{"id":"https://openalex.org/W4415157406","doi":"https://doi.org/10.1145/3746027.3754544","title":"FractalForensics: Proactive Deepfake Detection and Localization via Fractal Watermarks","display_name":"FractalForensics: Proactive Deepfake Detection and Localization via Fractal Watermarks","publication_year":2025,"publication_date":"2025-10-25","ids":{"openalex":"https://openalex.org/W4415157406","doi":"https://doi.org/10.1145/3746027.3754544"},"language":"en","primary_location":{"id":"doi:10.1145/3746027.3754544","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3746027.3754544","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 33rd ACM International Conference on Multimedia","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1145/3746027.3754544","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100399645","display_name":"Tianyi Wang","orcid":"https://orcid.org/0000-0003-2920-6099"},"institutions":[{"id":"https://openalex.org/I165932596","display_name":"National University of Singapore","ror":"https://ror.org/01tgyzw49","country_code":"SG","type":"education","lineage":["https://openalex.org/I165932596"]}],"countries":["SG"],"is_corresponding":true,"raw_author_name":"Tianyi Wang","raw_affiliation_strings":["National University of Singapore, Singapore, Singapore"],"raw_orcid":"https://orcid.org/0000-0003-2920-6099","affiliations":[{"raw_affiliation_string":"National University of Singapore, Singapore, Singapore","institution_ids":["https://openalex.org/I165932596"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059602960","display_name":"Harry H. Cheng","orcid":"https://orcid.org/0000-0001-7436-0162"},"institutions":[{"id":"https://openalex.org/I165932596","display_name":"National University of Singapore","ror":"https://ror.org/01tgyzw49","country_code":"SG","type":"education","lineage":["https://openalex.org/I165932596"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Harry Cheng","raw_affiliation_strings":["National University of Singapore, Singapore, Singapore"],"raw_orcid":"https://orcid.org/0000-0001-7436-0162","affiliations":[{"raw_affiliation_string":"National University of Singapore, Singapore, Singapore","institution_ids":["https://openalex.org/I165932596"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100358119","display_name":"Minghui Liu","orcid":"https://orcid.org/0000-0001-7242-5452"},"institutions":[{"id":"https://openalex.org/I154099455","display_name":"Shandong University","ror":"https://ror.org/0207yh398","country_code":"CN","type":"education","lineage":["https://openalex.org/I154099455"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ming-Hui Liu","raw_affiliation_strings":["Shandong University, Jinan, Shandong, China"],"raw_orcid":"https://orcid.org/0000-0001-7242-5452","affiliations":[{"raw_affiliation_string":"Shandong University, Jinan, Shandong, China","institution_ids":["https://openalex.org/I154099455"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5016415049","display_name":"Mohan Kankanhalli","orcid":"https://orcid.org/0000-0002-4846-2015"},"institutions":[{"id":"https://openalex.org/I165932596","display_name":"National University of Singapore","ror":"https://ror.org/01tgyzw49","country_code":"SG","type":"education","lineage":["https://openalex.org/I165932596"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Mohan Kankanhalli","raw_affiliation_strings":["National University of Singapore, Singapore, Singapore"],"raw_orcid":"https://orcid.org/0000-0002-4846-2015","affiliations":[{"raw_affiliation_string":"National University of Singapore, Singapore, Singapore","institution_ids":["https://openalex.org/I165932596"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5100399645"],"corresponding_institution_ids":["https://openalex.org/I165932596"],"apc_list":null,"apc_paid":null,"fwci":5.0758,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.95763375,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":91,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"7210","last_page":"7219"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12357","display_name":"Digital Media Forensic Detection","score":0.9950000047683716,"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/T12357","display_name":"Digital Media Forensic Detection","score":0.9950000047683716,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9746000170707703,"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/T13114","display_name":"Image Processing Techniques and Applications","score":0.9291999936103821,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/digital-watermarking","display_name":"Digital watermarking","score":0.8421000242233276},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.7978000044822693},{"id":"https://openalex.org/keywords/watermark","display_name":"Watermark","score":0.6948000192642212},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.5519000291824341},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4869000017642975},{"id":"https://openalex.org/keywords/detector","display_name":"Detector","score":0.38510000705718994}],"concepts":[{"id":"https://openalex.org/C150817343","wikidata":"https://www.wikidata.org/wiki/Q875932","display_name":"Digital