{"id":"https://openalex.org/W3200261204","doi":"https://doi.org/10.1109/ijcnn52387.2021.9533949","title":"Efficient Adversarial Defense without Adversarial Training: A Batch Normalization Approach","display_name":"Efficient Adversarial Defense without Adversarial Training: A Batch Normalization Approach","publication_year":2021,"publication_date":"2021-07-18","ids":{"openalex":"https://openalex.org/W3200261204","doi":"https://doi.org/10.1109/ijcnn52387.2021.9533949","mag":"3200261204"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn52387.2021.9533949","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn52387.2021.9533949","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5101567069","display_name":"Yao Zhu","orcid":"https://orcid.org/0000-0003-0991-1970"},"institutions":[{"id":"https://openalex.org/I4210131997","display_name":"Dalian Neusoft University of Information","ror":"https://ror.org/0304ty515","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210131997"]},{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yao Zhu","raw_affiliation_strings":["Dalian Neusoft University of Information, Dalian, China","Multimedia and Embedded System Lab, Zhejiang University, Hangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dalian Neusoft University of Information, Dalian, China","institution_ids":["https://openalex.org/I4210131997"]},{"raw_affiliation_string":"Multimedia and Embedded System Lab, Zhejiang University, Hangzhou, China","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100692645","display_name":"Wei Xiao","orcid":"https://orcid.org/0000-0003-3449-1218"},"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":"Xiao Wei","raw_affiliation_strings":["Tsinghua University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5003751717","display_name":"Yue Zhu","orcid":"https://orcid.org/0000-0002-0359-4532"},"institutions":[{"id":"https://openalex.org/I4210131997","display_name":"Dalian Neusoft University of Information","ror":"https://ror.org/0304ty515","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210131997"]},{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yue Zhu","raw_affiliation_strings":["Dalian Neusoft University of Information, Dalian, China","Multimedia and Embedded System Lab, Zhejiang University, Hangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dalian Neusoft University of Information, Dalian, China","institution_ids":["https://openalex.org/I4210131997"]},{"raw_affiliation_string":"Multimedia and Embedded System Lab, Zhejiang University, Hangzhou, China","institution_ids":["https://openalex.org/I76130692"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9998999834060669,"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":0.9998999834060669,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9781000018119812,"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/T11515","display_name":"Bacillus and Francisella bacterial research","score":0.9089000225067139,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.9452645778656006},{"id":"https://openalex.org/keywords/normalization","display_name":"Normalization (sociology)","score":0.7545264363288879},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7480491995811462},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6309853792190552},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5781204700469971},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.4857902526855469},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.483661025762558},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.449678897857666},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4228886365890503},{"id":"https://openalex.org/keywords/training","display_name":"Training (meteorology)","score":0.41491368412971497},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3445724546909332}],"concepts":[{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.9452645778656006},{"id":"https://openalex.org/C136886441","wikidata":"https://www.wikidata.org/wiki/Q926129","display_name":"Normalization (sociology)","level":2,"score":0.7545264363288879},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7480491995811462},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6309853792190552},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5781204700469971},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.4857902526855469},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.483661025762558},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.449678897857666},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4228886365890503},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.41491368412971497},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3445724546909332},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"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/C19165224","wikidata":"https://www.wikidata.org/wiki/Q23404","display_name":"Anthropology","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/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.0},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn52387.2021.9533949","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn52387.2021.9533949","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions","score":0.7900000214576721}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":101,"referenced_works":["https://openalex.org/W1673923490","https://openalex.org/W1945616565","https://openalex.org/W2097117768","https://openalex.org/W2123045220","https://openalex.org/W2243397390","https://openalex.org/W2282821441","https://openalex.org/W2295107