{"id":"https://openalex.org/W4388821145","doi":"https://doi.org/10.1109/apsipaasc58517.2023.10317501","title":"Hindering Adversarial Attacks with Multiple Encrypted Patch Embeddings","display_name":"Hindering Adversarial Attacks with Multiple Encrypted Patch Embeddings","publication_year":2023,"publication_date":"2023-10-31","ids":{"openalex":"https://openalex.org/W4388821145","doi":"https://doi.org/10.1109/apsipaasc58517.2023.10317501"},"language":"en","primary_location":{"id":"doi:10.1109/apsipaasc58517.2023.10317501","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/apsipaasc58517.2023.10317501","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 Asia Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC)","raw_type":"proceedings-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/I184597095","display_name":"National Institute of Informatics","ror":"https://ror.org/04ksd4g47","country_code":"JP","type":"facility","lineage":["https://openalex.org/I1319490839","https://openalex.org/I184597095","https://openalex.org/I4210158934"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"AprilPyone MaungMaung","raw_affiliation_strings":["National Institute of Informatics,Tokyo,Japan","National Institute of Informatics, Tokyo, Japan"],"affiliations":[{"raw_affiliation_string":"National Institute of Informatics,Tokyo,Japan","institution_ids":["https://openalex.org/I184597095"]},{"raw_affiliation_string":"National Institute of Informatics, Tokyo, Japan","institution_ids":["https://openalex.org/I184597095"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5044556342","display_name":"Isao Echizen","orcid":"https://orcid.org/0000-0003-4908-1860"},"institutions":[{"id":"https://openalex.org/I184597095","display_name":"National Institute of Informatics","ror":"https://ror.org/04ksd4g47","country_code":"JP","type":"facility","lineage":["https://openalex.org/I1319490839","https://openalex.org/I184597095","https://openalex.org/I4210158934"]},{"id":"https://openalex.org/I74801974","display_name":"The University of Tokyo","ror":"https://ror.org/057zh3y96","country_code":"JP","type":"education","lineage":["https://openalex.org/I74801974"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Isao Echizen","raw_affiliation_strings":["National Institute of Informatics,Tokyo,Japan","National Institute of Informatics, Tokyo, Japan","University of Tokyo, Tokyo, Japan"],"affiliations":[{"raw_affiliation_string":"National Institute of Informatics,Tokyo,Japan","institution_ids":["https://openalex.org/I184597095"]},{"raw_affiliation_string":"National Institute of Informatics, Tokyo, Japan","institution_ids":["https://openalex.org/I184597095"]},{"raw_affiliation_string":"University of Tokyo, Tokyo, Japan","institution_ids":["https://openalex.org/I74801974"]}]},{"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,Tokyo,Japan","Tokyo Metropolitan University, Tokyo, Japan"],"affiliations":[{"raw_affiliation_string":"Tokyo Metropolitan University,Tokyo,Japan","institution_ids":["https://openalex.org/I69740276"]},{"raw_affiliation_string":"Tokyo Metropolitan University, Tokyo, Japan","institution_ids":["https://openalex.org/I69740276"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5061499776"],"corresponding_institution_ids":["https://openalex.org/I184597095"],"apc_list":null,"apc_paid":null,"fwci":0.3491,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.66678823,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":96},"biblio":{"volume":"33","issue":null,"first_page":"1398","last_page":"1404"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9998999834060669,"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":0.9998999834060669,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9520000219345093,"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/T10751","display_name":"Forensic and Genetic Research","score":0.9480000138282776,"subfield":{"id":"https://openalex.org/subfields/1311","display_name":"Genetics"},"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/computer-science","display_name":"Computer science","score":0.80268394947052},{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.7357146739959717},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6792863011360168},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.6346185207366943},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.6165963411331177},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.602108895778656},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4985544681549072},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.46771472692489624},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.31976038217544556}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.80268394947052},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.7357146739959717},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6792863011360168},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.6346185207366943},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.6165963411331177},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.602108895778656},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4985544681549072},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.46771472692489624},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.31976038217544556},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","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/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/apsipaasc58517.2023.10317501","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/apsipaasc58517.2023.10317501","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 