{"id":"https://openalex.org/W4388692087","doi":"https://doi.org/10.1109/tip.2023.3331582","title":"Towards Transferable Adversarial Attacks on Image and Video Transformers","display_name":"Towards Transferable Adversarial Attacks on Image and Video Transformers","publication_year":2023,"publication_date":"2023-01-01","ids":{"openalex":"https://openalex.org/W4388692087","doi":"https://doi.org/10.1109/tip.2023.3331582","pmid":"https://pubmed.ncbi.nlm.nih.gov/37966925"},"language":"en","primary_location":{"id":"doi:10.1109/tip.2023.3331582","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2023.3331582","pdf_url":null,"source":{"id":"https://openalex.org/S4210173141","display_name":"IEEE Transactions on Image Processing","issn_l":"1057-7149","issn":["1057-7149","1941-0042"],"is_oa":false,"is_in_doaj":false,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Image Processing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5085286017","display_name":"Zhipeng Wei","orcid":"https://orcid.org/0000-0001-6315-497X"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zhipeng Wei","raw_affiliation_strings":["Shanghai Key Laboratory of Intelligent Information Processing, School of Computer Science, Fudan University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Shanghai Key Laboratory of Intelligent Information Processing, School of Computer Science, Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100373492","display_name":"Jingjing Chen","orcid":"https://orcid.org/0000-0003-3148-264X"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jingjing Chen","raw_affiliation_strings":["Shanghai Key Laboratory of Intelligent Information Processing, School of Computer Science, Fudan University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Shanghai Key Laboratory of Intelligent Information Processing, School of Computer Science, Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066564672","display_name":"Micah Goldblum","orcid":"https://orcid.org/0000-0002-8266-2424"},"institutions":[{"id":"https://openalex.org/I57206974","display_name":"New York University","ror":"https://ror.org/0190ak572","country_code":"US","type":"education","lineage":["https://openalex.org/I57206974"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Micah Goldblum","raw_affiliation_strings":["Center for Data Science, New York University, New York, NY, USA"],"affiliations":[{"raw_affiliation_string":"Center for Data Science, New York University, New York, NY, USA","institution_ids":["https://openalex.org/I57206974"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5026167547","display_name":"Zuxuan Wu","orcid":"https://orcid.org/0000-0002-8689-5807"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zuxuan Wu","raw_affiliation_strings":["Shanghai Key Laboratory of Intelligent Information Processing, School of Computer Science, Fudan University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Shanghai Key Laboratory of Intelligent Information Processing, School of Computer Science, Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5060687985","display_name":"Tom Goldstein","orcid":"https://orcid.org/0000-0003-1660-9307"},"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":"Tom Goldstein","raw_affiliation_strings":["Department of Computer Science, University of Maryland, College Park, MD, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of Maryland, College Park, MD, USA","institution_ids":["https://openalex.org/I66946132"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047962986","display_name":"Yu\u2013Gang Jiang","orcid":"https://orcid.org/0000-0002-1907-8567"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yu-Gang Jiang","raw_affiliation_strings":["Shanghai Key Laboratory of Intelligent Information Processing, School of Computer Science, Fudan University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Shanghai Key Laboratory of Intelligent Information Processing, School of Computer Science, Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5111454036","display_name":"Larry S. Davis","orcid":null},"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":"Larry S. Davis","raw_affiliation_strings":["Department of Computer Science, University of Maryland, College Park, MD, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of Maryland, College Park, MD, USA","institution_ids":["https://openalex.org/I66946132"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5085286017"],"corresponding_institution_ids":["https://openalex.org/I24943067"],"apc_list":null,"apc_paid":null,"fwci":2.2615,"has_fulltext":false,"cited_by_count":13,"citation_normalized_percentile":{"value":0.90596148,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":"32","issue":null,"first_page":"6346","last_page":"6358"},"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9617000222206116,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9368000030517578,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8443949818611145},{"id":"https://openalex.org/keywords/transferability","display_name":"Transferability","score":0.751288890838623},{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.6904622316360474},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6419795155525208},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5901985168457031},{"id":"https://openalex.org/keywords/generalizability-theory","display_name":"Generalizability theory","score":0.5463013648986816},{"id":"https://openalex.org/keywords/backpropagation","display_name":"Backpropagation","score":0.5349537134170532},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5097424387931824},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.4644038677215576},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.45059096813201904},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.3765002489089966},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.37363767623901367},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3201897144317627}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8443949818611145},{"id":"https://openalex.org/C61272859","wikidata":"https://www.wikidata.org/wiki/Q7834031","display_name":"Transferability","level":3,"score":0.751288890838623},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.6904622316360474},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6419795155525208},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5901985168457031},{"id":"https://openalex.org/C27158222","wikidata":"https://www.wikidata.org/wiki/Q5532422","display_name":"Generalizability