{"id":"https://openalex.org/W4385071055","doi":"https://doi.org/10.1007/s13389-023-00330-4","title":"Autoencoder-enabled model portability for reducing hyperparameter tuning efforts in side-channel analysis","display_name":"Autoencoder-enabled model portability for reducing hyperparameter tuning efforts in side-channel analysis","publication_year":2023,"publication_date":"2023-07-21","ids":{"openalex":"https://openalex.org/W4385071055","doi":"https://doi.org/10.1007/s13389-023-00330-4"},"language":"en","primary_location":{"id":"doi:10.1007/s13389-023-00330-4","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s13389-023-00330-4","pdf_url":"https://link.springer.com/content/pdf/10.1007/s13389-023-00330-4.pdf","source":{"id":"https://openalex.org/S2764800400","display_name":"Journal of Cryptographic Engineering","issn_l":"2190-8508","issn":["2190-8508","2190-8516"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","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":"Journal of Cryptographic Engineering","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/s13389-023-00330-4.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5058744435","display_name":"Marina Kr\u010dek","orcid":"https://orcid.org/0000-0001-8475-1853"},"institutions":[{"id":"https://openalex.org/I98358874","display_name":"Delft University of Technology","ror":"https://ror.org/02e2c7k09","country_code":"NL","type":"education","lineage":["https://openalex.org/I98358874"]}],"countries":["NL"],"is_corresponding":true,"raw_author_name":"Marina Kr\u010dek","raw_affiliation_strings":["Delft University of Technology, Mekelweg 2, Delft, The Netherlands"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Delft University of Technology, Mekelweg 2, Delft, The Netherlands","institution_ids":["https://openalex.org/I98358874"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5082617536","display_name":"Guilherme Perin","orcid":"https://orcid.org/0000-0003-3799-7636"},"institutions":[{"id":"https://openalex.org/I121797337","display_name":"Leiden University","ror":"https://ror.org/027bh9e22","country_code":"NL","type":"education","lineage":["https://openalex.org/I121797337"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"Guilherme Perin","raw_affiliation_strings":["Leiden University, Rapenburg 70, Leiden, The Netherlands"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Leiden University, Rapenburg 70, Leiden, The Netherlands","institution_ids":["https://openalex.org/I121797337"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5058744435"],"corresponding_institution_ids":["https://openalex.org/I98358874"],"apc_list":{"value":2390,"currency":"EUR","value_usd":2990},"apc_paid":{"value":2390,"currency":"EUR","value_usd":2990},"fwci":0.6509,"has_fulltext":true,"cited_by_count":4,"citation_normalized_percentile":{"value":0.74549006,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":"14","issue":"3","first_page":"475","last_page":"497"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10951","display_name":"Cryptographic Implementations and Security","score":0.9969000220298767,"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":0.9969000220298767,"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/T12495","display_name":"Electrostatic Discharge in Electronics","score":0.9824000000953674,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11241","display_name":"Advanced Malware Detection Techniques","score":0.9801999926567078,"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/hyperparameter","display_name":"Hyperparameter","score":0.8890384435653687},{"id":"https://openalex.org/keywords/profiling","display_name":"Profiling (computer programming)","score":0.8109222650527954},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7982645034790039},{"id":"https://openalex.org/keywords/software-portability","display_name":"Software portability","score":0.7613488435745239},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6465201377868652},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6057528257369995},{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.547137975692749},{"id":"https://openalex.org/keywords/hyperparameter-optimization","display_name":"Hyperparameter optimization","score":0.4828663170337677},{"id":"https://openalex.org/keywords/dimensionality-reduction","display_name":"Dimensionality reduction","score":0.44131767749786377},{"id":"https://openalex.org/keywords/curse-of-dimensionality","display_name":"Curse of dimensionality","score":0.42422258853912354},{"id":"https://openalex.org/keywords/preprocessor","display_name":"Preprocessor","score":0.41743335127830505},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.38454484939575195},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3226741850376129},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.2777290940284729}],"concepts":[{"id":"https://openalex.org/C8642999","wikidata":"https://www.wikidata.org/wiki/Q4171168","display_name":"Hyperparameter","level":2,"score":0.8890384435653687},{"id":"https://openalex.org/C187191949","wikidata":"https://www.wikidata.org/wiki/Q1138496","display_name":"Profiling (computer programming)","level":2,"score":0.8109222650527954},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7982645034790039},{"id":"https://openalex.org/C63000827","wikidata":"https://www.wikidata.org/wiki/Q3080428","display_name":"Software portability","level":2,"score":0.7613488435745239},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6465201377868652},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6057528257369995},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.547137975692749},{"id":"https://openalex.org/C10485038","wikidata":"https://www.wikidata.org/wiki/Q48996162","display_name":"Hyperparameter optimization","level":3,"score":0.4828663170337677},{"id":"https://openalex.org/C70518039","wikidata":"https://www.wikidata.org/wiki/Q16000077","display_name":"Dimensionality