{"id":"https://openalex.org/W4385338942","doi":"https://doi.org/10.1109/access.2023.3299862","title":"Defending Against Adversarial Fingerprint Attacks Based on Deep Image Prior","display_name":"Defending Against Adversarial Fingerprint Attacks Based on Deep Image Prior","publication_year":2023,"publication_date":"2023-01-01","ids":{"openalex":"https://openalex.org/W4385338942","doi":"https://doi.org/10.1109/access.2023.3299862"},"language":"en","primary_location":{"id":"doi:10.1109/access.2023.3299862","is_oa":true,"landing_page_url":"http://dx.doi.org/10.1109/access.2023.3299862","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10196440.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10196440.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5102806033","display_name":"Hwajung Yoo","orcid":"https://orcid.org/0009-0007-2581-6275"},"institutions":[{"id":"https://openalex.org/I94588446","display_name":"Hongik University","ror":"https://ror.org/00egdv862","country_code":"KR","type":"education","lineage":["https://openalex.org/I94588446"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Hwajung Yoo","raw_affiliation_strings":["Department of Computer Engineering, Hongik University, Seoul, Republic of Korea"],"affiliations":[{"raw_affiliation_string":"Department of Computer Engineering, Hongik University, Seoul, Republic of Korea","institution_ids":["https://openalex.org/I94588446"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008152841","display_name":"Pyo Min Hong","orcid":null},"institutions":[{"id":"https://openalex.org/I94588446","display_name":"Hongik University","ror":"https://ror.org/00egdv862","country_code":"KR","type":"education","lineage":["https://openalex.org/I94588446"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Pyo Min Hong","raw_affiliation_strings":["Department of Computer Engineering, Hongik University, Seoul, Republic of Korea"],"affiliations":[{"raw_affiliation_string":"Department of Computer Engineering, Hongik University, Seoul, Republic of Korea","institution_ids":["https://openalex.org/I94588446"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100747806","display_name":"Tae-Yong Kim","orcid":"https://orcid.org/0009-0000-9974-1279"},"institutions":[{"id":"https://openalex.org/I94588446","display_name":"Hongik University","ror":"https://ror.org/00egdv862","country_code":"KR","type":"education","lineage":["https://openalex.org/I94588446"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Taeyong Kim","raw_affiliation_strings":["Department of Computer Engineering, Hongik University, Seoul, Republic of Korea"],"affiliations":[{"raw_affiliation_string":"Department of Computer Engineering, Hongik University, Seoul, Republic of Korea","institution_ids":["https://openalex.org/I94588446"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102722163","display_name":"Jung Won Yoon","orcid":"https://orcid.org/0009-0002-9774-2440"},"institutions":[{"id":"https://openalex.org/I94588446","display_name":"Hongik University","ror":"https://ror.org/00egdv862","country_code":"KR","type":"education","lineage":["https://openalex.org/I94588446"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Jung Won Yoon","raw_affiliation_strings":["Department of Computer Engineering, Hongik University, Seoul, Republic of Korea"],"affiliations":[{"raw_affiliation_string":"Department of Computer Engineering, Hongik University, Seoul, Republic of Korea","institution_ids":["https://openalex.org/I94588446"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5083293918","display_name":"Youn Kyu Lee","orcid":"https://orcid.org/0000-0002-4569-2640"},"institutions":[{"id":"https://openalex.org/I94588446","display_name":"Hongik University","ror":"https://ror.org/00egdv862","country_code":"KR","type":"education","lineage":["https://openalex.org/I94588446"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Youn Kyu Lee","raw_affiliation_strings":["Department of Computer Engineering, Hongik University, Seoul, Republic of Korea"],"affiliations":[{"raw_affiliation_string":"Department of Computer Engineering, Hongik University, Seoul, Republic of Korea","institution_ids":["https://openalex.org/I94588446"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5102806033"],"corresponding_institution_ids":["https://openalex.org/I94588446"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":1.5659,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.86302979,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":99},"biblio":{"volume":"11","issue":null,"first_page":"78713","last_page":"78725"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9937999844551086,"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":0.9937999844551086,"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/T12357","display_name":"Digital