{"id":"https://openalex.org/W4386888948","doi":"https://doi.org/10.1145/3617893","title":"Lightning: Leveraging DVFS-induced Transient Fault Injection to Attack Deep Learning Accelerator of GPUs","display_name":"Lightning: Leveraging DVFS-induced Transient Fault Injection to Attack Deep Learning Accelerator of GPUs","publication_year":2023,"publication_date":"2023-09-20","ids":{"openalex":"https://openalex.org/W4386888948","doi":"https://doi.org/10.1145/3617893"},"language":"en","primary_location":{"id":"doi:10.1145/3617893","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3617893","pdf_url":null,"source":{"id":"https://openalex.org/S105046310","display_name":"ACM Transactions on Design Automation of Electronic Systems","issn_l":"1084-4309","issn":["1084-4309","1557-7309"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Design Automation of Electronic Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101634932","display_name":"Rihui Sun","orcid":"https://orcid.org/0000-0002-9948-8653"},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Rihui Sun","raw_affiliation_strings":["Harbin Institute of Technology, China"],"raw_orcid":"https://orcid.org/0000-0002-9948-8653","affiliations":[{"raw_affiliation_string":"Harbin Institute of Technology, China","institution_ids":["https://openalex.org/I204983213"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5003865038","display_name":"Pengfei Qiu","orcid":"https://orcid.org/0009-0009-4043-2119"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Pengfei Qiu","raw_affiliation_strings":["Beijing University of Posts and Telecommunications, China"],"raw_orcid":"https://orcid.org/0009-0009-4043-2119","affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058507537","display_name":"Yongqiang Lyu","orcid":"https://orcid.org/0000-0003-2573-963X"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yongqiang Lyu","raw_affiliation_strings":["Tsinghua University, China"],"raw_orcid":"https://orcid.org/0000-0003-2573-963X","affiliations":[{"raw_affiliation_string":"Tsinghua University, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5063004428","display_name":"Jian Dong","orcid":"https://orcid.org/0000-0002-2980-9431"},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jian Dong","raw_affiliation_strings":["Harbin Institute of Technology, China"],"raw_orcid":"https://orcid.org/0000-0002-2980-9431","affiliations":[{"raw_affiliation_string":"Harbin Institute of Technology, China","institution_ids":["https://openalex.org/I204983213"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100439437","display_name":"Haixia Wang","orcid":"https://orcid.org/0009-0008-0474-5030"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haixia Wang","raw_affiliation_strings":["Tsinghua University, China"],"raw_orcid":"https://orcid.org/0009-0008-0474-5030","affiliations":[{"raw_affiliation_string":"Tsinghua University, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100450575","display_name":"Dongsheng Wang","orcid":"https://orcid.org/0000-0001-5779-9026"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dongsheng Wang","raw_affiliation_strings":["Tsinghua University, China"],"raw_orcid":"https://orcid.org/0000-0001-5779-9026","affiliations":[{"raw_affiliation_string":"Tsinghua University, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5012474783","display_name":"Gang Qu","orcid":"https://orcid.org/0000-0001-6759-8949"},"institutions":[{"id":"https://openalex.org/I66946132","display_name":"University of Maryland, College Park","ror":"https://ror.org/047s2c258","country_code":"US","type":"education","lineage":["https://openalex.org/I66946132"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Gang Qu","raw_affiliation_strings":["University of Maryland, USA"],"raw_orcid":"https://orcid.org/0000-0001-6759-8949","affiliations":[{"raw_affiliation_string":"University of Maryland, USA","institution_ids":["https://openalex.org/I66946132"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.5904,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.82745796,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":"29","issue":"1","first_page":"1","last_page":"22"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12122","display_name":"Physical Unclonable Functions (PUFs) and Hardware