reduction","level":2,"score":0.44131767749786377},{"id":"https://openalex.org/C111030470","wikidata":"https://www.wikidata.org/wiki/Q1430460","display_name":"Curse of dimensionality","level":2,"score":0.42422258853912354},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.41743335127830505},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.38454484939575195},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3226741850376129},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.2777290940284729},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"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":2,"locations":[{"id":"doi:10.1007/s13389-023-00330-4","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s13389-023-00330-4","pdf_url":"https://link.springer.com/content/pdf/10.1007/s13389-023-00330-4.pdf","source":{"id":"https://openalex.org/S2764800400","display_name":"Journal of Cryptographic Engineering","issn_l":"2190-8508","issn":["2190-8508","2190-8516"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","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":"Journal of Cryptographic Engineering","raw_type":"journal-article"},{"id":"pmh:oai:tudelft.nl:uuid:ef0529dd-1506-4e53-8aba-c9d20909125b","is_oa":true,"landing_page_url":"http://resolver.tudelft.nl/uuid:ef0529dd-1506-4e53-8aba-c9d20909125b","pdf_url":null,"source":{"id":"https://openalex.org/S4306400906","display_name":"Research Repository (Delft University of Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I98358874","host_organization_name":"Delft University of Technology","host_organization_lineage":["https://openalex.org/I98358874"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"journal article"}],"best_oa_location":{"id":"doi:10.1007/s13389-023-00330-4","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s13389-023-00330-4","pdf_url":"https://link.springer.com/content/pdf/10.1007/s13389-023-00330-4.pdf","source":{"id":"https://openalex.org/S2764800400","display_name":"Journal of Cryptographic Engineering","issn_l":"2190-8508","issn":["2190-8508","2190-8516"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","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":"Journal of Cryptographic Engineering","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4385071055.pdf"},"referenced_works_count":33,"referenced_works":["https://openalex.org/W207867780","https://openalex.org/W1489838709","https://openalex.org/W1562542037","https://openalex.org/W1613874182","https://openalex.org/W1752847028","https://openalex.org/W1890612873","https://openalex.org/W2100495367","https://openalex.org/W2154909745","https://openalex.org/W2165698076","https://openalex.org/W2395579298","https://openalex.org/W2746796098","https://openalex.org/W2914572864","https://openalex.org/W2939963136","https://openalex.org/W2945476062","https://openalex.org/W2967098993","https://openalex.org/W2982314978","https://openalex.org/W2990296674","https://openalex.org/W3008439737","https://openalex.org/W3041133507","https://openalex.org/W3096110808","https://openalex.org/W3126247501","https://openalex.org/W3164261842","https://openalex.org/W3166170034","https://openalex.org/W3178245564","https://openalex.org/W3202469603","https://openalex.org/W3202863046","https://openalex.org/W3208177954","https://openalex.org/W4226266650","https://openalex.org/W4241727697","https://openalex.org/W4293024996","https://openalex.org/W4310480138","https://openalex.org/W4390689254","https://openalex.org/W6904124101"],"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/W4287818966","https://openalex.org/W3192751261"],"abstract_inverted_index":{"Abstract":[0],"Hyperparameter":[1],"tuning":[2,31,91,96,104,138,171,218],"represents":[3,150],"one":[4],"of":[5,81,219],"the":[6,20,50,79,89,100,112,119,124,128,151,160,179,201,212,220],"main":[7,35],"challenges":[8],"in":[9,137,181],"deep":[10],"learning-based":[11],"profiling":[12,26,52,82,94,121,162,185,221],"side-channel":[13,18,39],"analysis.":[14],"For":[15],"each":[16,116],"different":[17,45,76,165],"dataset,":[19,102],"typical":[21],"procedure":[22],"to":[23,70],"find":[24],"a":[25,190,206],"model":[27,53,95,122,163,202,222],"is":[28,37,97,106,159,203,223],"applying":[29],"hyperparameter":[30,90,182],"from":[32,41,75],"scratch.":[33],"The":[34],"reason":[36],"that":[38,146,170],"measurements":[40],"various":[42],"targets":[43,77],"contain":[44],"underlying":[46],"leakage":[47],"distributions.":[48],"Consequently,":[49],"same":[51],"hyperparameters":[54],"are":[55],"usually":[56],"not":[57],"equally":[58],"efficient":[59],"for":[60,67,99,111,115,184,205],"other":[61],"targets.":[62],"This":[63],"paper":[64],"considers":[65],"autoencoders":[66,105,172],"dimensionality":[68,195],"reduction":[69,196],"verify":[71,156],"if":[72,200],"encoded":[73,125,143,147],"datasets":[74],"enable":[78],"portability":[80,87,176],"models":[83],"and":[84,103,118,142,174,225],"architectures.":[85],"Successful":[86],"reduces":[88],"efforts":[92,139],"as":[93],"eliminated":[98,224],"new":[101,213],"simpler.":[107],"We":[108],"first":[109],"search":[110,183],"best":[113,120,161],"autoencoder":[114],"dataset":[117,126,207],"when":[123],"becomes":[127],"training":[129,226],"set.":[130],"Our":[131,167],"results":[132,168],"show":[133,169],"no":[134],"significant":[135],"difference":[136],"using":[140],"original":[141,152],"traces,":[144],"meaning":[145],"data":[148],"reliably":[149],"data.":[153],"Next,":[154],"we":[155,188],"how":[157],"portable":[158],"among":[164],"datasets.":[166],"enables":[173],"improves":[175],"while":[177],"reducing":[178],"effort":[180],"models.":[186],"Lastly,":[187],"present":[189],"transfer":[191],"learning":[192],"case":[193],"where":[194],"might":[197],"be":[198],"necessary":[199],"tuned":[204],"with":[208],"fewer":[209],"features":[210],"than":[211],"dataset.":[214],"In":[215],"this":[216],"case,":[217],"time":[227],"reduced.":[228]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1}],"updated_date":"2026-06-13T06:13:01.061226","created_date":"2025-10-10T00:00:00"}