watermarking","level":3,"score":0.8421000242233276},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.7978000044822693},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7817999720573425},{"id":"https://openalex.org/C164112704","wikidata":"https://www.wikidata.org/wiki/Q7974348","display_name":"Watermark","level":3,"score":0.6948000192642212},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5792999863624573},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.5519000291824341},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4869000017642975},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.398499995470047},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.38510000705718994},{"id":"https://openalex.org/C40636538","wikidata":"https://www.wikidata.org/wiki/Q81392","display_name":"Fractal","level":2,"score":0.3813000023365021},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.3589000105857849},{"id":"https://openalex.org/C2987933465","wikidata":"https://www.wikidata.org/wiki/Q141130","display_name":"Image manipulation","level":3,"score":0.3499999940395355},{"id":"https://openalex.org/C148730421","wikidata":"https://www.wikidata.org/wiki/Q141090","display_name":"Encryption","level":2,"score":0.337799996137619},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.334199994802475},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3321000039577484},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2849000096321106},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.2563999891281128}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1145/3746027.3754544","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3746027.3754544","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 33rd ACM International Conference on Multimedia","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2504.09451","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2504.09451","pdf_url":"https://arxiv.org/pdf/2504.09451","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"},{"id":"doi:10.48550/arxiv.2504.09451","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2504.09451","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":"article"}],"best_oa_location":{"id":"doi:10.1145/3746027.3754544","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3746027.3754544","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 33rd ACM International Conference on Multimedia","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W4313127140","https://openalex.org/W3092709185","https://openalex.org/W4386071484","https://openalex.org/W3176990204","https://openalex.org/W2072605585","https://openalex.org/W2752782242","https://openalex.org/W3164572690","https://openalex.org/W3193750732","https://openalex.org/W4287080402","https://openalex.org/W2618530766","https://openalex.org/W4386076699","https://openalex.org/W4388623432","https://openalex.org/W2010620862","https://openalex.org/W4390841259","https://openalex.org/W4312388562","https://openalex.org/W4308238062","https://openalex.org/W4394842931","https://openalex.org/W3206071277","https://openalex.org/W4361003656","https://openalex.org/W4382318331","https://openalex.org/W4403792060","https://openalex.org/W4390905233","https://openalex.org/W4387968109","https://openalex.org/W4402716358","https://openalex.org/W4413145315","https://openalex.org/W4319299925"],"related_works":[],"abstract_inverted_index":{"Proactive":[0],"Deepfake":[1,12,58,114,142,160,171,186],"detection":[2,25,34,46,59,187],"via":[3],"robust":[4,104],"watermarks":[5,41,55,80],"has":[6],"seen":[7],"interest":[8],"ever":[9],"since":[10],"passive":[11,168],"detectors":[13,169],"encountered":[14],"challenges":[15],"in":[16,33,116],"identifying":[17],"high-quality":[18],"synthetic":[19],"images.":[20],"However,":[21],"while":[22],"demonstrating":[23],"reasonable":[24],"performance,":[26],"they":[27],"lack":[28],"localization":[29,140],"functionality":[30],"and":[31,60,81,99,110,149,159,167],"explainability":[32,182],"results.":[35,188],"Additionally,":[36],"the":[37,45,66,86,129,176,184],"unstable":[38],"robustness":[39,148],"of":[40,68,85,141,151],"can":[42],"significantly":[43],"affect":[44],"performance.":[47],"In":[48],"this":[49],"study,":[50],"we":[51,70,90,121],"propose":[52,91],"novel":[53],"fractal":[54],"for":[56,96,170,183],"proactive":[57,185],"localization,":[61],"namely":[62],"FractalForensics.":[63],"Benefiting":[64],"from":[65],"characteristics":[67],"fractals,":[69],"devise":[71],"a":[72,92,117],"parameter-driven":[73],"watermark":[74,97,130],"generation":[75],"pipeline":[76],"that":[77,126],"derives":[78],"fractal-based":[79],"performs":[82],"one-way":[83],"encryption":[84],"selected":[87],"parameters.":[88],"Subsequently,":[89],"semi-fragile":[93,164],"watermarking":[94,165],"framework":[95],"embedding":[98],"recovery,":[100],"trained":[101],"to":[102],"be":[103],"against":[105,154],"benign":[106],"image":[107,134,156],"processing":[108,157],"operations":[109,158],"fragile":[111],"when":[112],"facing":[113],"manipulations":[115],"black-box":[118],"setting.":[119],"Moreover,":[120],"introduce":[122],"an":[123],"entry-to-patch":[124],"strategy":[125],"implicitly":[127],"embeds":[128],"matrix":[131],"entries":[132],"into":[133],"patches":[135],"at":[136],"corresponding":[137],"positions,":[138],"achieving":[139],"manipulations.":[143],"Extensive":[144],"experiments":[145],"demonstrate":[146],"satisfactory":[147],"fragility":[150],"our":[152,179],"approach":[153],"common":[155],"manipulations,":[161],"outperforming":[162],"state-of-the-art":[163],"algorithms":[166],"detection.":[172],"Furthermore,":[173],"by":[174],"highlighting":[175],"areas":[177],"manipulated,":[178],"method":[180],"provides":[181]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":1}],"updated_date":"2026-05-21T09:19:25.381259","created_date":"2025-10-14T00:00:00"}