{"id":"https://openalex.org/W4377966851","doi":"https://doi.org/10.1109/access.2023.3279488","title":"Invisible Adversarial Attacks on Deep Learning-Based Face Recognition Models","display_name":"Invisible Adversarial Attacks on Deep Learning-Based Face Recognition Models","publication_year":2023,"publication_date":"2023-01-01","ids":{"openalex":"https://openalex.org/W4377966851","doi":"https://doi.org/10.1109/access.2023.3279488"},"language":"en","primary_location":{"id":"doi:10.1109/access.2023.3279488","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2023.3279488","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/10005208/10132477.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/ielx7/6287639/10005208/10132477.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5087964642","display_name":"Chih\u2010Yang Lin","orcid":"https://orcid.org/0000-0002-0401-8473"},"institutions":[{"id":"https://openalex.org/I22265921","display_name":"National Central University","ror":"https://ror.org/00944ve71","country_code":"TW","type":"education","lineage":["https://openalex.org/I22265921"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Chih-Yang Lin","raw_affiliation_strings":["Department of Mechanical Engineering, National Central University, Taoyuan, Taiwan"],"raw_orcid":"https://orcid.org/0000-0002-0401-8473","affiliations":[{"raw_affiliation_string":"Department of Mechanical Engineering, National Central University, Taoyuan, Taiwan","institution_ids":["https://openalex.org/I22265921"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110979882","display_name":"Feng-Jie Chen","orcid":null},"institutions":[{"id":"https://openalex.org/I148099254","display_name":"National Chung Cheng University","ror":"https://ror.org/0028v3876","country_code":"TW","type":"education","lineage":["https://openalex.org/I148099254"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Feng-Jie Chen","raw_affiliation_strings":["Department of Computer Science and Information Engineering, National Chung Cheng University, Chiayi, Taiwan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Information Engineering, National Chung Cheng University, Chiayi, Taiwan","institution_ids":["https://openalex.org/I148099254"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009152648","display_name":"Hui\u2010Fuang Ng","orcid":"https://orcid.org/0000-0003-4394-2770"},"institutions":[{"id":"https://openalex.org/I931681460","display_name":"Universiti Tunku Abdul Rahman","ror":"https://ror.org/050pq4m56","country_code":"MY","type":"education","lineage":["https://openalex.org/I931681460"]}],"countries":["MY"],"is_corresponding":false,"raw_author_name":"Hui-Fuang Ng","raw_affiliation_strings":["Department of Computer Science, University Tunku Abdul Rahman, Kampar, Malaysia"],"raw_orcid":"https://orcid.org/0000-0003-4394-2770","affiliations":[{"raw_affiliation_string":"Department of Computer Science, University Tunku Abdul Rahman, Kampar, Malaysia","institution_ids":["https://openalex.org/I931681460"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101420358","display_name":"Wei-Yang Lin","orcid":"https://orcid.org/0000-0003-0895-2498"},"institutions":[{"id":"https://openalex.org/I148099254","display_name":"National Chung Cheng University","ror":"https://ror.org/0028v3876","country_code":"TW","type":"education","lineage":["https://openalex.org/I148099254"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Wei-Yang Lin","raw_affiliation_strings":["Department of Computer Science and Information Engineering, National Chung Cheng University, Chiayi, Taiwan"],"raw_orcid":"https://orcid.org/0000-0003-0895-2498","affiliations":[{"raw_affiliation_string":"Department of Computer Science and Information Engineering, National Chung Cheng University, Chiayi, Taiwan","institution_ids":["https://openalex.org/I148099254"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":1.9579,"has_fulltext":true,"cited_by_count":12,"citation_normalized_percentile":{"value":0.88728712,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"11","issue":null,"first_page":"51567","last_page":"51577"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9990000128746033,"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":0.9990000128746033,"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/T11448","display_name":"Face recognition and analysis","score":0.9754999876022339,"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/T11515","display_name":"Bacillus and Francisella bacterial