{"id":"https://openalex.org/W3126247501","doi":"https://doi.org/10.46586/tches.v2021.i3.677-707","title":"Reinforcement Learning for Hyperparameter Tuning in Deep Learning-based Side-channel Analysis","display_name":"Reinforcement Learning for Hyperparameter Tuning in Deep Learning-based Side-channel Analysis","publication_year":2021,"publication_date":"2021-07-09","ids":{"openalex":"https://openalex.org/W3126247501","doi":"https://doi.org/10.46586/tches.v2021.i3.677-707","mag":"3126247501"},"language":"en","primary_location":{"id":"doi:10.46586/tches.v2021.i3.677-707","is_oa":true,"landing_page_url":"https://doi.org/10.46586/tches.v2021.i3.677-707","pdf_url":"https://tches.iacr.org/index.php/TCHES/article/download/8989/8566","source":{"id":"https://openalex.org/S4210207404","display_name":"IACR Transactions on Cryptographic Hardware and Embedded Systems","issn_l":"2569-2925","issn":["2569-2925"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IACR Transactions on Cryptographic Hardware and Embedded Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://tches.iacr.org/index.php/TCHES/article/download/8989/8566","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5023700092","display_name":"Jorai Rijsdijk","orcid":"https://orcid.org/0000-0002-7188-1744"},"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":false,"raw_author_name":"Jorai Rijsdijk","raw_affiliation_strings":["Delft University of Technology, The Netherlands"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Delft University of Technology, The Netherlands","institution_ids":["https://openalex.org/I98358874"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5045570758","display_name":"Lichao Wu","orcid":"https://orcid.org/0000-0002-7139-732X"},"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":false,"raw_author_name":"Lichao Wu","raw_affiliation_strings":["Delft University of Technology, The Netherlands"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Delft University of Technology, The Netherlands","institution_ids":["https://openalex.org/I98358874"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5082617536","display_name":"Guilherme Perin","orcid":"https://orcid.org/0000-0003-3799-7636"},"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":false,"raw_author_name":"Guilherme Perin","raw_affiliation_strings":["Delft University of Technology, The Netherlands"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Delft University of Technology, The Netherlands","institution_ids":["https://openalex.org/I98358874"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5024072796","display_name":"Stjepan Picek","orcid":"https://orcid.org/0000-0001-7509-4337"},"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":false,"raw_author_name":"Stjepan Picek","raw_affiliation_strings":["Delft University of Technology, The Netherlands"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Delft University of Technology, The Netherlands","institution_ids":["https://openalex.org/I98358874"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I98358874"],"apc_list":null,"apc_paid":null,"fwci":8.1882,"has_fulltext":true,"cited_by_count":137,"citation_normalized_percentile":{"value":0.98511463,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"677","last_page":"707"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12495","display_name":"Electrostatic Discharge in Electronics","score":0.9904000163078308,"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"}},"topics":[{"id":"https://openalex.org/T12495","display_name":"Electrostatic Discharge in Electronics","score":0.9904000163078308,"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/T12357","display_name":"Digital Media Forensic Detection","score":0.9857000112533569,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T10951","display_name":"Cryptographic Implementations and Security","score":0.9761000275611877,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/hyperparameter","display_name":"Hyperparameter","score":0.8707717657089233},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.8509750962257385},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8159589767456055},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7196134328842163},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6411821246147156},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6355403661727905},{"id":"https://openalex.org/keywords/hyperparameter-optimization","display_name":"Hyperparameter