{"id":"https://openalex.org/W3203210388","doi":"https://doi.org/10.1109/access.2021.3117761","title":"Deep K-TSVM: A Novel Profiled Power Side-Channel Attack on AES-128","display_name":"Deep K-TSVM: A Novel Profiled Power Side-Channel Attack on AES-128","publication_year":2021,"publication_date":"2021-01-01","ids":{"openalex":"https://openalex.org/W3203210388","doi":"https://doi.org/10.1109/access.2021.3117761","mag":"3203210388"},"language":"en","primary_location":{"id":"doi:10.1109/access.2021.3117761","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2021.3117761","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/09558769.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/09558769.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5032077568","display_name":"Soroor Ghandali","orcid":null},"institutions":[{"id":"https://openalex.org/I1291425158","display_name":"Google (United States)","ror":"https://ror.org/00njsd438","country_code":"US","type":"company","lineage":["https://openalex.org/I1291425158","https://openalex.org/I4210128969"]},{"id":"https://openalex.org/I16269868","display_name":"Santa Clara University","ror":"https://ror.org/03ypqe447","country_code":"US","type":"education","lineage":["https://openalex.org/I16269868"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Soroor Ghandali","raw_affiliation_strings":["Department of Electrical and computer engineering, Santa clara university, 500 El Camino Real, Santa Clara, California, USA","Google, California, USA","Department of Electrical and Computer Engineering, Santa Clara University, Santa Clara, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and computer engineering, Santa clara university, 500 El Camino Real, Santa Clara, California, USA","institution_ids":["https://openalex.org/I16269868"]},{"raw_affiliation_string":"Google, California, USA","institution_ids":["https://openalex.org/I1291425158"]},{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Santa Clara University, Santa Clara, CA, USA","institution_ids":["https://openalex.org/I16269868"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5086924960","display_name":"Samaneh Ghandali","orcid":null},"institutions":[{"id":"https://openalex.org/I1291425158","display_name":"Google (United States)","ror":"https://ror.org/00njsd438","country_code":"US","type":"company","lineage":["https://openalex.org/I1291425158","https://openalex.org/I4210128969"]},{"id":"https://openalex.org/I16269868","display_name":"Santa Clara University","ror":"https://ror.org/03ypqe447","country_code":"US","type":"education","lineage":["https://openalex.org/I16269868"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Samaneh Ghandali","raw_affiliation_strings":["Department of Electrical and computer engineering, Santa clara university, 500 El Camino Real, Santa Clara, California, USA","Google, California, USA","Google Mountain View CA USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and computer engineering, Santa clara university, 500 El Camino Real, Santa Clara, California, USA","institution_ids":["https://openalex.org/I16269868"]},{"raw_affiliation_string":"Google, California, USA","institution_ids":["https://openalex.org/I1291425158"]},{"raw_affiliation_string":"Google Mountain View CA USA","institution_ids":["https://openalex.org/I1291425158"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5090068474","display_name":"Fatemeh Tehranipoor","orcid":"https://orcid.org/0000-0001-8410-4306"},"institutions":[{"id":"https://openalex.org/I16269868","display_name":"Santa Clara University","ror":"https://ror.org/03ypqe447","country_code":"US","type":"education","lineage":["https://openalex.org/I16269868"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sara Tehranipoor","raw_affiliation_strings":["Department of Electrical and computer engineering, Santa clara university, 500 El Camino Real, Santa Clara, California, USA. (e-mail: ftehranipoor@scu.edu)","Department of Electrical and Computer Engineering, Santa Clara University, Santa Clara, CA, USA"],"raw_orcid":"https://orcid.org/0000-0001-8410-4306","affiliations":[{"raw_affiliation_string":"Department of Electrical and computer engineering, Santa clara university, 500 El Camino Real, Santa Clara, California, USA. (e-mail: ftehranipoor@scu.edu)","institution_ids":["https://openalex.org/I16269868"]},{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Santa Clara University, Santa Clara, CA, USA","institution_ids":["https://openalex.org/I16269868"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":1.9108,"has_fulltext":true,"cited_by_count":18,"citation_normalized_percentile":{"value":0.88282757,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"9","issue":null,"first_page":"136448","last_page":"136458"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10951","display_name":"Cryptographic