{"id":"https://openalex.org/W4312904563","doi":"https://doi.org/10.1109/les.2022.3213443","title":"Efficient Nonprofiled Side-Channel Attack Using Multi-Output Classification Neural Network","display_name":"Efficient Nonprofiled Side-Channel Attack Using Multi-Output Classification Neural Network","publication_year":2022,"publication_date":"2022-10-10","ids":{"openalex":"https://openalex.org/W4312904563","doi":"https://doi.org/10.1109/les.2022.3213443"},"language":"en","primary_location":{"id":"doi:10.1109/les.2022.3213443","is_oa":false,"landing_page_url":"https://doi.org/10.1109/les.2022.3213443","pdf_url":null,"source":{"id":"https://openalex.org/S22443479","display_name":"IEEE Embedded Systems Letters","issn_l":"1943-0663","issn":["1943-0663","1943-0671"],"is_oa":false,"is_in_doaj":false,"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 Embedded Systems Letters","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/A5082516246","display_name":"Van\u2010Phuc Hoang","orcid":"https://orcid.org/0000-0003-0944-8701"},"institutions":[{"id":"https://openalex.org/I131359167","display_name":"Le Quy Don Technical University","ror":"https://ror.org/04wgyjv21","country_code":"VN","type":"education","lineage":["https://openalex.org/I131359167"]}],"countries":["VN"],"is_corresponding":false,"raw_author_name":"Van-Phuc Hoang","raw_affiliation_strings":["Institute of System Integration, Le Quy Don Technical University, Hanoi, Vietnam","Faculty of Communications and Radar, Vietnam Naval Academy, Nha Trang, Vietnam"],"raw_orcid":"https://orcid.org/0000-0003-0944-8701","affiliations":[{"raw_affiliation_string":"Institute of System Integration, Le Quy Don Technical University, Hanoi, Vietnam","institution_ids":["https://openalex.org/I131359167"]},{"raw_affiliation_string":"Faculty of Communications and Radar, Vietnam Naval Academy, Nha Trang, Vietnam","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088968161","display_name":"Ngoc\u2010Tuan Do","orcid":"https://orcid.org/0000-0002-9195-658X"},"institutions":[{"id":"https://openalex.org/I131359167","display_name":"Le Quy Don Technical University","ror":"https://ror.org/04wgyjv21","country_code":"VN","type":"education","lineage":["https://openalex.org/I131359167"]}],"countries":["VN"],"is_corresponding":false,"raw_author_name":"Ngoc-Tuan Do","raw_affiliation_strings":["Institute of System Integration, Le Quy Don Technical University, Hanoi, Vietnam","Faculty of Communications and Radar, Vietnam Naval Academy, Nha Trang, Vietnam"],"raw_orcid":"https://orcid.org/0000-0002-9195-658X","affiliations":[{"raw_affiliation_string":"Institute of System Integration, Le Quy Don Technical University, Hanoi, Vietnam","institution_ids":["https://openalex.org/I131359167"]},{"raw_affiliation_string":"Faculty of Communications and Radar, Vietnam Naval Academy, Nha Trang, Vietnam","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5035179778","display_name":"Van\u2010Sang Doan","orcid":"https://orcid.org/0000-0001-9048-4341"},"institutions":[{"id":"https://openalex.org/I131359167","display_name":"Le Quy Don Technical University","ror":"https://ror.org/04wgyjv21","country_code":"VN","type":"education","lineage":["https://openalex.org/I131359167"]}],"countries":["VN"],"is_corresponding":false,"raw_author_name":"Van Sang Doan","raw_affiliation_strings":["Institute of System Integration, Le Quy Don Technical University, Hanoi, Vietnam","Faculty of Communications and Radar, Vietnam Naval Academy, Nha Trang, Vietnam"],"raw_orcid":"https://orcid.org/0000-0001-9048-4341","affiliations":[{"raw_affiliation_string":"Institute of System Integration, Le Quy Don Technical University, Hanoi, Vietnam","institution_ids":["https://openalex.org/I131359167"]},{"raw_affiliation_string":"Faculty of Communications and Radar, Vietnam Naval Academy, Nha Trang, Vietnam","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I131359167"],"apc_list":null,"apc_paid":null,"fwci":1.3121,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":{"value":0.83717988,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":98},"biblio":{"volume":"15","issue":"3","first_page":"145","last_page":"148"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10951","display_name":"Cryptographic Implementations and Security","score":0.9984999895095825,"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":0.9984999895095825,"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/T11241","display_name":"Advanced Malware Detection Techniques","score":0.9904999732971191,"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/T12122","display_name":"Physical Unclonable Functions (PUFs) and Hardware Security","score":0.9765999913215637,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8878830075263977},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.575083315372467},{"id":"https://openalex.org/keywords/masking","display_name":"Masking (illustration)","score":0.5468258261680603},{"id":"https://openalex.org/keywords/synchronization","display_name":"Synchronization (alternating current)","score":0.540223240852356},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4991943836212158},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.49448394775390625},{"id":"https://openalex.org/keywords/side-channel-attack","display_name":"Side channel attack","score":0.49211472272872925},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4861302077770233},{"id":"https://openalex.org/keywords/trace","display_name":"TRACE (psycholinguistics)","score":0.47706902027130127},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.4718579947948456},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4636121690273285},{"id":"https://openalex.org/keywords/multilayer-perceptron","display_name":"Multilayer