[19,25,56,195],"a":[20,42,216],"challenging":[21],"problem":[22,34],"whose":[23,49],"impact":[24],"growing":[26],"over":[27],"time.":[28],"A":[29],"failure":[30],"to":[31,38,62,76,86,120],"address":[32],"this":[33,116],"allows":[35],"bad":[36],"actors":[37],"defraud":[39],"individuals":[40],"paying":[41],"premium":[43],"for":[44,59,66],"and":[47,65,104,136,154,161,172,182,213,220,229],"companies":[48],"stated":[50],"policies":[51],"forbid":[52],"imagery.":[54],"It":[55],"also":[57],"critical":[58],"content":[60],"owners":[61],"establish":[63],"copyright,":[64],"model":[67,79],"trainers":[68],"interested":[69],"in":[70,74,133,191],"curating":[71],"training":[72],"data":[73],"order":[75],"avoid":[77],"potential":[78],"collapse.":[80],"There":[81],"are":[82],"several":[83],"different":[84,163,192],"approaches":[85,125],"distinguishing":[87],"images,":[92],"including":[93,166],"classifiers":[94],"trained":[95],"by":[96,106],"supervised":[97],"learning,":[98],"research":[99],"tools":[100],"targeting":[101],"diffusion":[102],"models,":[103,153],"identification":[105],"professional":[107,170],"artists":[108,175,184,202],"using":[109],"their":[110],"knowledge":[111],"artistic":[113],"techniques.":[114],"In":[115],"paper,":[117],"we":[118],"seek":[119],"understand":[121],"how":[122],"well":[123],"these":[124,209],"can":[126],"perform":[127],"against":[128,197],"today's":[129],"modern":[130],"models":[132],"both":[134],"benign":[135],"adversarial":[137,198],"settings.":[138],"We":[139,207],"curate":[140],"real":[141],"across":[144],"7":[145],"styles,":[146],"generate":[147],"matching":[148],"5":[151],"apply":[155],"8":[156],"detectors":[157,160,222],"(5":[158],"automated":[159,221],"3":[162],"groups":[165],"180":[167],"crowdworkers,":[168],"3800+":[169],"artists,":[171],"13":[173],"expert":[174,183],"experienced":[176],"at":[177],"detecting":[178],"AI).":[179],"Both":[180],"Hive":[181],"do":[185],"very":[186],"well,":[187],"but":[188],"make":[189],"mistakes":[190],"ways":[193],"(Hive":[194],"weaker":[196],"perturbations":[199],"while":[200],"Expert":[201],"produce":[203],"higher":[204],"false":[205],"positives).":[206],"believe":[208],"weaknesses":[210],"will":[211],"persist,":[212],"argue":[214],"that":[215],"combination":[217,226],"provides":[223],"best":[225],"accuracy":[228],"robustness.":[230]},"counts_by_year":[{"year":2025,"cited_by_count":14},{"year":2024,"cited_by_count":3}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