Implementations and Security","score":0.9995999932289124,"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":0.9995999932289124,"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":0.9948999881744385,"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":0.9873999953269958,"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/computer-science","display_name":"Computer science","score":0.8484433889389038},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6896394491195679},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6114823222160339},{"id":"https://openalex.org/keywords/perceptron","display_name":"Perceptron","score":0.6044273972511292},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5677671432495117},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5316368341445923},{"id":"https://openalex.org/keywords/side-channel-attack","display_name":"Side channel attack","score":0.5016381740570068},{"id":"https://openalex.org/keywords/hyperparameter","display_name":"Hyperparameter","score":0.4957023859024048},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4394402801990509},{"id":"https://openalex.org/keywords/hyperparameter-optimization","display_name":"Hyperparameter optimization","score":0.4323435425758362},{"id":"https://openalex.org/keywords/model-selection","display_name":"Model selection","score":0.42592093348503113},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.41622233390808105},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.3722682595252991},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.27644896507263184},{"id":"https://openalex.org/keywords/cryptography","display_name":"Cryptography","score":0.26084354519844055}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8484433889389038},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6896394491195679},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6114823222160339},{"id":"https://openalex.org/C60908668","wikidata":"https://www.wikidata.org/wiki/Q690207","display_name":"Perceptron","level":3,"score":0.6044273972511292},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5677671432495117},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5316368341445923},{"id":"https://openalex.org/C49289754","wikidata":"https://www.wikidata.org/wiki/Q2267081","display_name":"Side channel attack","level":3,"score":0.5016381740570068},{"id":"https://openalex.org/C8642999","wikidata":"https://www.wikidata.org/wiki/Q4171168","display_name":"Hyperparameter","level":2,"score":0.4957023859024048},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4394402801990509},{"id":"https://openalex.org/C10485038","wikidata":"https://www.wikidata.org/wiki/Q48996162","display_name":"Hyperparameter optimization","level":3,"score":0.4323435425758362},{"id":"https://openalex.org/C93959086","wikidata":"https://www.wikidata.org/wiki/Q6888345","display_name":"Model selection","level":2,"score":0.42592093348503113},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.41622233390808105},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.3722682595252991},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.27644896507263184},{"id":"https://openalex.org/C178489894","wikidata":"https://www.wikidata.org/wiki/Q8789","display_name":"Cryptography","level":2,"score":0.26084354519844055}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2021.3117761","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2021.3117761","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/09558769.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:e6e7f73a39d747908ef49d2f3abdecfb","is_oa":true,"landing_page_url":"https://doaj.org/article/e6e7f73a39d747908ef49d2f3abdecfb","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 9, Pp 136448-136458 (2021)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2021.3117761","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2021.3117761","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/09558769.