Media Forensic Detection","score":0.9858999848365784,"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/T13192","display_name":"Forensic Fingerprint Detection Methods","score":0.9833999872207642,"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/computer-science","display_name":"Computer science","score":0.8325073719024658},{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.7989282011985779},{"id":"https://openalex.org/keywords/fingerprint","display_name":"Fingerprint (computing)","score":0.7975715398788452},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7602248191833496},{"id":"https://openalex.org/keywords/fingerprint-recognition","display_name":"Fingerprint recognition","score":0.6647105813026428},{"id":"https://openalex.org/keywords/biometrics","display_name":"Biometrics","score":0.6356539130210876},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.6121523380279541},{"id":"https://openalex.org/keywords/authentication","display_name":"Authentication (law)","score":0.5971468091011047},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5671646595001221},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5548082590103149},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.48293325304985046},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3373928666114807},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.27630820870399475}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8325073719024658},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.7989282011985779},{"id":"https://openalex.org/C2777826928","wikidata":"https://www.wikidata.org/wiki/Q3745713","display_name":"Fingerprint (computing)","level":2,"score":0.7975715398788452},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7602248191833496},{"id":"https://openalex.org/C168406668","wikidata":"https://www.wikidata.org/wiki/Q178022","display_name":"Fingerprint recognition","level":3,"score":0.6647105813026428},{"id":"https://openalex.org/C184297639","wikidata":"https://www.wikidata.org/wiki/Q177765","display_name":"Biometrics","level":2,"score":0.6356539130210876},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.6121523380279541},{"id":"https://openalex.org/C148417208","wikidata":"https://www.wikidata.org/wiki/Q4825882","display_name":"Authentication (law)","level":2,"score":0.5971468091011047},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5671646595001221},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5548082590103149},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.48293325304985046},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3373928666114807},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.27630820870399475}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2023.3299862","is_oa":true,"landing_page_url":"http://dx.doi.org/10.1109/access.2023.3299862","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10196440.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:056c5429a3f24802a384e34a0862f464","is_oa":true,"landing_page_url":"https://doaj.org/article/056c5429a3f24802a384e34a0862f464","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 11, Pp 78713-78725 (2023)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2023.3299862","is_oa":true,"landing_page_url":"http://dx.doi.org/10.1109/access.2023.3299862","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10196440.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16","score":0.46000000834465027}],"awards":[{"id":"https://openalex.org/G5136051803","display_name":null,"funder_award_id":"RS-2022-00165648","funder_id":"https://openalex.org/F4320322120","funder_display_name":"National Research Foundation of Korea"},{"id":"https://openalex.org/G7240127599","display_name":null,"funder_award_id":"RS-2023-00237308","funder_id":"https://openalex.org/F4320328359","funder_display_name":"Ministry of Science and ICT, South Korea"}],"funders":[{"id":"https://openalex.org/F4320321237","display_name":"Hongik University","ror":"https://ror.org/00egdv862"},{"id":"https://openalex.org/F4320322120","display_name":"National Research Foundation of Korea","ror":"https://ror.org/013aysd81"},{"id":"https://openalex.org/F4320328359","display_name":"Ministry