{"id":"https://openalex.org/W3182276460","doi":"https://doi.org/10.1007/s42979-021-00755-w","title":"Tandem Deep Learning Side-Channel Attack on FPGA Implementation of AES","display_name":"Tandem Deep Learning Side-Channel Attack on FPGA Implementation of AES","publication_year":2021,"publication_date":"2021-07-09","ids":{"openalex":"https://openalex.org/W3182276460","doi":"https://doi.org/10.1007/s42979-021-00755-w","mag":"3182276460"},"language":"en","primary_location":{"id":"doi:10.1007/s42979-021-00755-w","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s42979-021-00755-w","pdf_url":"https://link.springer.com/content/pdf/10.1007/s42979-021-00755-w.pdf","source":{"id":"https://openalex.org/S4210174798","display_name":"SN Computer Science","issn_l":"2661-8907","issn":["2661-8907","2662-995X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SN Computer Science","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://link.springer.com/content/pdf/10.1007/s42979-021-00755-w.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100696528","display_name":"Huanyu Wang","orcid":"https://orcid.org/0000-0001-9630-5869"},"institutions":[{"id":"https://openalex.org/I86987016","display_name":"KTH Royal Institute of Technology","ror":"https://ror.org/026vcq606","country_code":"SE","type":"education","lineage":["https://openalex.org/I86987016"]}],"countries":["SE"],"is_corresponding":true,"raw_author_name":"Huanyu Wang","raw_affiliation_strings":["KTH Royal Institute of Technology, Stockholm, Sweden"],"raw_orcid":"https://orcid.org/0000-0001-9630-5869","affiliations":[{"raw_affiliation_string":"KTH Royal Institute of Technology, Stockholm, Sweden","institution_ids":["https://openalex.org/I86987016"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5011438358","display_name":"Elena Dubrova","orcid":"https://orcid.org/0000-0001-7382-9408"},"institutions":[{"id":"https://openalex.org/I86987016","display_name":"KTH Royal Institute of Technology","ror":"https://ror.org/026vcq606","country_code":"SE","type":"education","lineage":["https://openalex.org/I86987016"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Elena Dubrova","raw_affiliation_strings":["KTH Royal Institute of Technology, Stockholm, Sweden"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"KTH Royal Institute of Technology, Stockholm, Sweden","institution_ids":["https://openalex.org/I86987016"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5100696528"],"corresponding_institution_ids":["https://openalex.org/I86987016"],"apc_list":{"value":2290,"currency":"EUR","value_usd":2890},"apc_paid":{"value":2290,"currency":"EUR","value_usd":2890},"fwci":1.9108,"has_fulltext":true,"cited_by_count":19,"citation_normalized_percentile":{"value":0.8813331,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":98},"biblio":{"volume":"2","issue":"5","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10951","display_name":"Cryptographic Implementations and Security","score":0.9998000264167786,"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/T10951","display_name":"Cryptographic Implementations and Security","score":0.9998000264167786,"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/T12122","display_name":"Physical Unclonable Functions (PUFs) and Hardware Security","score":0.9977999925613403,"subfield":{"id":"https://openalex.org/subfields/1708","display_name":"Hardware and Architecture"},"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/T11241","display_name":"Advanced Malware Detection Techniques","score":0.9772999882698059,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/side-channel-attack","display_name":"Side channel attack","score":0.8945838212966919},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8199301958084106},{"id":"https://openalex.org/keywords/power-analysis","display_name":"Power analysis","score":0.6015734672546387},{"id":"https://openalex.org/keywords/implementation","display_name":"Implementation","score":0.5866336226463318},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.5425307154655457},{"id":"https://openalex.org/keywords/field-programmable-gate-array","display_name":"Field-programmable gate