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3203210388.pdf","grobid_xml":"https://content.openalex.org/works/W3203210388.grobid-xml"},"referenced_works_count":47,"referenced_works":["https://openalex.org/W124803980","https://openalex.org/W182561961","https://openalex.org/W1412796964","https://openalex.org/W1512062395","https://openalex.org/W1873332500","https://openalex.org/W1981401636","https://openalex.org/W1993482360","https://openalex.org/W1995013121","https://openalex.org/W2008071701","https://openalex.org/W2011257923","https://openalex.org/W2012955216","https://openalex.org/W2055556325","https://openalex.org/W2116064496","https://openalex.org/W2120239875","https://openalex.org/W2130073327","https://openalex.org/W2213200328","https://openalex.org/W2556867355","https://openalex.org/W2584571971","https://openalex.org/W2607239406","https://openalex.org/W2734509410","https://openalex.org/W2746796098","https://openalex.org/W2810943746","https://openalex.org/W2903143476","https://openalex.org/W2911074137","https://openalex.org/W2923594358","https://openalex.org/W2928085298","https://openalex.org/W2953355178","https://openalex.org/W2996022685","https://openalex.org/W2996038230","https://openalex.org/W3038883095","https://openalex.org/W3081703780","https://openalex.org/W3138715001","https://openalex.org/W3144619878","https://openalex.org/W3160610815","https://openalex.org/W3209442501","https://openalex.org/W4245524709","https://openalex.org/W4251361495","https://openalex.org/W6628161219","https://openalex.org/W6639175750","https://openalex.org/W6677630571","https://openalex.org/W6752790553","https://openalex.org/W6758658729","https://openalex.org/W6761384861","https://openalex.org/W6771898502","https://openalex.org/W6771987059","https://openalex.org/W6795037245","https://openalex.org/W6802799431"],"related_works":["https://openalex.org/W2953665647","https://openalex.org/W4281646320","https://openalex.org/W4205712847","https://openalex.org/W3169687406","https://openalex.org/W1974336862","https://openalex.org/W4388119537","https://openalex.org/W3014750173","https://openalex.org/W3114025147","https://openalex.org/W1663203009","https://openalex.org/W4396671263"],"abstract_inverted_index":{"The":[0,120,215],"appearance":[1],"of":[2,18,31,41,60,76,118,151,161,187,227,251],"deep":[3,23,44,78,110,167],"neural":[4,45,62,79,197],"networks":[5,198],"for":[6,14,73,148],"Side-Channel":[7,51],"leads":[8],"to":[9,81,157,248],"strong":[10],"power":[11],"analysis":[12,175],"techniques":[13,25],"detecting":[15],"secret":[16],"information":[17],"physical":[19],"cryptography":[20],"implementations.":[21],"Generally,":[22],"learning":[24],"do":[26],"not":[27],"suffer":[28],"the":[29,39,83,92,126,144,149,219,243,249,256,263],"difficulties":[30],"template":[32],"attacks":[33],"such":[34,194],"as":[35,195],"trace":[36,164,235],"misalignment.":[37],"However,":[38],"generalization":[40],"a":[42,61,77,88,101,109,115,132,224,233],"trained":[43],"network":[46,80],"that":[47,218],"can":[48],"accurately":[49],"predict":[50],"leakages":[52],"largely":[53],"depends":[54],"on":[55,173,208],"its":[56,182,188],"adjustable":[57],"variables":[58],"(parameters":[59],"network).":[63],"Although":[64],"pre-training":[65],"is":[66,71,123,155],"no":[67],"longer":[68],"mandatory,":[69],"it":[70],"needed":[72],"parameter":[74],"selection":[75,150],"improve":[82],"success":[84,225],"rate":[85,226],"and":[86,135,176,199,211],"provide":[87],"better":[89],"insight":[90],"into":[91],"network\u2019s":[93],"inner":[94],"functionality.":[95],"In":[96],"this":[97,178],"paper,":[98],"we":[99,142],"propose":[100],"novel":[102],"model":[103,122,168,179,207,254],"via":[104,138],"Twin":[105],"support":[106],"vector":[107],"with":[108,125,232,239],"kernel":[111],"approach":[112,221],"when":[113,261],"targeting":[114],"hardware":[116],"implementation":[117],"AES-128.":[119],"proposed":[121,220],"pre-trained":[124],"Restricted":[127],"Boltzmann":[128],"Machine":[129],"method":[130],"in":[131,165,190],"layer-wise":[133],"manner":[134],"then":[136],"fine-tuned":[137],"gradient":[139],"descent.":[140],"Further,":[141],"used":[143,156],"grid":[145],"search":[146],"technique":[147],"each":[152],"hyperparameter":[153],"which":[154],"compute":[158],"class":[159],"probabilities":[160],"every":[162],"test":[163],"our":[166,174,206,253],"based":[169],"side-channel":[170],"attack.":[171],"Based":[172],"experiments,":[177],"empirically":[180],"shows":[181],"effectiveness":[183],"by":[184],"outperforming":[185],"some":[186],"competitors":[189],"profiling":[191],"attack":[192],"methods":[193],"convolutional":[196],"multilayer":[200],"perceptron":[201],"models.":[202],"We":[203,241],"also":[204],"evaluate":[205],"both":[209],"masked":[210],"unmasked":[212],"AES":[213,265],"implementation.":[214],"results":[216],"indicate":[217],"has":[222],"achieved":[223],"greater":[228],"than":[229],"99%":[230],"even":[231],"single":[234],"using":[236],"Keras":[237],"library":[238],"Tensorflow.":[240],"investigate":[242],"correct":[244],"\u201ckey":[245],"rank\"":[246],"according":[247],"number":[250],"traces;":[252],"reaches":[255],"key":[257],"rank":[258],"\u2264":[259],"10":[260],"attacking":[262],"third":[264],"SBox.":[266]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":8},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