optimization","score":0.6219347715377808},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5908001661300659},{"id":"https://openalex.org/keywords/perceptron","display_name":"Perceptron","score":0.5640215277671814},{"id":"https://openalex.org/keywords/source-code","display_name":"Source code","score":0.4845484793186188},{"id":"https://openalex.org/keywords/learning-classifier-system","display_name":"Learning classifier system","score":0.44907575845718384},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4232419729232788},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4128257930278778}],"concepts":[{"id":"https://openalex.org/C8642999","wikidata":"https://www.wikidata.org/wiki/Q4171168","display_name":"Hyperparameter","level":2,"score":0.8707717657089233},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.8509750962257385},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8159589767456055},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7196134328842163},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6411821246147156},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6355403661727905},{"id":"https://openalex.org/C10485038","wikidata":"https://www.wikidata.org/wiki/Q48996162","display_name":"Hyperparameter optimization","level":3,"score":0.6219347715377808},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5908001661300659},{"id":"https://openalex.org/C60908668","wikidata":"https://www.wikidata.org/wiki/Q690207","display_name":"Perceptron","level":3,"score":0.5640215277671814},{"id":"https://openalex.org/C43126263","wikidata":"https://www.wikidata.org/wiki/Q128751","display_name":"Source code","level":2,"score":0.4845484793186188},{"id":"https://openalex.org/C199190896","wikidata":"https://www.wikidata.org/wiki/Q3509276","display_name":"Learning classifier system","level":3,"score":0.44907575845718384},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4232419729232788},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4128257930278778},{"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/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"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":3,"locations":[{"id":"doi:10.46586/tches.v2021.i3.677-707","is_oa":true,"landing_page_url":"https://doi.org/10.46586/tches.v2021.i3.677-707","pdf_url":"https://tches.iacr.org/index.php/TCHES/article/download/8989/8566","source":{"id":"https://openalex.org/S4210207404","display_name":"IACR Transactions on Cryptographic Hardware and Embedded Systems","issn_l":"2569-2925","issn":["2569-2925"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IACR Transactions on Cryptographic Hardware and Embedded Systems","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:b7af900cc06f4925a756ba55fa323f7c","is_oa":true,"landing_page_url":"https://doaj.org/article/b7af900cc06f4925a756ba55fa323f7c","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":"Transactions on Cryptographic Hardware and Embedded Systems, Vol 2021, Iss 3 (2021)","raw_type":"article"},{"id":"pmh:oai:tudelft.nl:uuid:33d86a53-21c4-4e41-97c7-b42fbbf53b5f","is_oa":false,"landing_page_url":"http://resolver.tudelft.nl/uuid:33d86a53-21c4-4e41-97c7-b42fbbf53b5f","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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"journal article"}],"best_oa_location":{"id":"doi:10.46586/tches.v2021.i3.677-707","is_oa":true,"landing_page_url":"https://doi.org/10.46586/tches.v2021.i3.677-707","pdf_url":"https://tches.iacr.org/index.php/TCHES/article/download/8989/8566","source":{"id":"https://openalex.org/S4210207404","display_name":"IACR Transactions on Cryptographic Hardware and Embedded Systems","issn_l":"2569-2925","issn":["2569-2925"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IACR Transactions on Cryptographic Hardware and Embedded