perceptron","score":0.45571091771125793},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4345707297325134},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.4332120716571808},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.32121792435646057},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.26165783405303955},{"id":"https://openalex.org/keywords/cryptography","display_name":"Cryptography","score":0.21925082802772522},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.14886194467544556},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.11229044198989868}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8878830075263977},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.575083315372467},{"id":"https://openalex.org/C2777402240","wikidata":"https://www.wikidata.org/wiki/Q6783436","display_name":"Masking (illustration)","level":2,"score":0.5468258261680603},{"id":"https://openalex.org/C2778562939","wikidata":"https://www.wikidata.org/wiki/Q1298791","display_name":"Synchronization (alternating current)","level":3,"score":0.540223240852356},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4991943836212158},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.49448394775390625},{"id":"https://openalex.org/C49289754","wikidata":"https://www.wikidata.org/wiki/Q2267081","display_name":"Side channel attack","level":3,"score":0.49211472272872925},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4861302077770233},{"id":"https://openalex.org/C75291252","wikidata":"https://www.wikidata.org/wiki/Q1315756","display_name":"TRACE (psycholinguistics)","level":2,"score":0.47706902027130127},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.4718579947948456},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4636121690273285},{"id":"https://openalex.org/C179717631","wikidata":"https://www.wikidata.org/wiki/Q2991667","display_name":"Multilayer perceptron","level":3,"score":0.45571091771125793},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4345707297325134},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.4332120716571808},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.32121792435646057},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.26165783405303955},{"id":"https://openalex.org/C178489894","wikidata":"https://www.wikidata.org/wiki/Q8789","display_name":"Cryptography","level":2,"score":0.21925082802772522},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.14886194467544556},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.11229044198989868},{"id":"https://openalex.org/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0},{"id":"https://openalex.org/C153349607","wikidata":"https://www.wikidata.org/wiki/Q36649","display_name":"Visual arts","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/les.2022.3213443","is_oa":false,"landing_page_url":"https://doi.org/10.1109/les.2022.3213443","pdf_url":null,"source":{"id":"https://openalex.org/S22443479","display_name":"IEEE Embedded Systems Letters","issn_l":"1943-0663","issn":["1943-0663","1943-0671"],"is_oa":false,"is_in_doaj":false,"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 Embedded Systems Letters","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2584614727","display_name":null,"funder_award_id":"102.02-2020.14","funder_id":"https://openalex.org/F4320313223","funder_display_name":"Vietnam Academy of Science and Technology"}],"funders":[{"id":"https://openalex.org/F4320313223","display_name":"Vietnam Academy of Science and Technology","ror":"https://ror.org/02wsd5p50"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W29626722","https://openalex.org/W1599906532","https://openalex.org/W2532602199","https://openalex.org/W2953355178","https://openalex.org/W2982857584","https://openalex.org/W3008730847","https://openalex.org/W3211095618","https://openalex.org/W3212334786","https://openalex.org/W3212633227","https://openalex.org/W4206230818","https://openalex.org/W4251361495","https://openalex.org/W6758101381","https://openalex.org/W6764477545"],"related_works":["https://openalex.org/W4323824501","https://openalex.org/W2355552010","https://openalex.org/W2136687465","https://openalex.org/W3016859066","https://openalex.org/W5280335","https://openalex.org/W4200321003","https://openalex.org/W4400339423","https://openalex.org/W3215861253","https://openalex.org/W2900215011","https://openalex.org/W2354319712"],"abstract_inverted_index":{"Differential":[0],"deep":[1],"learning":[2],"analysis":[3],"(DDLA)":[4],"is":[5],"the":[6,24,41,86,96,126,129],"first":[7],"deep-learning-based":[8],"nonprofiled":[9,33],"side-channel":[10],"attack":[11,87],"(SCA)":[12],"on":[13,74],"embedded":[14],"systems.":[15],"However,":[16],"DDLA":[17,94],"requires":[18],"many":[19],"training":[20],"processes":[21],"to":[22,39,89,133],"distinguish":[23],"correct":[25],"key.":[26],"In":[27,104],"this":[28],"letter,":[29],"we":[30],"introduce":[31],"a":[32,45,50,117],"SCA":[34,59],"technique":[35],"using":[36],"multi-output":[37,46,51],"classification":[38],"mitigate":[40],"aforementioned":[42],"issue.":[43],"Specifically,":[44],"multilayer":[47],"perceptron":[48],"and":[49,67,100,109,135],"convolutional":[52],"neural":[53],"network":[54],"are":[55],"introduced":[56],"against":[57],"various":[58],"protected":[60],"schemes,":[61],"such":[62],"as":[63],"masking,":[64],"noise":[65,110],"generation,":[66],"trace":[68],"de-synchronization":[69,101],"countermeasures.":[70],"The":[71],"experimental":[72],"results":[73],"different":[75],"power":[76],"side":[77],"channel":[78],"datasets":[79],"have":[80],"clarified":[81],"that":[82],"our":[83,113],"model":[84,115],"performs":[85],"up":[88],"9\u201330":[90],"times":[91],"faster":[92],"than":[93],"in":[95,125],"case":[97],"of":[98,121,128],"masking":[99,108],"countermeasures,":[102],"respectively.":[103],"addition,":[105],"regarding":[106],"combined":[107],"generation":[111],"countermeasure,":[112],"proposed":[114],"achieves":[116],"higher":[118],"success":[119],"rate":[120],"at":[122],"least":[123],"20%":[124],"cases":[127],"standard":[130],"deviation":[131],"equal":[132],"1.0":[134],"1.5.":[136]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":2}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}