Security","score":0.9994000196456909,"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"}},"topics":[{"id":"https://openalex.org/T12122","display_name":"Physical Unclonable Functions (PUFs) and Hardware Security","score":0.9994000196456909,"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/T11424","display_name":"Security and Verification in Computing","score":0.996999979019165,"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/T11005","display_name":"Radiation Effects in Electronics","score":0.9959999918937683,"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/computer-science","display_name":"Computer science","score":0.87359219789505},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6369401216506958},{"id":"https://openalex.org/keywords/fault-injection","display_name":"Fault injection","score":0.5914782881736755},{"id":"https://openalex.org/keywords/transient","display_name":"Transient (computer programming)","score":0.5854539275169373},{"id":"https://openalex.org/keywords/lightning","display_name":"Lightning (connector)","score":0.5480731129646301},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5329533219337463},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4625309109687805},{"id":"https://openalex.org/keywords/embedded-system","display_name":"Embedded system","score":0.4417327344417572},{"id":"https://openalex.org/keywords/fault","display_name":"Fault (geology)","score":0.43728557229042053},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.38333016633987427},{"id":"https://openalex.org/keywords/power","display_name":"Power (physics)","score":0.334881067276001},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.32111603021621704},{"id":"https://openalex.org/keywords/computer-engineering","display_name":"Computer engineering","score":0.3202507495880127},{"id":"https://openalex.org/keywords/software","display_name":"Software","score":0.2033691108226776}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.87359219789505},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6369401216506958},{"id":"https://openalex.org/C2775928411","wikidata":"https://www.wikidata.org/wiki/Q2041312","display_name":"Fault injection","level":3,"score":0.5914782881736755},{"id":"https://openalex.org/C2780799671","wikidata":"https://www.wikidata.org/wiki/Q17087362","display_name":"Transient (computer programming)","level":2,"score":0.5854539275169373},{"id":"https://openalex.org/C69398868","wikidata":"https://www.wikidata.org/wiki/Q129052","display_name":"Lightning (connector)","level":3,"score":0.5480731129646301},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5329533219337463},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4625309109687805},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.4417327344417572},{"id":"https://openalex.org/C175551986","wikidata":"https://www.wikidata.org/wiki/Q47089","display_name":"Fault (geology)","level":2,"score":0.43728557229042053},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.38333016633987427},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.334881067276001},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.32111603021621704},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.3202507495880127},{"id":"https://openalex.org/C2777904410","wikidata":"https://www.wikidata.org/wiki/Q7397","display_name":"Software","level":2,"score":0.2033691108226776},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"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/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0},{"id":"https://openalex.org/C165205528","wikidata":"https://www.wikidata.org/wiki/Q83371","display_name":"Seismology","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3617893","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3617893","pdf_url":null,"source":{"id":"https://openalex.org/S105046310","display_name":"ACM Transactions on Design Automation of Electronic Systems","issn_l":"1084-4309","issn":["1084-4309","1557-7309"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Design Automation of Electronic Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/7","display_name":"Affordable and clean