{"id":"https://openalex.org/W4231242640","doi":"https://doi.org/10.1109/ojcas.2021.3116244","title":"Understanding the Energy vs. Adversarial Robustness Trade-Off in Deep Neural Networks","display_name":"Understanding the Energy vs. Adversarial Robustness Trade-Off in Deep Neural Networks","publication_year":2021,"publication_date":"2021-01-01","ids":{"openalex":"https://openalex.org/W4231242640","doi":"https://doi.org/10.1109/ojcas.2021.3116244"},"language":"en","primary_location":{"id":"doi:10.1109/ojcas.2021.3116244","is_oa":true,"landing_page_url":"https://doi.org/10.1109/ojcas.2021.3116244","pdf_url":"https://ieeexplore.ieee.org/ielx7/8784029/9314963/09645046.pdf","source":{"id":"https://openalex.org/S4210192473","display_name":"IEEE Open Journal of Circuits and Systems","issn_l":"2644-1225","issn":["2644-1225"],"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 Open Journal of Circuits and Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/8784029/9314963/09645046.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5062648698","display_name":"Kyungmi Lee","orcid":"https://orcid.org/0000-0001-6406-9515"},"institutions":[{"id":"https://openalex.org/I63966007","display_name":"Massachusetts Institute of Technology","ror":"https://ror.org/042nb2s44","country_code":"US","type":"education","lineage":["https://openalex.org/I63966007"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Kyungmi Lee","raw_affiliation_strings":["Massachusetts Institute of Technology, Cambridge, MA, USA"],"affiliations":[{"raw_affiliation_string":"Massachusetts Institute of Technology, Cambridge, MA, USA","institution_ids":["https://openalex.org/I63966007"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5084128470","display_name":"Anantha P. Chandrakasan","orcid":"https://orcid.org/0000-0002-5977-2748"},"institutions":[{"id":"https://openalex.org/I63966007","display_name":"Massachusetts Institute of Technology","ror":"https://ror.org/042nb2s44","country_code":"US","type":"education","lineage":["https://openalex.org/I63966007"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Anantha P. Chandrakasan","raw_affiliation_strings":["Massachusetts Institute of Technology, Cambridge, MA, USA"],"affiliations":[{"raw_affiliation_string":"Massachusetts Institute of Technology, Cambridge, MA, USA","institution_ids":["https://openalex.org/I63966007"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5062648698"],"corresponding_institution_ids":["https://openalex.org/I63966007"],"apc_list":{"value":1750,"currency":"USD","value_usd":1750},"apc_paid":{"value":1750,"currency":"USD","value_usd":1750},"fwci":0.2795,"has_fulltext":true,"cited_by_count":2,"citation_normalized_percentile":{"value":0.66405363,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":93,"max":95},"biblio":{"volume":"2","issue":null,"first_page":"843","last_page":"855"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":1.0,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":1.0,"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":0.9758999943733215,"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/T14117","display_name":"Integrated Circuits and Semiconductor Failure Analysis","score":0.9587000012397766,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.8545741438865662},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7289818525314331},{"id":"https://openalex.org/keywords/initialization","display_name":"Initialization","score":0.687332034111023},{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.6423393487930298},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.52432781457901},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.48997679352760315},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.4733826220035553},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4593977630138397},{"id":"https://openalex.org/keywords/deep-neural-networks","display_name":"Deep neural networks","score":0.4420726001262665},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3261796236038208}],"concepts":[{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.8545741438865662},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7289818525314331},{"id":"https://openalex.org/C114466953","wikidata":"https://www.wikidata.org/wiki/Q6034165","display_name":"Initialization","level":2,"score":0.687332034111023},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.6423393487930298},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.52432781457901},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.48997679352760315},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.4733826220035553},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4593977630138397},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.4420726001262665},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3261796236038208},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"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:10.1109/ojcas.2021.3116244","is_oa":true,"landing_page_url":"https://doi.org/10.1109/ojcas.2021.3116244","pdf_url":"https://ieeexplore.ieee.org/ielx7/8784029/9314963/09645046.pdf","source":{"id":"https://openalex.org/S4210192473","display_name":"IEEE Open Journal of Circuits and Systems","issn_l":"2644-1225","issn":["2644-1225"],"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 Open Journal of Circuits and Systems","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:12ef1808aaca433ab0a51b698d8e013d","is_oa":true,"landing_page_url":"https://doaj.org/article/12ef1808aaca433ab0a51b698d8e013d","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"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 Open Journal of Circuits and Systems, Vol 2, Pp 843-855 (2021)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/ojcas.2021.3116244","is_oa":true,"landing_page_url":"https://doi.org/10.1109/ojcas.2021.3116244","pdf_url":"https://ieeexplore.ieee.org/ielx7/8784029/9314963/09645046.pdf","source":{"id":"https://openalex.org/S4210192473","display_name":"IEEE