{"id":"https://openalex.org/W2605595487","doi":"https://doi.org/10.1109/tifs.2017.2692683","title":"A Theoretical Framework for Estimating False Acceptance Rate of PRNU-Based Camera Identification","display_name":"A Theoretical Framework for Estimating False Acceptance Rate of PRNU-Based Camera Identification","publication_year":2017,"publication_date":"2017-04-12","ids":{"openalex":"https://openalex.org/W2605595487","doi":"https://doi.org/10.1109/tifs.2017.2692683","mag":"2605595487"},"language":"en","primary_location":{"id":"doi:10.1109/tifs.2017.2692683","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tifs.2017.2692683","pdf_url":null,"source":{"id":"https://openalex.org/S61310614","display_name":"IEEE Transactions on Information Forensics and Security","issn_l":"1556-6013","issn":["1556-6013","1556-6021"],"is_oa":false,"is_in_doaj":false,"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 Transactions on Information Forensics and Security","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5103201618","display_name":"Shota Saito","orcid":"https://orcid.org/0000-0002-7226-2814"},"institutions":[{"id":"https://openalex.org/I92614990","display_name":"Tokyo University of Agriculture and Technology","ror":"https://ror.org/00qg0kr10","country_code":"JP","type":"education","lineage":["https://openalex.org/I92614990"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Shota Saito","raw_affiliation_strings":["Tokyo University of Agriculture and Technology, Tokyo, Japan"],"raw_orcid":"https://orcid.org/0000-0002-7226-2814","affiliations":[{"raw_affiliation_string":"Tokyo University of Agriculture and Technology, Tokyo, Japan","institution_ids":["https://openalex.org/I92614990"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101768297","display_name":"Yoichi Tomioka","orcid":"https://orcid.org/0000-0003-3509-6607"},"institutions":[{"id":"https://openalex.org/I141591182","display_name":"University of Aizu","ror":"https://ror.org/02pg0e883","country_code":"JP","type":"education","lineage":["https://openalex.org/I141591182"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Yoichi Tomioka","raw_affiliation_strings":["University of Aizu, Aizuwakamatsu, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Aizu, Aizuwakamatsu, Japan","institution_ids":["https://openalex.org/I141591182"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102350873","display_name":"Hitoshi Kitazawa","orcid":null},"institutions":[{"id":"https://openalex.org/I92614990","display_name":"Tokyo University of Agriculture and Technology","ror":"https://ror.org/00qg0kr10","country_code":"JP","type":"education","lineage":["https://openalex.org/I92614990"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Hitoshi Kitazawa","raw_affiliation_strings":["Tokyo University of Agriculture and Technology, Tokyo, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tokyo University of Agriculture and Technology, Tokyo, Japan","institution_ids":["https://openalex.org/I92614990"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.3202,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":{"value":0.63667727,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"12","issue":"9","first_page":"2026","last_page":"2035"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12357","display_name":"Digital Media Forensic Detection","score":1.0,"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":1.0,"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/T10388","display_name":"Advanced Steganography and Watermarking Techniques","score":0.933899998664856,"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/T12364","display_name":"Archaeological Research and Protection","score":0.9158999919891357,"subfield":{"id":"https://openalex.org/subfields/1912","display_name":"Space and Planetary Science"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7639281749725342},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.7491262555122375},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.6713175773620605},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6635599136352539},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.6005311012268066},{"id":"https://openalex.org/keywords/digital-camera","display_name":"Digital camera","score":0.5185106992721558},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5140668153762817},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.456760436296463},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.40464505553245544},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.22218185663223267}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7639281749725342},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.7491262555122375},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.6713175773620605},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6635599136352539},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.6005311012268066},{"id":"https://openalex.org/C2779705975","wikidata":"https://www.wikidata.org/wiki/Q62927","display_name":"Digital camera","level":2,"score":0.5185106992721558},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5140668153762817},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.456760436296463},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.40464505553245544},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.22218185663223267},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tifs.2017.2692683","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tifs.2017.2692683","pdf_url":null,"source":{"id":"https://openalex.org/S61310614","display_name":"IEEE