array","score":0.5319576263427734},{"id":"https://openalex.org/keywords/cryptography","display_name":"Cryptography","score":0.5290336012840271},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5035678744316101},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.48064982891082764},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.47891175746917725},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.4610063433647156},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.45702454447746277},{"id":"https://openalex.org/keywords/aes-implementations","display_name":"AES implementations","score":0.45335355401039124},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4157188832759857},{"id":"https://openalex.org/keywords/advanced-encryption-standard","display_name":"Advanced Encryption Standard","score":0.3621363043785095},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.30270057916641235},{"id":"https://openalex.org/keywords/embedded-system","display_name":"Embedded system","score":0.22414201498031616}],"concepts":[{"id":"https://openalex.org/C49289754","wikidata":"https://www.wikidata.org/wiki/Q2267081","display_name":"Side channel attack","level":3,"score":0.8945838212966919},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8199301958084106},{"id":"https://openalex.org/C71743495","wikidata":"https://www.wikidata.org/wiki/Q2845210","display_name":"Power analysis","level":3,"score":0.6015734672546387},{"id":"https://openalex.org/C26713055","wikidata":"https://www.wikidata.org/wiki/Q245962","display_name":"Implementation","level":2,"score":0.5866336226463318},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.5425307154655457},{"id":"https://openalex.org/C42935608","wikidata":"https://www.wikidata.org/wiki/Q190411","display_name":"Field-programmable gate array","level":2,"score":0.5319576263427734},{"id":"https://openalex.org/C178489894","wikidata":"https://www.wikidata.org/wiki/Q8789","display_name":"Cryptography","level":2,"score":0.5290336012840271},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5035678744316101},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.48064982891082764},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.47891175746917725},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.4610063433647156},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.45702454447746277},{"id":"https://openalex.org/C46331935","wikidata":"https://www.wikidata.org/wiki/Q4651362","display_name":"AES implementations","level":4,"score":0.45335355401039124},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4157188832759857},{"id":"https://openalex.org/C94520183","wikidata":"https://www.wikidata.org/wiki/Q190746","display_name":"Advanced Encryption Standard","level":3,"score":0.3621363043785095},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.30270057916641235},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.22414201498031616},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","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},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1007/s42979-021-00755-w","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s42979-021-00755-w","pdf_url":"https://link.springer.com/content/pdf/10.1007/s42979-021-00755-w.pdf","source":{"id":"https://openalex.org/S4210174798","display_name":"SN Computer Science","issn_l":"2661-8907","issn":["2661-8907","2662-995X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SN Computer Science","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1007/s42979-021-00755-w","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s42979-021-00755-w","pdf_url":"https://link.springer.com/content/pdf/10.1007/s42979-021-00755-w.pdf","source":{"id":"https://openalex.org/S4210174798","display_name":"SN Computer Science","issn_l":"2661-8907","issn":["2661-8907","2662-995X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SN Computer Science","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/7","display_name":"Affordable and clean energy","score":0.44999998807907104}],"awards":[{"id":"https://openalex.org/G4140816807","display_name":null,"funder_award_id":"2018-04482","funder_id":"https://openalex.org/F4320322581","funder_display_name":"Vetenskapsr\u00e5det"},{"id":"https://openalex.org/G712881263","display_name":null,"funder_award_id":"2018-","funder_id":"https://openalex.org/F4320322581","funder_display_name":"Vetenskapsr\u00e5det"}],"funders":[{"id":"https://openalex.org/F4320322509","display_name":"Kungliga