energy","score":0.550000011920929}],"awards":[{"id":"https://openalex.org/G2529879782","display_name":null,"funder_award_id":"92067206","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3477364470","display_name":null,"funder_award_id":"2021YFB3100902","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G6714212579","display_name":null,"funder_award_id":"62072263","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":39,"referenced_works":["https://openalex.org/W95608104","https://openalex.org/W1938355940","https://openalex.org/W1989831790","https://openalex.org/W1999528892","https://openalex.org/W2039845393","https://openalex.org/W2041435997","https://openalex.org/W2060193918","https://openalex.org/W2062455052","https://openalex.org/W2134732727","https://openalex.org/W2162282468","https://openalex.org/W2172583428","https://openalex.org/W2213200328","https://openalex.org/W2323777873","https://openalex.org/W2557443516","https://openalex.org/W2737356556","https://openalex.org/W2792994523","https://openalex.org/W2794806694","https://openalex.org/W2891810898","https://openalex.org/W2895385416","https://openalex.org/W2904294250","https://openalex.org/W2910279915","https://openalex.org/W2913252637","https://openalex.org/W2949981335","https://openalex.org/W2960267604","https://openalex.org/W2982304716","https://openalex.org/W2983058739","https://openalex.org/W2997384620","https://openalex.org/W2998897128","https://openalex.org/W3015806656","https://openalex.org/W3213748123","https://openalex.org/W4205540825","https://openalex.org/W4231124057","https://openalex.org/W4232007745","https://openalex.org/W4234208415","https://openalex.org/W4246282713","https://openalex.org/W4249878737","https://openalex.org/W4252254358","https://openalex.org/W4293025163","https://openalex.org/W4301329292"],"related_works":["https://openalex.org/W2604133224","https://openalex.org/W4234532445","https://openalex.org/W2062132293","https://openalex.org/W3044620288","https://openalex.org/W2991843241","https://openalex.org/W2358137648","https://openalex.org/W2543002644","https://openalex.org/W2570564682","https://openalex.org/W2055243143","https://openalex.org/W4312356560"],"abstract_inverted_index":{"Graphics":[0],"Processing":[1],"Units":[2],"(GPU)":[3],"are":[4,53,63,82],"widely":[5],"used":[6],"as":[7,78],"deep":[8],"learning":[9,51],"accelerators":[10],"because":[11],"of":[12,33,129,191],"its":[13],"high":[14],"performance":[15],"and":[16,111,139],"low":[17],"power":[18],"consumption.":[19],"Additionally,":[20],"it":[21],"remains":[22],"secure":[23],"against":[24,55],"hardware-induced":[25,103],"transient":[26,104],"fault":[27,57],"injection":[28,58],"attacks,":[29,183],"a":[30,117,141,188],"classic":[31],"type":[32],"attacks":[34,59],"that":[35,48,69,81,167],"have":[36,72],"been":[37],"developed":[38],"on":[39,107,156,179],"other":[40],"computing":[41],"platforms.":[42],"In":[43],"this":[44,88],"work,":[45],"we":[46,67,75,90],"demonstrate":[47],"well-trained":[49],"machine":[50],"models":[52,71,134,165],"robust":[54],"hardware":[56],"when":[60],"the":[61,92,98,108,124,136,147,168,174],"faults":[62,105],"generated":[64],"randomly.":[65],"However,":[66],"discover":[68],"these":[70],"components,":[73],"which":[74,95],"refer":[76],"to":[77,84,122,144,152],"sensitive":[79,100,118],"targets,":[80],"vulnerable":[83],"faults.":[85,154],"By":[86],"exploiting":[87],"vulnerability,":[89],"propose":[91],"Lightning":[93,170],"attack,":[94],"precisely":[96],"strikes":[97],"model\u2019s":[99],"targets":[101,119],"with":[102],"based":[106],"Dynamic":[109],"Voltage":[110],"Frequency":[112],"Scaling":[113],"(DVFS).":[114],"We":[115],"design":[116],"search":[120],"algorithm":[121,143],"find":[123],"most":[125],"critical":[126],"processing":[127],"units":[128],"Deep":[130],"Neural":[131],"Network":[132],"(DNN)":[133],"determining":[135],"inference":[137,175],"results,":[138],"develop":[140],"genetic":[142],"automatically":[145],"optimize":[146],"attack":[148,171],"parameters":[149],"for":[150,161,181,193],"DVFS":[151],"induce":[153],"Experiments":[155],"three":[157],"commodity":[158],"Nvidia":[159],"GPUs":[160],"four":[162],"widely-used":[163],"DNN":[164],"show":[166],"proposed":[169],"can":[172],"reduce":[173],"accuracy":[176],"by":[177],"69.1%":[178],"average":[180],"non-targeted":[182],"and,":[184],"more":[185],"interestingly,":[186],"achieve":[187],"success":[189],"rate":[190],"67.9%":[192],"targeted":[194],"attacks.":[195]},"counts_by_year":[{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":1}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}