Asia Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","score":0.4099999964237213,"display_name":"Sustainable cities and communities"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":71,"referenced_works":["https://openalex.org/W9657784","https://openalex.org/W2117539524","https://openalex.org/W2143612262","https://openalex.org/W2194775991","https://openalex.org/W2535873859","https://openalex.org/W2603766943","https://openalex.org/W2618235498","https://openalex.org/W2766972025","https://openalex.org/W2774018344","https://openalex.org/W2798302089","https://openalex.org/W2919115771","https://openalex.org/W2963178695","https://openalex.org/W2963542245","https://openalex.org/W2963855547","https://openalex.org/W2964286909","https://openalex.org/W2969664989","https://openalex.org/W2971266385","https://openalex.org/W3033586497","https://openalex.org/W3091761040","https://openalex.org/W3097573595","https://openalex.org/W3103340107","https://openalex.org/W3103836116","https://openalex.org/W3112272555","https://openalex.org/W3134815184","https://openalex.org/W3157506437","https://openalex.org/W3163465952","https://openalex.org/W4200625937","https://openalex.org/W4226117697","https://openalex.org/W4226297238","https://openalex.org/W4226363321","https://openalex.org/W4285275243","https://openalex.org/W4285661751","https://openalex.org/W4286977100","https://openalex.org/W4287637349","https://openalex.org/W4288363925","https://openalex.org/W4293846201","https://openalex.org/W4323323110","https://openalex.org/W4385245566","https://openalex.org/W4385656546","https://openalex.org/W4388721484","https://openalex.org/W4401450512","https://openalex.org/W6637162671","https://openalex.org/W6640425456","https://openalex.org/W6738369334","https://openalex.org/W6741036071","https://openalex.org/W6744679260","https://openalex.org/W6745272055","https://openalex.org/W6745797779","https://openalex.org/W6746402973","https://openalex.org/W6747920752","https://openalex.org/W6748277150","https://openalex.org/W6748475379","https://openalex.org/W6757660717","https://openalex.org/W6758684365","https://openalex.org/W6761100157","https://openalex.org/W6762993384","https://openalex.org/W6765694979","https://openalex.org/W6771809012","https://openalex.org/W6774469542","https://openalex.org/W6774549192","https://openalex.org/W6784333009","https://openalex.org/W6784493056","https://openalex.org/W6787575297","https://openalex.org/W6787972765","https://openalex.org/W6795140394","https://openalex.org/W6796417832","https://openalex.org/W6801534648","https://openalex.org/W6811014117","https://openalex.org/W6845718657","https://openalex.org/W6850557276","https://openalex.org/W6850577816"],"related_works":["https://openalex.org/W2502115930","https://openalex.org/W2482350142","https://openalex.org/W4246396837","https://openalex.org/W3176240006","https://openalex.org/W3126451824","https://openalex.org/W1561927205","https://openalex.org/W3191453585","https://openalex.org/W4297672492","https://openalex.org/W4288019534","https://openalex.org/W4310988119"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"we":[3],"propose":[4],"a":[5,81,131,136],"new":[6],"key-based":[7,18,144],"defense":[8,19,44,55,69,95,111,129],"focusing":[9],"on":[10,45,98,104],"both":[11],"efficiency":[12],"and":[13,36,63,77,108,135],"robustness.":[14],"Although":[15],"the":[16,33,42,53,93,105,109,127,142],"previous":[17,34,43,54,143],"seems":[20],"effective":[21],"in":[22],"defending":[23],"against":[24,114],"adversarial":[25],"examples,":[26],"carefully":[27],"designed":[28],"adaptive":[29,121],"attacks":[30],"can":[31],"bypass":[32],"defense,":[35],"it":[37],"is":[38],"difficult":[39],"to":[40,141],"train":[41],"large":[46],"datasets":[47],"like":[48],"ImageNet.":[49],"We":[50],"build":[51],"upon":[52],"with":[56,80],"two":[57],"major":[58],"improvements:":[59],"(1)":[60],"efficient":[61],"training":[62],"(2)":[64],"optional":[65],"randomization.":[66],"The":[67,123],"proposed":[68,94,110,128],"utilizes":[70],"one":[71,88],"or":[72],"more":[73,86],"secret":[74,89],"patch":[75],"embeddings":[76,90],"classifier":[78],"heads":[79],"pre-trained":[82],"isotropic":[83],"network.":[84],"When":[85],"than":[87],"are":[91],"used,":[92],"enables":[96],"randomization":[97],"inference.":[99],"Experiments":[100],"were":[101],"carried":[102],"out":[103],"ImageNet":[106],"dataset,":[107],"was":[112],"evaluated":[113],"an":[115],"arsenal":[116],"of":[117],"state-of-the-art":[118],"attacks,":[119],"including":[120],"ones.":[122],"results":[124],"show":[125],"that":[126],"achieves":[130],"high":[132],"robust":[133],"accuracy":[134,139],"comparable":[137],"clean":[138],"compared":[140],"defense.":[145]},"counts_by_year":[{"year":2024,"cited_by_count":2}],"updated_date":"2025-12-19T19:40:27.379048","created_date":"2025-10-10T00:00:00"}