Transactions on Information Forensics and Security","issn_l":"1556-6013","issn":["1556-6013","1556-6021"],"is_oa":false,"is_in_doaj":false,"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 Transactions on Information Forensics and Security","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","score":0.550000011920929,"display_name":"Peace, Justice and strong institutions"}],"awards":[{"id":"https://openalex.org/G8652047548","display_name":"Establishment of Robust Source Camera Identification Technologies for Digital Images","funder_award_id":"26330152","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"}],"funders":[{"id":"https://openalex.org/F4320324691","display_name":"Tokyo University of Agriculture","ror":"https://ror.org/05crbcr45"},{"id":"https://openalex.org/F4320334764","display_name":"Japan Society for the Promotion of Science","ror":"https://ror.org/00hhkn466"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W1838866347","https://openalex.org/W1985836135","https://openalex.org/W1988600563","https://openalex.org/W1990547779","https://openalex.org/W2001426616","https://openalex.org/W2016094207","https://openalex.org/W2018810641","https://openalex.org/W2023827590","https://openalex.org/W2045905048","https://openalex.org/W2048698160","https://openalex.org/W2049771774","https://openalex.org/W2086666872","https://openalex.org/W2096754397","https://openalex.org/W2108243386","https://openalex.org/W2111007158","https://openalex.org/W2124283009","https://openalex.org/W2124695272","https://openalex.org/W2129240197","https://openalex.org/W2129551701","https://openalex.org/W2139322889","https://openalex.org/W2145080442","https://openalex.org/W2152203125","https://openalex.org/W2168126647","https://openalex.org/W2168745915","https://openalex.org/W4206302131","https://openalex.org/W6656666587","https://openalex.org/W6679658051"],"related_works":["https://openalex.org/W2085033728","https://openalex.org/W4285411112","https://openalex.org/W2171299904","https://openalex.org/W1647606319","https://openalex.org/W4390494008","https://openalex.org/W2053596378","https://openalex.org/W2922442631","https://openalex.org/W2168523118","https://openalex.org/W2804364458","https://openalex.org/W2284814053"],"abstract_inverted_index":{"In":[0,90,169,205,268],"recent":[1],"years,":[2],"camera":[3,17,60,74,157,184,239],"identification":[4,18,61,70,75,92,107,158,185,240,259,295],"methods":[5,19],"have":[6,68,141],"attracted":[7],"attention":[8],"in":[9,123],"the":[10,24,33,36,45,64,78,83,102,116,124,153,209,215,231,244,250,257,262,265,277,311],"field":[11],"of":[12,35,48,82,118,160,188,201,233,252,264,289,302,310],"digital":[13],"forensics.":[14],"The":[15,287],"existing":[16],"use":[20],"features,":[21],"such":[22,100],"as":[23,101],"Exif":[25],"header":[26],"data":[27,98,285],"and":[28,52,72,192],"image":[29,50,104,279],"noise,":[30,191],"that":[31,179,224,293],"indicate":[32,292],"characteristics":[34],"camera.":[37,58],"Of":[38],"them,":[39],"photo-response":[40],"non-uniformity":[41],"(PRNU)":[42],"noise":[43,66,86,237],"contains":[44],"unique":[46],"features":[47],"an":[49,219],"sensor":[51],"is":[53,94,134,226,282],"different":[54],"for":[55,136,152,183,218,307,316],"each":[56],"individual":[57],"A":[59,128],"method":[62,76,133,151,178,241,296],"using":[63,77,186,214,243],"PRNU":[65,85,155,190,236],"should":[67],"high":[69],"ability,":[71],"a":[73,121,145,162,174,198,202,234,283,298],"pairwise":[79],"magnitude":[80],"relations":[81],"clustered":[84,154,189,235],"was":[87],"previously":[88],"proposed.":[89],"general,":[91],"accuracy":[93,108,131],"estimated":[95],"from":[96,276],"test":[97,217],"sets,":[99],"Dresden":[103,278],"database.":[105],"However,":[106],"can":[109],"be":[110],"evaluated":[111],"only":[112],"with":[113,261],"respect":[114],"to":[115,228],"range":[117],"images":[119,275],"within":[120],"database":[122],"conventional":[125],"evaluation":[126,132,150,246,291],"method.":[127,247],"more":[129],"detailed":[130],"required":[135],"practical":[137],"use.":[138],"Furthermore,":[139],"studies":[140],"not":[142],"yet":[143],"reported":[144],"false":[146,299],"acceptance":[147],"rate":[148,301],"(FAR)":[149],"pair-based":[156,238],"capable":[159],"guaranteeing":[161],"low":[163],"FAR":[164,166,182,195,220,232,317],"(e.g.,":[165],"=":[167,318],"10-9).":[168],"this":[170,269,294],"paper,":[171],"we":[172,207,255,271],"proposed":[173,245,266],"new":[175],"pixel":[176],"clustering":[177],"guarantees":[180],"An":[181],"pairs":[187],"evaluate":[193],"its":[194],"based":[196],"on":[197],"probability":[199],"calculation":[200],"mathematical":[203],"model.":[204],"addition,":[206],"investigate":[208],"appropriate":[210],"cluster":[211],"size":[212],"by":[213,242],"Shapiro-Wilk":[216],"evaluation.":[221],"We":[222],"show":[223],"it":[225],"possible":[227],"reliably":[229],"calculate":[230],"To":[248],"demonstrate":[249],"validity":[251],"our":[253,290],"calculations,":[254],"compare":[256],"actual":[258],"result":[260,263],"calculation.":[267],"case,":[270],"used":[272],"16958":[273],"query":[274],"database,":[280],"which":[281],"benchmark":[284],"set.":[286],"results":[288],"maintains":[297],"rejection":[300],"less":[303],"than":[304],"5%":[305],"(10%)":[306],"5":[308],"(8)":[309],"10":[312],"tested":[313],"cameras":[314],"even":[315],"10-9.":[319]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":2},{"year":2017,"cited_by_count":1}],"updated_date":"2026-07-29T09:40:50.615796","created_date":"2025-10-10T00:00:00"}