of Science and ICT, South Korea","ror":"https://ror.org/01wpjm123"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4385338942.pdf","grobid_xml":"https://content.openalex.org/works/W4385338942.grobid-xml"},"referenced_works_count":53,"referenced_works":["https://openalex.org/W1673923490","https://openalex.org/W1945616565","https://openalex.org/W2041114617","https://openalex.org/W2041625018","https://openalex.org/W2048695508","https://openalex.org/W2056370875","https://openalex.org/W2097073572","https://openalex.org/W2172275395","https://openalex.org/W2215622264","https://openalex.org/W2243397390","https://openalex.org/W2508457857","https://openalex.org/W2764207251","https://openalex.org/W2774018344","https://openalex.org/W2898001268","https://openalex.org/W2962700793","https://openalex.org/W2962933288","https://openalex.org/W2963001136","https://openalex.org/W2963920068","https://openalex.org/W2964013315","https://openalex.org/W2972986629","https://openalex.org/W2983498217","https://openalex.org/W2987644081","https://openalex.org/W2996731563","https://openalex.org/W3005066631","https://openalex.org/W3007679772","https://openalex.org/W3013854549","https://openalex.org/W3021182036","https://openalex.org/W3035515196","https://openalex.org/W3035542568","https://openalex.org/W3047011367","https://openalex.org/W3122061855","https://openalex.org/W3126279905","https://openalex.org/W3131158285","https://openalex.org/W3149938609","https://openalex.org/W3169893408","https://openalex.org/W3173775919","https://openalex.org/W3174102408","https://openalex.org/W3196506678","https://openalex.org/W3200686910","https://openalex.org/W3208614786","https://openalex.org/W4200131942","https://openalex.org/W4205979394","https://openalex.org/W4224104371","https://openalex.org/W4288024909","https://openalex.org/W4293846201","https://openalex.org/W4310007307","https://openalex.org/W6637162671","https://openalex.org/W6640425456","https://openalex.org/W6739868092","https://openalex.org/W6745272055","https://openalex.org/W6746402973","https://openalex.org/W6755694737","https://openalex.org/W6779358743"],"related_works":["https://openalex.org/W4233349824","https://openalex.org/W3014822659","https://openalex.org/W2117826006","https://openalex.org/W1621827506","https://openalex.org/W4362496757","https://openalex.org/W2051501574","https://openalex.org/W2124627279","https://openalex.org/W2050967184","https://openalex.org/W2566091814","https://openalex.org/W4200422973"],"abstract_inverted_index":{"Recently,":[0],"deep":[1,25],"learning-based":[2],"biometric":[3],"authentication":[4],"systems,":[5],"especially":[6,43],"fingerprint":[7,64,104,113,132,145],"authentication,":[8],"have":[9,40,71],"been":[10,41],"used":[11],"widely":[12],"in":[13,81,139],"real-world.":[14],"However,":[15],"these":[16,35],"systems":[17],"are":[18],"vulnerable":[19],"to":[20,97,110,156],"adversarial":[21,63,99,131],"attacks":[22,133],"which":[23,77],"prevent":[24],"learning":[26],"models":[27],"from":[28],"distinguishing":[29],"input":[30,103],"data":[31],"properly.":[32],"To":[33,66],"solve":[34],"problems,":[36],"various":[37,128],"defense":[38,51,60,68,125],"methods":[39],"proposed,":[42],"utilizing":[44],"denoising":[45],"mechanisms,":[46],"but":[47],"they":[48],"provided":[49],"limited":[50],"performance.":[52],"In":[53],"this":[54],"study,":[55],"we":[56,70],"proposed":[57,94],"a":[58,88],"new":[59],"method":[61,95,121,149],"against":[62,127],"attacks.":[65],"ensure":[67],"performance,":[69],"introduced":[72],"Deep":[73,117],"Image":[74,118],"Prior":[75],"mechanism":[76],"has":[78,122,150],"superior":[79,155],"performance":[80,126],"image":[82,105,114,158],"reconstruction":[83,159],"without":[84],"prior":[85],"training":[86],"and":[87,106,142],"large":[89],"amount":[90],"of":[91,101,130,144],"dataset.":[92],"The":[93],"aims":[96],"remove":[98],"perturbations":[100],"the":[102,111],"reconstruct":[107],"it":[108,153],"close":[109],"original":[112],"by":[115],"adapting":[116],"Prior.":[119],"Our":[120],"achieved":[123],"robust":[124],"types":[129],"across":[134],"different":[135],"datasets,":[136],"encompassing":[137],"variations":[138],"sensors,":[140],"shapes,":[141],"materials":[143],"images.":[146],"Furthermore,":[147],"our":[148],"demonstrated":[151],"that":[152],"is":[154],"other":[157],"methods.":[160]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":2}],"updated_date":"2026-04-02T15:55:50.835912","created_date":"2025-10-10T00:00:00"}