{"id":"https://openalex.org/W4388958832","doi":"https://doi.org/10.1145/3605769.3623996","title":"Beyond the Last Layer: Deep Feature Loss Functions in Side-channel Analysis","display_name":"Beyond the Last Layer: Deep Feature Loss Functions in Side-channel Analysis","publication_year":2023,"publication_date":"2023-11-23","ids":{"openalex":"https://openalex.org/W4388958832","doi":"https://doi.org/10.1145/3605769.3623996"},"language":"en","primary_location":{"id":"doi:10.1145/3605769.3623996","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3605769.3623996","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3605769.3623996","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2023 Workshop on Attacks and Solutions in Hardware Security","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3605769.3623996","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5041917793","display_name":"Trevor Yap","orcid":"https://orcid.org/0000-0001-8651-574X"},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":true,"raw_author_name":"Trevor Yap","raw_affiliation_strings":["Nanyang Technological University, Singapore, Singapore"],"raw_orcid":"https://orcid.org/0000-0001-8651-574X","affiliations":[{"raw_affiliation_string":"Nanyang Technological University, Singapore, Singapore","institution_ids":["https://openalex.org/I172675005"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024072796","display_name":"Stjepan Picek","orcid":"https://orcid.org/0000-0001-7509-4337"},"institutions":[{"id":"https://openalex.org/I145872427","display_name":"Radboud University Nijmegen","ror":"https://ror.org/016xsfp80","country_code":"NL","type":"education","lineage":["https://openalex.org/I145872427"]},{"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":["Radboud University & Delft University of Technology, Nijmegen and Delft , Netherlands"],"raw_orcid":"https://orcid.org/0000-0001-7509-4337","affiliations":[{"raw_affiliation_string":"Radboud University & Delft University of Technology, Nijmegen and Delft , Netherlands","institution_ids":["https://openalex.org/I98358874","https://openalex.org/I145872427"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5081720773","display_name":"Shivam Bhasin","orcid":"https://orcid.org/0000-0002-6903-5127"},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Shivam Bhasin","raw_affiliation_strings":["Nanyang Technological University, Singapore, Singapore"],"raw_orcid":"https://orcid.org/0000-0002-6903-5127","affiliations":[{"raw_affiliation_string":"Nanyang Technological University, Singapore, Singapore","institution_ids":["https://openalex.org/I172675005"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5041917793"],"corresponding_institution_ids":["https://openalex.org/I172675005"],"apc_list":null,"apc_paid":null,"fwci":0.3532,"has_fulltext":true,"cited_by_count":3,"citation_normalized_percentile":{"value":0.60781499,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"73","last_page":"82"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12357","display_name":"Digital Media Forensic Detection","score":0.9873999953269958,"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"}},"topics":[{"id":"https://openalex.org/T12357","display_name":"Digital Media Forensic Detection","score":0.9873999953269958,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9775999784469604,"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/T11609","display_name":"Geophysical Methods and Applications","score":0.948199987411499,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.7894772887229919},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7309852242469788},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.6184149980545044},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5606659054756165},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.5601145029067993},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5409016013145447},{"id":"https://openalex.org/keywords/side-channel-attack","display_name":"Side channel attack","score":0.5328068733215332},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4773402512073517},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.46162039041519165},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4557371735572815},{"id":"https://openalex.org/keywords/deep-neural-networks","display_name":"Deep neural networks","score":0.4137829542160034},{"id":"https://openalex.org/keywords/profiling","display_name":"Profiling (computer programming)","score":0.4115697145462036},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.30540958046913147},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.1578628420829773}],"concepts":[{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.7894772887229919},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7309852242469788},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.6184149980545044},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5606659054756165},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.5601145029067993},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5409016013145447},{"id":"https://openalex.org/C49289754","wikidata":"https://www.wikidata.org/wiki/Q2267081","display_name":"Side channel attack","level":3,"score":0.5328068733215332},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4773402512073517},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.46162039041519165},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4557371735572815},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.4137829542160034},{"id":"https://openalex.org/C187191949","wikidata":"https://www.wikidata.org/wiki/Q1138496","display_name":"Profiling (computer programming)","level":2,"score":0.4115697145462036},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.30540958046913147},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.1578628420829773},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"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/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C178489894","wikidata":"https://www.wikidata.org/wiki/Q8789","display_name":"Cryptography","level":2,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3605769.3623996","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3605769.3623996","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3605769.3623996","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2023 Workshop on Attacks and Solutions in Hardware Security","raw_type":"proceedings-article"},{"id":"pmh:oai:repository.ubn.ru.nl:2066/299147","is_oa":true,"landing_page_url":"https://hdl.handle.net/2066/299147","pdf_url":"https://repository.ubn.ru.nl/bitstream/handle/2066/299147/1/299147.pdf","source":{"id":"https://openalex.org/S4306401067","display_name":"Radboud Repository (Radboud University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I145872427","host_organization_name":"Radboud University Nijmegen","host_organization_lineage":["https://openalex.org/I145872427"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Article in monograph or in proceedings"}],"best_oa_location":{"id":"doi:10.1145/3605769.3623996","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3605769.3623996","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3605769.3623996","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2023 Workshop on Attacks and Solutions in Hardware Security","raw_type":"proceedings-article"},"sustainable_development_goals":[{"display_name":"Reduced inequalities","score":0.7200000286102295,"id":"https://metadata.un.org/sdg/10"}],"awards":[{"id":"https://openalex.org/G5188059367","display_name":null,"funder_award_id":"NWA.1215.18.014","funder_id":"https://openalex.org/F4320321800","funder_display_name":"Nederlandse Organisatie voor Wetenschappelijk Onderzoek"},{"id":"https://openalex.org/G669276890","display_name":null,"funder_award_id":"CS.019","funder_id":"https://openalex.org/F4320321800","funder_display_name":"Nederlandse Organisatie voor Wetenschappelijk Onderzoek"}],"funders":[{"id":"https://openalex.org/F4320321800","display_name":"Nederlandse Organisatie voor Wetenschappelijk Onderzoek","ror":"https://ror.org/04jsz6e67"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4388958832.pdf","grobid_xml":"https://content.openalex.org/works/W4388958832.grobid-xml"},"referenced_works_count":8,"referenced_works":["https://openalex.org/W2520774990","https://openalex.org/W2604086375","https://openalex.org/W2746796098","https://openalex.org/W2963351448","https://openalex.org/W3004280948","https://openalex.org/W3096110808","https://openalex.org/W3203012334","https://openalex.org/W4238341678"],"related_works":["https://openalex.org/W2965546495","https://openalex.org/W4389116644","https://openalex.org/W2153315159","https://openalex.org/W3103844505","https://openalex.org/W259157601","https://openalex.org/W4205463238","https://openalex.org/W2761785940","https://openalex.org/W2110523656","https://openalex.org/W1482209366","https://openalex.org/W2521627374"],"abstract_inverted_index":{"This":[0,93],"paper":[1,94],"provides":[2],"a":[3,165],"novel":[4],"perspective":[5],"on":[6],"improving":[7,89],"the":[8,33,55,58,67,78,99,119,126,133,137,146,149,153,172],"efficiency":[9],"of":[10,101,129,174],"side-channel":[11,109,181],"analysis":[12],"by":[13],"applying":[14,140],"two":[15],"deep":[16,34,179],"feature":[17,51],"loss":[18,30,52,105,116,121,176],"functions:":[19],"Soft":[20],"Nearest":[21],"Neighbor":[22],"(SoftNN)":[23],"and":[24,85,103],"Center":[25,104,115],"loss.":[26],"By":[27],"leveraging":[28],"these":[29,75],"functions":[31,53,177],"during":[32],"neural":[35],"networks":[36],"(DNNs)":[37],"training":[38],"phase,":[39],"our":[40],"study":[41,161],"illuminates":[42],"how":[43],"profiling":[44],"attacks":[45],"can":[46,162],"be":[47],"more":[48,83,168],"powerful.":[49],"Deep":[50],"incorporate":[54],"outputs":[56],"from":[57],"DNN's":[59,79],"intermediate":[60],"layers":[61],"into":[62,171],"their":[63],"computations,":[64],"which":[65],"reduces":[66],"distance":[68],"between":[69],"similar":[70],"data":[71],"points.":[72],"As":[73],"such,":[74],"techniques":[76],"enhance":[77],"ability":[80],"to":[81,131],"generate":[82],"precise":[84],"meaningful":[86],"representations,":[87],"thereby":[88],"its":[90],"discriminative":[91],"power.":[92],"presents":[95],"empirical":[96],"evidence":[97],"illustrating":[98],"effectiveness":[100],"SoftNN":[102,141],"in":[106,159,178],"strengthening":[107],"DNN-based":[108],"attacks.":[110],"For":[111],"instance,":[112],"when":[113],"using":[114],"together":[117],"with":[118,142,152],"focal":[120],"ratio":[122],"(FLR),":[123],"it":[124],"requires":[125],"least":[127,154],"number":[128],"traces":[130],"break":[132],"ASCADf":[134],"dataset.":[135],"On":[136],"other":[138],"hand,":[139],"FLR":[143],"successfully":[144],"recovers":[145],"key":[147],"for":[148,167],"ASCADr":[150],"dataset":[151],"traces.":[155],"The":[156],"insights":[157],"presented":[158],"this":[160],"act":[163],"as":[164],"baseline":[166],"advanced":[169],"investigations":[170],"utility":[173],"such":[175],"learning-based":[180],"analysis.":[182]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2024,"cited_by_count":2}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}