{"id":"https://openalex.org/W4225775889","doi":"https://doi.org/10.1109/mmul.2022.3168441","title":"Privacy-Preserving Image Classification Using an Isotropic Network","display_name":"Privacy-Preserving Image Classification Using an Isotropic Network","publication_year":2022,"publication_date":"2022-04-01","ids":{"openalex":"https://openalex.org/W4225775889","doi":"https://doi.org/10.1109/mmul.2022.3168441"},"language":"en","primary_location":{"id":"doi:10.1109/mmul.2022.3168441","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mmul.2022.3168441","pdf_url":null,"source":{"id":"https://openalex.org/S72873717","display_name":"IEEE Multimedia","issn_l":"1070-986X","issn":["1070-986X","1941-0166"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","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 MultiMedia","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/A5061499776","display_name":"AprilPyone MaungMaung","orcid":"https://orcid.org/0000-0002-0036-6577"},"institutions":[{"id":"https://openalex.org/I69740276","display_name":"Tokyo Metropolitan University","ror":"https://ror.org/00ws30h19","country_code":"JP","type":"education","lineage":["https://openalex.org/I69740276"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"MaungMaung AprilPyone","raw_affiliation_strings":["Tokyo Metropolitan University, Hachioji, Japan"],"affiliations":[{"raw_affiliation_string":"Tokyo Metropolitan University, Hachioji, Japan","institution_ids":["https://openalex.org/I69740276"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5015250468","display_name":"Hitoshi Kiya","orcid":"https://orcid.org/0000-0001-8061-3090"},"institutions":[{"id":"https://openalex.org/I69740276","display_name":"Tokyo Metropolitan University","ror":"https://ror.org/00ws30h19","country_code":"JP","type":"education","lineage":["https://openalex.org/I69740276"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Hitoshi Kiya","raw_affiliation_strings":["Tokyo Metropolitan University, Hachioji, Japan"],"affiliations":[{"raw_affiliation_string":"Tokyo Metropolitan University, Hachioji, Japan","institution_ids":["https://openalex.org/I69740276"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5061499776"],"corresponding_institution_ids":["https://openalex.org/I69740276"],"apc_list":null,"apc_paid":null,"fwci":3.464,"has_fulltext":false,"cited_by_count":35,"citation_normalized_percentile":{"value":0.93917284,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":"29","issue":"2","first_page":"23","last_page":"33"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12357","display_name":"Digital Media Forensic Detection","score":0.9995999932289124,"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":0.9995999932289124,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9983000159263611,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.9973999857902527,"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/computer-science","display_name":"Computer science","score":0.8255531787872314},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6872109174728394},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6247687339782715},{"id":"https://openalex.org/keywords/encryption","display_name":"Encryption","score":0.5984916090965271},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5750045776367188},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.5637122392654419},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.47571712732315063},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4537534713745117},{"id":"https://openalex.org/keywords/isotropy","display_name":"Isotropy","score":0.4247116148471832},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.39755189418792725},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.3680775761604309},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3365365266799927},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.08600100874900818}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8255531787872314},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6872109174728394},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6247687339782715},{"id":"https://openalex.org/C148730421","wikidata":"https://www.wikidata.org/wiki/Q141090","display_name":"Encryption","level":2,"score":0.5984916090965271},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5750045776367188},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.5637122392654419},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.47571712732315063},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4537534713745117},{"id":"https://openalex.org/C184050105","wikidata":"https://www.wikidata.org/wiki/Q273163","display_name":"Isotropy","level":2,"score":0.4247116148471832},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.39755189418792725},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3680775761604309},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3365365266799927},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.08600100874900818},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/mmul.2022.3168441","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mmul.2022.3168441","pdf_url":null,"source":{"id":"https://openalex.org/S72873717","display_name":"IEEE Multimedia","issn_l":"1070-986X","issn":["1070-986X","1941-0166"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","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 MultiMedia","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","score":0.44999998807907104,"display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W2053637704","https://openalex.org/W2535838896","https://openalex.org/W2898784076","https://openalex.org/W2962785568","https://openalex.org/W2964335264","https://openalex.org/W2995164854","https://openalex.org/W3002159741","https://openalex.org/W3022226764","https://openalex.org/W3118146262","https://openalex.org/W3118608800","https://openalex.org/W3134815184","https://openalex.org/W3153868986","https://openalex.org/W3159734327","https://openalex.org/W3201322425","https://openalex.org/W4285275243","https://openalex.org/W4285661751","https://openalex.org/W4287024535","https://openalex.org/W4297687186","https://openalex.org/W4322614810","https://openalex.org/W6663928093","https://openalex.org/W6772836532","https://openalex.org/W6776691762","https://openalex.org/W6784037095","https://openalex.org/W6787972765","https://openalex.org/W6796427001","https://openalex.org/W6800721355","https://openalex.org/W6811014117"],"related_works":["https://openalex.org/W2794789911","https://openalex.org/W4298134547","https://openalex.org/W2122976425","https://openalex.org/W2088773039","https://openalex.org/W2284229495","https://openalex.org/W2028697747","https://openalex.org/W3201490839","https://openalex.org/W4286980382","https://openalex.org/W3213778312","https://openalex.org/W3134175397"],"abstract_inverted_index":{"In":[0,53,122],"this":[1],"article,":[2],"we":[3],"propose":[4],"a":[5,49,85],"privacy-preserving":[6,108,127],"image":[7,109,115,128],"classification":[8,51,86,110,129,145],"method":[9,25],"that":[10],"uses":[11],"encrypted":[12,56],"images":[13,32,139],"and":[14,43,68,117,147,161],"an":[15,79,91,123],"isotropic":[16,120,157],"network,":[17,87],"such":[18],"as":[19],"the":[20,102,125,153],"vision":[21,159],"transformer.":[22],"The":[23],"proposed":[24,126],"allows":[26],"us":[27],"not":[28],"only":[29,96],"to":[30,36,47,75,132],"apply":[31],"without":[33,70],"visual":[34],"information":[35],"deep":[37],"neural":[38],"networks":[39],"for":[40,65],"both":[41,66],"training":[42,67],"testing,":[44],"but":[45],"also":[46],"maintain":[48],"high":[50],"accuracy.":[52],"addition,":[54],"compressible":[55],"images,":[57,61,78],"called":[58],"encryption-then-compression":[59],"(EtC)":[60],"can":[62],"be":[63],"used":[64,141],"testing":[69],"any":[71],"adaptation":[72,80,92],"network.":[73],"Previously,":[74],"classify":[76],"EtC":[77,138],"network":[81,93],"was":[82,130],"required":[83],"before":[84],"so":[88],"methods":[89,111,135],"with":[90],"have":[94,112],"been":[95],"tested":[97],"on":[98],"small":[99],"images.":[100],"To":[101],"best":[103],"of":[104,144,155],"our":[105],"knowledge,":[106],"previous":[107],"never":[113],"considered":[114],"compressibility":[116],"patch":[118],"embedding-based":[119],"networks.":[121],"experiment,":[124],"demonstrated":[131],"outperform":[133],"state-of-the-art":[134],"even":[136],"when":[137],"were":[140],"in":[142],"terms":[143],"accuracy":[146],"robustness":[148],"against":[149],"various":[150],"attacks":[151],"under":[152],"use":[154],"two":[156],"networks:":[158],"transformer":[160],"ConvMixer.":[162]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":8},{"year":2023,"cited_by_count":10},{"year":2022,"cited_by_count":11}],"updated_date":"2026-03-28T08:17:26.163206","created_date":"2025-10-10T00:00:00"}