Tekniska H\u00f6gskolan","ror":"https://ror.org/026vcq606"},{"id":"https://openalex.org/F4320322581","display_name":"Vetenskapsr\u00e5det","ror":"https://ror.org/03zttf063"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3182276460.pdf","grobid_xml":"https://content.openalex.org/works/W3182276460.grobid-xml"},"referenced_works_count":45,"referenced_works":["https://openalex.org/W29626722","https://openalex.org/W74920699","https://openalex.org/W402118205","https://openalex.org/W1556212265","https://openalex.org/W1560027954","https://openalex.org/W1562542037","https://openalex.org/W1849277567","https://openalex.org/W2100805904","https://openalex.org/W2112796928","https://openalex.org/W2145073242","https://openalex.org/W2148157928","https://openalex.org/W2273713505","https://openalex.org/W2293479964","https://openalex.org/W2556867355","https://openalex.org/W2557283755","https://openalex.org/W2559230071","https://openalex.org/W2602337255","https://openalex.org/W2746796098","https://openalex.org/W2809979774","https://openalex.org/W2810943746","https://openalex.org/W2903143476","https://openalex.org/W2922474087","https://openalex.org/W2945476062","https://openalex.org/W2953355178","https://openalex.org/W2954035222","https://openalex.org/W2955805282","https://openalex.org/W2963108767","https://openalex.org/W2981862476","https://openalex.org/W2990306706","https://openalex.org/W2990826112","https://openalex.org/W2996022685","https://openalex.org/W3009026932","https://openalex.org/W3046863412","https://openalex.org/W3080202734","https://openalex.org/W3089979403","https://openalex.org/W3090829831","https://openalex.org/W3093679526","https://openalex.org/W3095249062","https://openalex.org/W3096110808","https://openalex.org/W3119473183","https://openalex.org/W3126247501","https://openalex.org/W3162738495","https://openalex.org/W3209546151","https://openalex.org/W4245524709","https://openalex.org/W4289115712"],"related_works":["https://openalex.org/W2029006445","https://openalex.org/W4255075415","https://openalex.org/W2384300182","https://openalex.org/W2100546736","https://openalex.org/W169923757","https://openalex.org/W2059218952","https://openalex.org/W1998454494","https://openalex.org/W4253685677","https://openalex.org/W2133707980","https://openalex.org/W2369513516"],"abstract_inverted_index":{"Abstract":[0],"Side-channel":[1],"attacks":[2,27],"have":[3,55],"become":[4],"a":[5,29,70],"realistic":[6],"threat":[7],"to":[8,34,91,100,111],"implementations":[9,39],"of":[10,17,22,40,46,108,119,131],"cryptographic":[11,41],"algorithms,":[12],"especially":[13],"with":[14],"the":[15,36,51,61,74,93,106,113,134],"help":[16],"deep-learning":[18,25],"techniques.":[19],"The":[20,43],"majority":[21],"recently":[23],"demonstrated":[24],"side-channel":[26,62],"use":[28],"single":[30],"neural":[31],"network":[32],"classifier":[33],"extract":[35],"secret":[37],"from":[38,115],"algorithms.":[42],"potential":[44],"benefits":[45],"combining":[47],"multiple":[48,78],"classifiers":[49,132],"using":[50],"ensemble":[52],"learning":[53],"method":[54],"not":[56,128],"been":[57],"fully":[58],"explored":[59],"in":[60,76,89],"attack\u2019s":[63],"context.":[64],"In":[65],"this":[66],"paper,":[67],"we":[68],"propose":[69],"tandem":[71],"approach":[72,97],"for":[73],"attack":[75,84,135],"which":[77],"models":[79],"are":[80,87],"trained":[81],"on":[82,104],"different":[83],"points":[85],"but":[86],"used":[88],"parallel":[90],"recover":[92,112],"key.":[94],"Such":[95],"an":[96,116],"allows":[98],"us":[99],"considerably":[101],"reduce":[102],"(33.5%":[103],"average)":[105],"number":[107],"traces":[109],"required":[110],"key":[114],"FPGA":[117],"implementation":[118],"AES":[120],"by":[121],"power":[122],"analysis.":[123],"We":[124],"also":[125],"show":[126],"that":[127],"all":[129],"combinations":[130],"improve":[133],"efficiency.":[136]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":2}],"updated_date":"2026-06-19T15:47:20.252518","created_date":"2025-10-10T00:00:00"}