Open Journal of Circuits and Systems","issn_l":"2644-1225","issn":["2644-1225"],"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 Open Journal of Circuits and Systems","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1139554836","display_name":null,"funder_award_id":"Fellowship","funder_id":"https://openalex.org/F4320324571","funder_display_name":"Korea Foundation for Advanced Studies"}],"funders":[{"id":"https://openalex.org/F4320315933","display_name":"Siebel Scholars Foundation","ror":null},{"id":"https://openalex.org/F4320317705","display_name":"NXP Semiconductors","ror":"https://ror.org/059be4e97"},{"id":"https://openalex.org/F4320324571","display_name":"Korea Foundation for Advanced Studies","ror":"https://ror.org/0556dev32"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4231242640.pdf","grobid_xml":"https://content.openalex.org/works/W4231242640.grobid-xml"},"referenced_works_count":62,"referenced_works":["https://openalex.org/W1673923490","https://openalex.org/W1686810756","https://openalex.org/W1821462560","https://openalex.org/W1836465849","https://openalex.org/W1945616565","https://openalex.org/W2096733369","https://openalex.org/W2112796928","https://openalex.org/W2117539524","https://openalex.org/W2119144962","https://openalex.org/W2194775991","https://openalex.org/W2335728318","https://openalex.org/W2408141691","https://openalex.org/W2535873859","https://openalex.org/W2603766943","https://openalex.org/W2610190180","https://openalex.org/W2759471388","https://openalex.org/W2768346313","https://openalex.org/W2785678896","https://openalex.org/W2786163515","https://openalex.org/W2807040120","https://openalex.org/W2887603965","https://openalex.org/W2916286792","https://openalex.org/W2962965870","https://openalex.org/W2963001136","https://openalex.org/W2963143631","https://openalex.org/W2963163009","https://openalex.org/W2963460857","https://openalex.org/W2963496101","https://openalex.org/W2963857521","https://openalex.org/W2963976704","https://openalex.org/W2964014389","https://openalex.org/W2964082701","https://openalex.org/W2964116600","https://openalex.org/W2964137095","https://openalex.org/W2964159205","https://openalex.org/W3009542902","https://openalex.org/W3035965352","https://openalex.org/W3099878876","https://openalex.org/W3118608800","https://openalex.org/W3132111889","https://openalex.org/W4247200422","https://openalex.org/W4293846201","https://openalex.org/W4295312788","https://openalex.org/W4297672357","https://openalex.org/W4299356147","https://openalex.org/W4300167250","https://openalex.org/W6637373629","https://openalex.org/W6638667902","https://openalex.org/W6703116779","https://openalex.org/W6745272055","https://openalex.org/W6745454490","https://openalex.org/W6745893766","https://openalex.org/W6748475379","https://openalex.org/W6748582592","https://openalex.org/W6749781174","https://openalex.org/W6751834733","https://openalex.org/W6755310938","https://openalex.org/W6758508162","https://openalex.org/W6759204839","https://openalex.org/W6765694979","https://openalex.org/W6766978945","https://openalex.org/W6774469542"],"related_works":["https://openalex.org/W2950183588","https://openalex.org/W3080754722","https://openalex.org/W3093978547","https://openalex.org/W3203790781","https://openalex.org/W2997056298","https://openalex.org/W2738001131","https://openalex.org/W4285785480","https://openalex.org/W3127875750","https://openalex.org/W4383221314","https://openalex.org/W4386850404"],"abstract_inverted_index":{"Adversarial":[0],"examples,":[1],"which":[2],"are":[3],"crafted":[4],"by":[5,143,171],"adding":[6],"small":[7],"perturbations":[8],"to":[9,14,27],"typical":[10],"inputs":[11],"in":[12,78],"order":[13],"fool":[15],"the":[16,47,55,85,101,117,144,152,158,162,181,187,195],"prediction":[17],"of":[18,72,84,194],"a":[19,25,107],"deep":[20],"neural":[21],"network":[22],"(DNN),":[23],"pose":[24],"threat":[26],"security-critical":[28],"applications,":[29],"and":[30,59,80,122,135,161,165,191],"robustness":[31,52,121,155],"against":[32],"adversarial":[33,51,120],"examples":[34],"is":[35,169],"becoming":[36],"an":[37,126],"important":[38],"design":[39],"factor.":[40],"In":[41],"this":[42,64,138,167],"work,":[43],"we":[44,91,115,150],"first":[45],"examine":[46,151],"methodology":[48,66,111],"for":[49,112],"evaluating":[50],"that":[53,95,137,180],"uses":[54],"first-order":[56],"attack":[57,86,103,159],"methods,":[58,104,164],"analyze":[60],"three":[61,145],"cases":[62,146],"when":[63],"evaluation":[65,110,133,197],"overestimates":[67],"robustness:":[68],"1)":[69],"numerical":[70],"saturation":[71],"cross-entropy":[73],"loss,":[74],"2)":[75],"non-differentiable":[76],"functions":[77],"DNNs,":[79],"3)":[81],"ineffective":[82],"initialization":[83],"methods.":[87,175],"For":[88],"each":[89],"case,":[90],"propose":[92],"compensation":[93,174],"methods":[94,160],"can":[96,140],"be":[97,141],"easily":[98],"combined":[99],"with":[100,157],"existing":[102],"thus":[105],"provide":[106],"more":[108],"precise":[109,196],"robustness.":[113],"Second,":[114],"benchmark":[116],"relationship":[118,139],"between":[119,154],"inference-time":[123],"energy":[124],"at":[125],"embedded":[127],"hardware":[128],"platform":[129],"using":[130],"our":[131,172,177],"proposed":[132,173],"methodology,":[134],"demonstrate":[136],"obscured":[142],"behind":[147],"overestimation.":[148],"Finally,":[149],"gap":[153,168],"measured":[156],"verification":[163],"show":[166],"reduced":[170],"Overall,":[176],"work":[178],"shows":[179],"robustness-energy":[182],"trade-off":[183],"has":[184],"differences":[185],"from":[186],"conventional":[188],"accuracy-energy":[189],"trade-off,":[190],"highlights":[192],"importance":[193],"methodology.":[198]},"counts_by_year":[{"year":2021,"cited_by_count":2}],"updated_date":"2026-03-18T14:38:29.013473","created_date":"2025-10-10T00:00:00"}