390","https://openalex.org/W2299668505","https://openalex.org/W2395317528","https://openalex.org/W2513314332","https://openalex.org/W2516574342","https://openalex.org/W2640329709","https://openalex.org/W2736899637","https://openalex.org/W2746600820","https://openalex.org/W2765424254","https://openalex.org/W2765793020","https://openalex.org/W2768346313","https://openalex.org/W2786118190","https://openalex.org/W2786163515","https://openalex.org/W2787708942","https://openalex.org/W2895033754","https://openalex.org/W2898193427","https://openalex.org/W2901570380","https://openalex.org/W2913266441","https://openalex.org/W2916286792","https://openalex.org/W2924630351","https://openalex.org/W2945359720","https://openalex.org/W2949389295","https://openalex.org/W2950179405","https://openalex.org/W2951652972","https://openalex.org/W2954165282","https://openalex.org/W2962759300","https://openalex.org/W2962851944","https://openalex.org/W2963001136","https://openalex.org/W2963026800","https://openalex.org/W2963143631","https://openalex.org/W2963207607","https://openalex.org/W2963382180","https://openalex.org/W2963557656","https://openalex.org/W2963626025","https://openalex.org/W2963703197","https://openalex.org/W2963733622","https://openalex.org/W2963857521","https://openalex.org/W2963920068","https://openalex.org/W2964116600","https://openalex.org/W2964153729","https://openalex.org/W2970049488","https://openalex.org/W2970316625","https://openalex.org/W2970971581","https://openalex.org/W2971257389","https://openalex.org/W2991381767","https://openalex.org/W2996564870","https://openalex.org/W2998835636","https://openalex.org/W3009542902","https://openalex.org/W3034266196","https://openalex.org/W3034734289","https://openalex.org/W3035160371","https://openalex.org/W3035444186","https://openalex.org/W3035656068","https://openalex.org/W3035743198","https://openalex.org/W3036920016","https://openalex.org/W3080297477","https://openalex.org/W3092873005","https://openalex.org/W3096488581","https://openalex.org/W3103557498","https://openalex.org/W3106412272","https://openalex.org/W3109212549","https://openalex.org/W3134673757","https://openalex.org/W4286796588","https://openalex.org/W4288360049","https://openalex.org/W4288363925","https://openalex.org/W4293846201","https://openalex.org/W4294349862","https://openalex.org/W4295312788","https://openalex.org/W4295803779","https://openalex.org/W6637162671","https://openalex.org/W6640425456","https://openalex.org/W6677995690","https://openalex.org/W6685133223","https://openalex.org/W6697443983","https://openalex.org/W6697673422","https://openalex.org/W6711870810","https://openalex.org/W6725672702","https://openalex.org/W6728458142","https://openalex.org/W6741036071","https://openalex.org/W6744679260","https://openalex.org/W6745272055","https://openalex.org/W6746402973","https://openalex.org/W6747920752","https://openalex.org/W6748277150","https://openalex.org/W6755310938","https://openalex.org/W6759204839","https://openalex.org/W6760716073","https://openalex.org/W6761100157","https://openalex.org/W6762775584","https://openalex.org/W6763111939","https://openalex.org/W6766978945","https://openalex.org/W6771809012","https://openalex.org/W6774357917","https://openalex.org/W6777613727","https://openalex.org/W6779431773"],"related_works":["https://openalex.org/W2502115930","https://openalex.org/W4246396837","https://openalex.org/W2482350142","https://openalex.org/W3176240006","https://openalex.org/W3126451824","https://openalex.org/W3176659669","https://openalex.org/W3211393740","https://openalex.org/W3208049411","https://openalex.org/W3022908591","https://openalex.org/W2946768379"],"abstract_inverted_index":{"Adversarial":[0,25],"training":[1,35],"is":[2,16,46,146],"one":[3],"of":[4,39,86],"the":[5,49,68,84,90,101,108,115,118,133],"most":[6],"effective":[7],"methods":[8],"for":[9,58,136],"defending":[10,149],"against":[11,122],"adversarial":[12,34],"attacks,":[13,151],"but":[14],"it":[15],"computationally":[17],"costly.":[18],"In":[19],"this":[20,75],"paper,":[21],"we":[22,72],"propose":[23],"Saliency":[24],"Defense":[26],"(SAD),":[27],"an":[28],"efficient":[29],"defense":[30],"algorithm":[31],"that":[32,55,74,98,132,144],"avoids":[33],"by":[36,81],"minor":[37],"modification":[38],"a":[40,64],"deployed":[41],"model.":[42],"The":[43],"saliency":[44],"map":[45],"added":[47],"to":[48,51,67],"input":[50],"enhance":[52],"those":[53],"pixels":[54],"are":[56],"important":[57],"making":[59],"decisions.":[60],"This":[61],"process":[62],"causes":[63],"distribution":[65],"shift":[66,76],"original":[69],"data.":[70],"Interestingly,":[71],"find":[73],"can":[77,120],"be":[78],"effectively":[79],"fixed":[80],"only":[82],"updating":[83],"statistics":[85],"batch":[87],"normalization":[88],"with":[89],"processed":[91,105],"data":[92,106],"without":[93],"further":[94],"training.":[95],"We":[96,128],"verify":[97],"SAD":[99,145],"enlarges":[100],"average":[102],"distance":[103],"between":[104],"and":[107,112,125,139,155],"updated":[109],"decision":[110],"boundary,":[111],"significantly":[113],"smooths":[114],"landscape.":[116],"Hence":[117],"model":[119],"defend":[121],"stronger":[123],"attacks":[124],"improve":[126],"robustness.":[127],"show":[129],"in":[130,148],"experiments":[131],"results":[134,142],"hold":[135],"complex":[137],"models":[138],"datasets.":[140],"Our":[141],"demonstrate":[143],"superior":[147],"various":[150],"including":[152],"both":[153],"white-box":[154],"black-box":[156],"ones.":[157]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":3}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
