{"id":"https://openalex.org/W4242053016","doi":"https://doi.org/10.1109/iccad.2017.8203770","title":"Fault injection attack on deep neural network","display_name":"Fault injection attack on deep neural network","publication_year":2017,"publication_date":"2017-11-01","ids":{"openalex":"https://openalex.org/W4242053016","doi":"https://doi.org/10.1109/iccad.2017.8203770"},"language":"en","primary_location":{"id":"doi:10.1109/iccad.2017.8203770","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccad.2017.8203770","pdf_url":null,"source":{"id":"https://openalex.org/S4363608376","display_name":"2017 IEEE/ACM International Conference on Computer-Aided Design (ICCAD)","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE/ACM International Conference on Computer-Aided Design (ICCAD)","raw_type":"proceedings-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/A5038764214","display_name":"Yannan Liu","orcid":"https://orcid.org/0000-0002-7379-3385"},"institutions":[{"id":"https://openalex.org/I177725633","display_name":"Chinese University of Hong Kong","ror":"https://ror.org/00t33hh48","country_code":"CN","type":"education","lineage":["https://openalex.org/I177725633"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yannan Liu","raw_affiliation_strings":["Department of Computer Science & Engineering, The Chinese University of Hong Kong"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science & Engineering, The Chinese University of Hong Kong","institution_ids":["https://openalex.org/I177725633"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005629203","display_name":"Lingxiao Wei","orcid":null},"institutions":[{"id":"https://openalex.org/I177725633","display_name":"Chinese University of Hong Kong","ror":"https://ror.org/00t33hh48","country_code":"CN","type":"education","lineage":["https://openalex.org/I177725633"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lingxiao Wei","raw_affiliation_strings":["Department of Computer Science & Engineering, The Chinese University of Hong Kong"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science & Engineering, The Chinese University of Hong Kong","institution_ids":["https://openalex.org/I177725633"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052233895","display_name":"Bo Luo","orcid":"https://orcid.org/0000-0001-8196-2436"},"institutions":[{"id":"https://openalex.org/I177725633","display_name":"Chinese University of Hong Kong","ror":"https://ror.org/00t33hh48","country_code":"CN","type":"education","lineage":["https://openalex.org/I177725633"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bo Luo","raw_affiliation_strings":["Department of Computer Science & Engineering, The Chinese University of Hong Kong"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science & Engineering, The Chinese University of Hong Kong","institution_ids":["https://openalex.org/I177725633"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5088556682","display_name":"Qiang Xu","orcid":"https://orcid.org/0000-0001-6747-126X"},"institutions":[{"id":"https://openalex.org/I177725633","display_name":"Chinese University of Hong Kong","ror":"https://ror.org/00t33hh48","country_code":"CN","type":"education","lineage":["https://openalex.org/I177725633"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qiang Xu","raw_affiliation_strings":["Department of Computer Science & Engineering, The Chinese University of Hong Kong"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science & Engineering, The Chinese University of Hong Kong","institution_ids":["https://openalex.org/I177725633"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5038764214"],"corresponding_institution_ids":["https://openalex.org/I177725633"],"apc_list":null,"apc_paid":null,"fwci":5.5777,"has_fulltext":false,"cited_by_count":174,"citation_normalized_percentile":{"value":0.96934588,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"131","last_page":"138"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9997000098228455,"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":0.9997000098228455,"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/T11241","display_name":"Advanced Malware Detection Techniques","score":0.9714000225067139,"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"}},{"id":"https://openalex.org/T12122","display_name":"Physical Unclonable Functions (PUFs) and Hardware Security","score":0.968500018119812,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/fault-injection","display_name":"Fault injection","score":0.7440131306648254},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.7196801900863647},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7091054916381836},{"id":"https://openalex.org/keywords/fault","display_name":"Fault (geology)","score":0.6156232357025146},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5903214812278748},{"id":"https://openalex.org/keywords/gradient-descent","display_name":"Gradient descent","score":0.49447202682495117},{"id":"https://openalex.org/keywords/deep-neural-networks","display_name":"Deep neural networks","score":0.47372904419898987},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.44557642936706543},{"id":"https://openalex.org/keywords/descent","display_name":"Descent (aeronautics)","score":0.41521120071411133},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.41325652599334717},{"id":"https://openalex.org/keywords/control-theory","display_name":"Control theory (sociology)","score":0.35019218921661377},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.14517134428024292}],"concepts":[{"id":"https://openalex.org/C2775928411","wikidata":"https://www.wikidata.org/wiki/Q2041312","display_name":"Fault injection","level":3,"score":0.7440131306648254},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.7196801900863647},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7091054916381836},{"id":"https://openalex.org/C175551986","wikidata":"https://www.wikidata.org/wiki/Q47089","display_name":"Fault (geology)","level":2,"score":0.6156232357025146},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5903214812278748},{"id":"https://openalex.org/C153258448","wikidata":"https://www.wikidata.org/wiki/Q1199743","display_name":"Gradient descent","level":3,"score":0.49447202682495117},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.47372904419898987},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.44557642936706543},{"id":"https://openalex.org/C2776637919","wikidata":"https://www.wikidata.org/wiki/Q624380","display_name":"Descent (aeronautics)","level":2,"score":0.41521120071411133},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.41325652599334717},{"id":"https://openalex.org/C47446073","wikidata":"https://www.wikidata.org/wiki/Q5165890","display_name":"Control theory (sociology)","level":3,"score":0.35019218921661377},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.14517134428024292},{"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/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.0},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","level":1,"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/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0},{"id":"https://openalex.org/C2777904410","wikidata":"https://www.wikidata.org/wiki/Q7397","display_name":"Software","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iccad.2017.8203770","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccad.2017.8203770","pdf_url":null,"source":{"id":"https://openalex.org/S4363608376","display_name":"2017 IEEE/ACM International Conference on Computer-Aided Design (ICCAD)","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE/ACM International Conference on Computer-Aided Design (ICCAD)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320309949","display_name":"Canadian Institute for Advanced Research","ror":"https://ror.org/01sdtdd95"},{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335357","display_name":"Guangdong Academy of Sciences","ror":"https://ror.org/01g9hkj35"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":32,"referenced_works":["https://openalex.org/W1665214252","https://openalex.org/W1673923490","https://openalex.org/W1883420340","https://openalex.org/W1945616565","https://openalex.org/W1966948031","https://openalex.org/W2085992264","https://openalex.org/W2108069432","https://openalex.org/W2108857396","https://openalex.org/W2110475502","https://openalex.org/W2116830579","https://openalex.org/W2118717163","https://openalex.org/W2123045220","https://openalex.org/W2143851138","https://openalex.org/W2144784023","https://openalex.org/W2145253420","https://openalex.org/W2145287260","https://openalex.org/W2148461049","https://openalex.org/W2152175008","https://openalex.org/W2152839228","https://openalex.org/W2157116240","https://openalex.org/W2475053276","https://openalex.org/W2491829854","https://openalex.org/W2505343551","https://openalex.org/W2537014044","https://openalex.org/W2546302380","https://openalex.org/W2964082701","https://openalex.org/W6632100021","https://openalex.org/W6637242042","https://openalex.org/W6681813608","https://openalex.org/W6720908527","https://openalex.org/W6723169266","https://openalex.org/W6725368715"],"related_works":["https://openalex.org/W2486267010","https://openalex.org/W1678820847","https://openalex.org/W2559216629","https://openalex.org/W2037211941","https://openalex.org/W4298096494","https://openalex.org/W1553684505","https://openalex.org/W2588465033","https://openalex.org/W2042403445","https://openalex.org/W2725816051","https://openalex.org/W2015288657"],"abstract_inverted_index":{"Deep":[0],"neural":[1],"network":[2],"(DNN),":[3],"being":[4],"able":[5,141],"to":[6,55,83,99,136,142],"effectively":[7],"learn":[8],"from":[9],"a":[10,57],"training":[11],"set":[12],"and":[13,161],"provide":[14],"highly":[15],"accurate":[16],"classification":[17],"results,":[18],"has":[19],"become":[20],"the":[21,44,67,91,109,112,132,144,153,159,164],"de-facto":[22],"technique":[23],"used":[24,69],"in":[25,70,103],"many":[26],"mission-critical":[27],"systems.":[28],"The":[29],"security":[30],"of":[31,36,46,79,90,114,134,163],"DNN":[32,71,104,115,137],"itself":[33],"is":[34,140],"therefore":[35],"great":[37],"concern.":[38],"In":[39],"this":[40,85],"paper,":[41],"we":[42],"investigate":[43],"impact":[45,147],"fault":[47,73,80,145],"injection":[48,81,146],"attacks":[49,82],"on":[50,108,119,148],"DNN,":[51],"wherein":[52],"attackers":[53],"try":[54],"misclassify":[56],"specified":[58,154],"input":[59,149],"pattern":[60],"into":[61,128],"an":[62],"adversarial":[63],"class":[64],"by":[65],"modifying":[66],"parameters":[68],"via":[72],"injection.":[74],"We":[75],"propose":[76],"two":[77],"kinds":[78],"achieve":[84],"objective.":[86],"Without":[87],"considering":[88],"stealthiness":[89,127],"attack,":[92],"single":[93],"bias":[94],"attack":[95,124],"(SBA)":[96],"only":[97],"requires":[98],"modify":[100],"one":[101],"parameter":[102],"for":[105],"misclassification,":[106],"based":[107],"observation":[110],"that":[111],"outputs":[113],"may":[116],"linearly":[117],"depend":[118],"some":[120],"parameters.":[121],"Gradient":[122],"descent":[123],"(GDA)":[125],"takes":[126],"consideration.":[129],"By":[130],"controlling":[131],"amount":[133],"modification":[135],"parameters,":[138],"GDA":[139],"minimize":[143],"patterns":[150],"other":[151],"than":[152],"one.":[155],"Experimental":[156],"results":[157],"demonstrate":[158],"effectiveness":[160],"efficiency":[162],"proposed":[165],"attacks.":[166]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":20},{"year":2024,"cited_by_count":18},{"year":2023,"cited_by_count":26},{"year":2022,"cited_by_count":30},{"year":2021,"cited_by_count":30},{"year":2020,"cited_by_count":34},{"year":2019,"cited_by_count":12},{"year":2018,"cited_by_count":2}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}