Systems","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3126247501.pdf","grobid_xml":"https://content.openalex.org/works/W3126247501.grobid-xml"},"referenced_works_count":44,"referenced_works":["https://openalex.org/W41554520","https://openalex.org/W293732945","https://openalex.org/W1560027954","https://openalex.org/W1752847028","https://openalex.org/W1836465849","https://openalex.org/W1993482360","https://openalex.org/W2118686230","https://openalex.org/W2404161242","https://openalex.org/W2553303224","https://openalex.org/W2556833785","https://openalex.org/W2556867355","https://openalex.org/W2734509410","https://openalex.org/W2746796098","https://openalex.org/W2758683192","https://openalex.org/W2770836202","https://openalex.org/W2810943746","https://openalex.org/W2903143476","https://openalex.org/W2907922678","https://openalex.org/W2909124973","https://openalex.org/W2955506029","https://openalex.org/W2964054038","https://openalex.org/W2990296674","https://openalex.org/W2996022685","https://openalex.org/W3008439737","https://openalex.org/W3011120880","https://openalex.org/W3011591403","https://openalex.org/W3034141264","https://openalex.org/W3046385973","https://openalex.org/W3046682795","https://openalex.org/W3046730596","https://openalex.org/W3081745170","https://openalex.org/W3092825376","https://openalex.org/W3095249062","https://openalex.org/W3096110808","https://openalex.org/W3185518807","https://openalex.org/W4230633622","https://openalex.org/W4239510810","https://openalex.org/W4239750483","https://openalex.org/W4241389749","https://openalex.org/W4245524709","https://openalex.org/W4289552067","https://openalex.org/W4295185264","https://openalex.org/W4301972454","https://openalex.org/W4382322519"],"related_works":["https://openalex.org/W2953665647","https://openalex.org/W4281646320","https://openalex.org/W4205712847","https://openalex.org/W3169687406","https://openalex.org/W4388119537","https://openalex.org/W3014750173","https://openalex.org/W3114025147","https://openalex.org/W4287818966","https://openalex.org/W3192751261","https://openalex.org/W1663203009"],"abstract_inverted_index":{"Deep":[0],"learning":[1,49,106,150],"represents":[2],"a":[3,53,70],"powerful":[4],"set":[5],"of":[6,55,163,182],"techniques":[7,50,92],"for":[8,95],"profiling":[9],"sidechannel":[10],"analysis.":[11],"The":[12],"results":[13,66,146],"in":[14,73],"the":[15,75,82,96,109,119,145,188],"last":[16],"few":[17],"years":[18],"show":[19,147],"that":[20,47,62,127,148,168],"neural":[21,29,111,154],"network":[22,112],"architectures":[23,186],"like":[24],"multilayer":[25],"perceptron":[26],"and":[27,122,140,173],"convolutional":[28,110,153],"networks":[30,155],"give":[31],"strong":[32],"attack":[33,65],"performance":[34,158],"where":[35,144],"it":[36,59],"is":[37,60,78,171],"possible":[38],"to":[39,57,93,103,107,178],"break":[40],"targets":[41],"protected":[42],"with":[43,69],"various":[44],"countermeasures.":[45],"Considering":[46],"deep":[48],"commonly":[51,85,137],"have":[52],"plethora":[54],"hyperparameters":[56],"tune,":[58],"clear":[61],"such":[63],"top":[64,157],"can":[67,151,174],"come":[68],"high":[71],"price":[72],"preparing":[74],"attack.":[76],"This":[77],"especially":[79],"problematic":[80],"as":[81],"side-channel":[83,129],"community":[84],"uses":[86],"random":[87],"search":[88,91],"or":[89],"grid":[90],"look":[94],"best":[97],"hyperparameters.In":[98],"this":[99],"paper,":[100],"we":[101,117,193],"propose":[102],"use":[104,128],"reinforcement":[105,149],"tune":[108],"hyperparameters.":[113],"In":[114],"our":[115,169,183,195],"framework,":[116],"investigate":[118],"Q-Learning":[120],"paradigm":[121],"develop":[123],"two":[124,141],"reward":[125],"functions":[126],"metrics.":[130],"We":[131,166],"mount":[132],"an":[133],"investigation":[134],"on":[135],"three":[136],"used":[138],"datasets":[139],"leakage":[142],"models":[143],"find":[152],"exhibiting":[156],"while":[159],"having":[160],"small":[161],"numbers":[162],"trainable":[164],"parameters.":[165],"note":[167],"approach":[170],"automated":[172],"be":[175],"easily":[176],"adapted":[177],"different":[179],"datasets.":[180],"Several":[181],"newly":[184],"developed":[185],"outperform":[187],"current":[189],"state-of-the-art":[190],"results.":[191],"Finally,":[192],"make":[194],"source":[196],"code":[197],"publicly":[198],"available.":[199],"https://github.com/AISyLab/Reinforcement-Learning-for-SCA":[200]},"counts_by_year":[{"year":2026,"cited_by_count":8},{"year":2025,"cited_by_count":27},{"year":2024,"cited_by_count":28},{"year":2023,"cited_by_count":34},{"year":2022,"cited_by_count":34},{"year":2021,"cited_by_count":6}],"updated_date":"2026-07-15T18:14:33.161393","created_date":"2025-10-10T00:00:00"}