{"id":"https://openalex.org/W3193955590","doi":"https://doi.org/10.1109/icip42928.2021.9506564","title":"Identifying Physically Realizable Triggers for Backdoored Face Recognition Networks","display_name":"Identifying Physically Realizable Triggers for Backdoored Face Recognition Networks","publication_year":2021,"publication_date":"2021-08-23","ids":{"openalex":"https://openalex.org/W3193955590","doi":"https://doi.org/10.1109/icip42928.2021.9506564","mag":"3193955590"},"language":"en","primary_location":{"id":"doi:10.1109/icip42928.2021.9506564","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip42928.2021.9506564","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5113378413","display_name":"Ankita Raj","orcid":null},"institutions":[{"id":"https://openalex.org/I68891433","display_name":"Indian Institute of Technology Delhi","ror":"https://ror.org/049tgcd06","country_code":"IN","type":"education","lineage":["https://openalex.org/I68891433"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Ankita Raj","raw_affiliation_strings":["Indian Institute of Technology Delhi"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Indian Institute of Technology Delhi","institution_ids":["https://openalex.org/I68891433"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5026449354","display_name":"Ambar Pal","orcid":null},"institutions":[{"id":"https://openalex.org/I145311948","display_name":"Johns Hopkins University","ror":"https://ror.org/00za53h95","country_code":"US","type":"education","lineage":["https://openalex.org/I145311948"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ambar Pal","raw_affiliation_strings":["Johns Hopkins University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Johns Hopkins University","institution_ids":["https://openalex.org/I145311948"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101532736","display_name":"Chetan Arora","orcid":"https://orcid.org/0000-0003-0155-0250"},"institutions":[{"id":"https://openalex.org/I68891433","display_name":"Indian Institute of Technology Delhi","ror":"https://ror.org/049tgcd06","country_code":"IN","type":"education","lineage":["https://openalex.org/I68891433"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Chetan Arora","raw_affiliation_strings":["Indian Institute of Technology Delhi"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Indian Institute of Technology Delhi","institution_ids":["https://openalex.org/I68891433"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.3626,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.50773054,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"3023","last_page":"3027"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10828","display_name":"Biometric Identification and Security","score":0.9988999962806702,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T10828","display_name":"Biometric Identification and Security","score":0.9988999962806702,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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":0.9984999895095825,"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/T12357","display_name":"Digital Media Forensic Detection","score":0.9976999759674072,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/backdoor","display_name":"Backdoor","score":0.9106945395469666},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7493581175804138},{"id":"https://openalex.org/keywords/face","display_name":"Face (sociological concept)","score":0.6622979640960693},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6118060350418091},{"id":"https://openalex.org/keywords/facial-recognition-system","display_name":"Facial recognition system","score":0.5722246766090393},{"id":"https://openalex.org/keywords/baseline","display_name":"Baseline (sea)","score":0.5016732215881348},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.46853652596473694},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.4180241823196411},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3998173773288727},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3415323495864868},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3202333450317383}],"concepts":[{"id":"https://openalex.org/C2781045450","wikidata":"https://www.wikidata.org/wiki/Q254569","display_name":"Backdoor","level":2,"score":0.9106945395469666},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7493581175804138},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.6622979640960693},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6118060350418091},{"id":"https://openalex.org/C31510193","wikidata":"https://www.wikidata.org/wiki/Q1192553","display_name":"Facial recognition system","level":3,"score":0.5722246766090393},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.5016732215881348},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.46853652596473694},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.4180241823196411},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3998173773288727},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3415323495864868},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3202333450317383},{"id":"https://openalex.org/C111368507","wikidata":"https://www.wikidata.org/wiki/Q43518","display_name":"Oceanography","level":1,"score":0.0},{"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},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icip42928.2021.9506564","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip42928.2021.9506564","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","score":0.5799999833106995,"id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":33,"referenced_works":["https://openalex.org/W1508960934","https://openalex.org/W1945616565","https://openalex.org/W1998808035","https://openalex.org/W2019464758","https://openalex.org/W2115733720","https://openalex.org/W2243397390","https://openalex.org/W2325939864","https://openalex.org/W2543927648","https://openalex.org/W2748789698","https://openalex.org/W2753783305","https://openalex.org/W2774423163","https://openalex.org/W2891524773","https://openalex.org/W2898759955","https://openalex.org/W2934843808","https://openalex.org/W2966187620","https://openalex.org/W2966689772","https://openalex.org/W2990270730","https://openalex.org/W2990347604","https://openalex.org/W3037928287","https://openalex.org/W3135176461","https://openalex.org/W4252979261","https://openalex.org/W4288093767","https://openalex.org/W4289300166","https://openalex.org/W6640425456","https://openalex.org/W6743581629","https://openalex.org/W6743986261","https://openalex.org/W6746897123","https://openalex.org/W6756074407","https://openalex.org/W6756333562","https://openalex.org/W6766253520","https://openalex.org/W6767183785","https://openalex.org/W6778888658","https://openalex.org/W6780032954"],"related_works":["https://openalex.org/W4320031223","https://openalex.org/W3015678314","https://openalex.org/W4281902577","https://openalex.org/W4200629851","https://openalex.org/W3009072493","https://openalex.org/W4386185023","https://openalex.org/W4317672133","https://openalex.org/W3140988292","https://openalex.org/W2098693229","https://openalex.org/W2384651879"],"abstract_inverted_index":{"Backdoor":[0],"attacks":[1,57],"embed":[2],"a":[3,20,51,59,73,86,97,108,125,131],"hidden":[4],"functionality":[5],"into":[6],"deep":[7],"neural":[8],"networks,":[9],"causing":[10],"the":[11,24,63,102,118],"network":[12,82],"to":[13,47,62,76,116],"display":[14],"anomalous":[15],"behavior":[16],"when":[17],"activated":[18],"by":[19],"predetermined":[21],"pattern":[22],"in":[23,68],"input":[25],"(Trigger),":[26],"while":[27],"behaving":[28],"well":[29],"otherwise":[30],"on":[31],"public":[32],"test":[33],"data.":[34],"Recent":[35],"works":[36],"have":[37],"shown":[38],"that":[39],"backdoored":[40],"face":[41],"recognition":[42],"(FR)":[43],"systems":[44,67],"can":[45],"respond":[46],"natural-looking":[48],"triggers":[49,95],"like":[50],"particular":[52],"pair":[53],"of":[54,65,104,128],"sunglasses.":[55],"Such":[56],"pose":[58],"serious":[60],"threat":[61],"applicability":[64],"FR":[66,81,110],"high-security":[69],"applications.":[70],"We":[71,100],"propose":[72],"novel":[74],"technique":[75],"(1)":[77],"detect":[78],"whether":[79],"an":[80],"is":[83],"compromised":[84,98,109],"with":[85,107,124],"natural,":[87],"physically":[88],"realizable":[89],"trigger,":[90],"and":[91],"(2)":[92],"identify":[93,117],"such":[94],"given":[96],"network.":[99],"demonstrate":[101],"effectiveness":[103],"our":[105],"methods":[106],"network,":[111],"where":[112],"we":[113],"are":[114],"able":[115],"trigger":[119],"(e.g.":[120],"green-sunglasses":[121],"or":[122],"redbowtie)":[123],"top-5":[126],"accuracy":[127],"74%,":[129],"whereas":[130],"na\u00efve":[132],"brute":[133],"force":[134],"baseline":[135],"achieves":[136],"56%":[137],"accuracy.":[138]},"counts_by_year":[{"year":2024,"cited_by_count":2}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}