research","score":0.9383000135421753,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.8300865888595581},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8037135601043701},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.7742509841918945},{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.7047792077064514},{"id":"https://openalex.org/keywords/landmark","display_name":"Landmark","score":0.6869234442710876},{"id":"https://openalex.org/keywords/face","display_name":"Face (sociological concept)","score":0.6493543386459351},{"id":"https://openalex.org/keywords/facial-recognition-system","display_name":"Facial recognition system","score":0.5736464262008667},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5618358850479126},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5375003814697266},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5298908352851868},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.5018765926361084},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4984867572784424},{"id":"https://openalex.org/keywords/deep-neural-networks","display_name":"Deep neural networks","score":0.4426567256450653},{"id":"https://openalex.org/keywords/face-detection","display_name":"Face detection","score":0.44046950340270996},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.4281449019908905},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.4206165671348572},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.41950464248657227}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.8300865888595581},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8037135601043701},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.7742509841918945},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.7047792077064514},{"id":"https://openalex.org/C2780297707","wikidata":"https://www.wikidata.org/wiki/Q4895393","display_name":"Landmark","level":2,"score":0.6869234442710876},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.6493543386459351},{"id":"https://openalex.org/C31510193","wikidata":"https://www.wikidata.org/wiki/Q1192553","display_name":"Facial recognition system","level":3,"score":0.5736464262008667},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5618358850479126},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5375003814697266},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5298908352851868},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.5018765926361084},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4984867572784424},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.4426567256450653},{"id":"https://openalex.org/C4641261","wikidata":"https://www.wikidata.org/wiki/Q11681085","display_name":"Face detection","level":4,"score":0.44046950340270996},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.4281449019908905},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.4206165671348572},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.41950464248657227},{"id":"https://openalex.org/C36289849","wikidata":"https://www.wikidata.org/wiki/Q34749","display_name":"Social science","level":1,"score":0.0},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2023.3279488","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2023.3279488","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/10005208/10132477.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:f0c15259868f4189b72ff69fae65a0ed","is_oa":true,"landing_page_url":"https://doaj.org/article/f0c15259868f4189b72ff69fae65a0ed","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","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":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 11, Pp 51567-51577 (2023)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2023.3279488","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2023.3279488","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/10005208/10132477.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":0.5199999809265137}],"awards":[{"id":"https://openalex.org/G109341913","display_name":null,"funder_award_id":"NSTC 110-2221-E-155-039-MY3","funder_id":"https://openalex.org/F4320331164","funder_display_name":"National Science and Technology Council"},{"id":"https://openalex.org/G7467150794","display_name":null,"funder_award_id":"NSTC 111-2221-E-155-039-MY3","funder_id":"https://openalex.org/F4320331164","funder_display_name":"National Science and Technology Council"}],"funders":[{"id":"https://openalex.org/F4320331164","display_name":"National Science and Technology Council","ror":"https://ror.org/00wnb9798"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4377966851.pdf","grobid_xml":"https://content.openalex.org/works/W4377966851.grobid-xml"},"referenced_works_count":27,"referenced_works":["https://openalex.org/W1509966554","https://openalex.org/W1915485278","https://openalex.org/W2087681821","https://openalex.org/W2096733369","https://openalex.org/W2132083787","https://openalex.org/W2133665775","https://openalex.org/W2535873859","https://openalex.org/W2561238782","https://openalex.org/W2963542245","https://openalex.org/W2963771536","https://openalex.org/W2969664989","https://openalex.org/W2969985801","https://openalex.org/W3099206234","https://openalex.org/W3119391778","https://openalex.org/W3167558987","https://openalex.org/W3189402954","https://openalex.org/W3210063376","https://openalex.org/W4293580221","https://openalex.org/W4293846201","https://openalex.org/W4296473303","https://openalex.org/W4297814571","https://openalex.org/W4323660286","https://openalex.org/W6630649318","https://openalex.org/W6637162671","https://openalex.org/W6640425456","https://openalex.org/W6730179637","https://openalex.org/W6739868092"],"related_works":["https://openalex.org/W2950183588","https://openalex.org/W3080754722","https://openalex.org/W4383221314","https://openalex.org/W3093978547","https://openalex.org/W2953536436","https://openalex.org/W3203790781","https://openalex.org/W2997056298","https://openalex.org/W2738001131","https://openalex.org/W4285785480","https://openalex.org/W3127875750"],"abstract_inverted_index":{"Deep":[0],"learning":[1,23],"technology":[2],"has":[3],"grown":[4],"rapidly":[5],"in":[6,13,28,56,84,119,289],"recent":[7],"years":[8],"and":[9,64,143,151,263],"achieved":[10],"tremendous":[11],"success":[12,234],"the":[14,46,102,135,147,157,167,175,178,187,204,226,245,250,256,269,277],"field":[15],"of":[16,49,58,228,232,244],"computer":[17],"vision.":[18],"At":[19],"present,":[20],"many":[21],"deep":[22,43,59,71],"technologies":[24],"have":[25,67,88],"been":[26],"applied":[27],"daily":[29],"life,":[30],"such":[31],"as":[32,37,192],"face":[33,73,94,116,129,158,257,270,286],"recognition":[34,74,117,258,271,287],"systems.":[35],"However,":[36,91],"human":[38],"life":[39],"increasingly":[40],"relies":[41],"on":[42,115,139,285],"neural":[44,50,60],"networks,":[45],"potential":[47],"harms":[48],"networks":[51],"are":[52,76,96,132,154,190,253,264],"being":[53],"revealed,":[54],"particularly":[55],"terms":[57],"network":[61],"security.":[62],"More":[63],"more":[65],"studies":[66],"shown":[68],"that":[69,86,131,210,276],"existing":[70,92,196],"learning-based":[72],"models":[75],"vulnerable":[77],"to":[78,99,111,173,194,199,238,255,267],"attacks":[79,114,284],"by":[80,249],"adversarial":[81,93,128,201,215,246,283],"samples,":[82],"resulting":[83],"misjudgments":[85],"could":[87],"serious":[89],"consequences.":[90],"images":[95,130,137,247],"rather":[97],"easy":[98],"identify":[100],"with":[101,182,217],"naked":[103],"eye,":[104],"so":[105],"it":[106],"is":[107,171],"difficult":[108],"for":[109,126],"attackers":[110],"carry":[112],"out":[113],"systems":[118,288],"practice.":[120],"This":[121],"paper":[122],"proposes":[123],"a":[124,161,229,261],"method":[125,212,252,279],"generating":[127],"indistinguishable":[133],"from":[134,156],"source":[136],"based":[138],"facial":[140,162,180],"landmark":[141,163],"detection":[142,164],"superpixel":[144,168],"segmentation.":[145],"First,":[146],"eyebrows,":[148],"eyes,":[149],"nose,":[150],"mouth":[152],"regions":[153,189],"extracted":[155,179],"image":[159],"using":[160],"algorithm.":[165],"Next,":[166],"segmentation":[169],"algorithm":[170],"used":[172,191],"include":[174],"pixels":[176],"neighboring":[177],"landmarks":[181],"similar":[183],"pixel":[184],"values.":[185],"Lastly,":[186],"segmented":[188],"masks":[193],"guide":[195],"attack":[197,233],"methods":[198],"insert":[200],"noise":[202],"within":[203],"masked":[205],"areas.":[206],"Experimental":[207,273],"results":[208,274],"show":[209],"our":[211],"can":[213,280],"generate":[214],"samples":[216],"high":[218],"Structural":[219],"Similarity":[220],"Index":[221],"Measure":[222],"(SSIM)":[223],"values":[224],"at":[225],"cost":[227],"small":[230],"percentage":[231],"rate.":[235],"In":[236],"addition,":[237],"simulate":[239],"real-time":[240],"physical":[241],"attacks,":[242],"printouts":[243],"generated":[248],"proposed":[251,278],"presented":[254],"system":[259],"via":[260],"camera":[262],"still":[265],"able":[266],"fool":[268],"model.":[272],"indicated":[275],"successfully":[281],"perform":[282],"real-world":[290],"scenarios.":[291]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