theory","level":2,"score":0.5463013648986816},{"id":"https://openalex.org/C155032097","wikidata":"https://www.wikidata.org/wiki/Q798503","display_name":"Backpropagation","level":3,"score":0.5349537134170532},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5097424387931824},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.4644038677215576},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.45059096813201904},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3765002489089966},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.37363767623901367},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3201897144317627},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C140331021","wikidata":"https://www.wikidata.org/wiki/Q1868104","display_name":"Logit","level":2,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tip.2023.3331582","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2023.3331582","pdf_url":null,"source":{"id":"https://openalex.org/S4210173141","display_name":"IEEE Transactions on Image Processing","issn_l":"1057-7149","issn":["1057-7149","1941-0042"],"is_oa":false,"is_in_doaj":false,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Image Processing","raw_type":"journal-article"},{"id":"pmid:37966925","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/37966925","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on image processing : a publication of the IEEE Signal Processing Society","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G8831750362","display_name":null,"funder_award_id":"2021ZD0112804","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"}],"funders":[{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":60,"referenced_works":["https://openalex.org/W1562353621","https://openalex.org/W1904365287","https://openalex.org/W1945616565","https://openalex.org/W2117539524","https://openalex.org/W2194775991","https://openalex.org/W2619947201","https://openalex.org/W2774644650","https://openalex.org/W2896078964","https://openalex.org/W2962847335","https://openalex.org/W2962858109","https://openalex.org/W2969542116","https://openalex.org/W2999683023","https://openalex.org/W3015468748","https://openalex.org/W3034176567","https://openalex.org/W3121523901","https://openalex.org/W3126721948","https://openalex.org/W3137278571","https://openalex.org/W3137963805","https://openalex.org/W3138516171","https://openalex.org/W3154326567","https://openalex.org/W3161120562","https://openalex.org/W3196621661","https://openalex.org/W3200643978","https://openalex.org/W3205752464","https://openalex.org/W3210279979","https://openalex.org/W4214493665","https://openalex.org/W4214588794","https://openalex.org/W4214612132","https://openalex.org/W4214614183","https://openalex.org/W4214634256","https://openalex.org/W4214636423","https://openalex.org/W4214669216","https://openalex.org/W4214703392","https://openalex.org/W4312414395","https://openalex.org/W4312560592","https://openalex.org/W4385245566","https://openalex.org/W4386065604","https://openalex.org/W6640036494","https://openalex.org/W6640425456","https://openalex.org/W6719080892","https://openalex.org/W6729756640","https://openalex.org/W6731927902","https://openalex.org/W6761472960","https://openalex.org/W6768366551","https://openalex.org/W6771961379","https://openalex.org/W6773713311","https://openalex.org/W6776048684","https://openalex.org/W6776690448","https://openalex.org/W6784025586","https://openalex.org/W6785111489","https://openalex.org/W6787052717","https://openalex.org/W6788135285","https://openalex.org/W6790690058","https://openalex.org/W6791705549","https://openalex.org/W6797263693","https://openalex.org/W6797592835","https://openalex.org/W6800772757","https://openalex.org/W6803813760","https://openalex.org/W6805152169","https://openalex.org/W6955071965"],"related_works":["https://openalex.org/W4288055406","https://openalex.org/W3137894200","https://openalex.org/W3092178728","https://openalex.org/W4226402597","https://openalex.org/W4220879026","https://openalex.org/W4200630034","https://openalex.org/W3132910851","https://openalex.org/W4377864639","https://openalex.org/W4392340763","https://openalex.org/W2997056298"],"abstract_inverted_index":{"The":[0],"transferability":[1,81,175],"of":[2,75,111,130,149,184,221],"adversarial":[3,62,155],"examples":[4,63,156],"across":[5,82],"different":[6,83],"convolutional":[7],"neural":[8],"networks":[9],"(CNNs)":[10],"makes":[11],"it":[12],"feasible":[13],"to":[14,30,107,137,167,201],"perform":[15],"black-box":[16],"attacks,":[17,196],"resulting":[18],"in":[19,85],"security":[20,74],"threats":[21],"for":[22,34,119,210],"CNNs.":[23],"However,":[24],"fewer":[25],"endeavors":[26],"have":[27],"been":[28],"made":[29],"investigate":[31,79],"transferable":[32,195],"attacks":[33],"vision":[35,45],"transformers":[36],"(ViTs),":[37],"which":[38,101],"achieve":[39],"superior":[40],"performance":[41],"on":[42,65,206],"various":[43],"computer":[44],"tasks.":[46],"Unlike":[47],"CNNs,":[48],"ViTs":[49,76,84],"establish":[50],"relationships":[51],"between":[52],"patches":[53],"extracted":[54],"from":[55,159],"inputs":[56,180],"by":[57,176],"the":[58,73,80,109,138,146,153,160,182,187,219,222],"self-attention":[59,183],"module.":[60],"Thus,":[61],"crafted":[64],"CNNs":[66],"might":[67],"hardly":[68],"attack":[69,118,190],"ViTs.":[70,121,185],"To":[71],"assess":[72],"comprehensively,":[77],"we":[78,93,114,144],"both":[86],"untargetd":[87],"and":[88,181,208,212],"targeted":[89],"scenarios.":[90],"More":[91],"specifically,":[92],"propose":[94],"a":[95,116,126],"Pay":[96],"No":[97],"Attention":[98],"(PNA)":[99],"attack,":[100],"ignores":[102],"attention":[103],"gradients":[104],"during":[105,132],"backpropagation":[106],"improve":[108],"linearity":[110],"backpropagation.":[112],"Additionally,":[113],"introduce":[115],"PatchOut/CubeOut":[117],"image/video":[120],"They":[122],"optimize":[123],"perturbations":[124],"within":[125],"randomly":[127],"selected":[128],"subset":[129],"patches/cubes":[131],"each":[133],"iteration,":[134],"preventing":[135],"over-fitting":[136],"white-box":[139],"surrogate":[140],"ViT":[141],"model.":[142],"Furthermore,":[143],"maximize":[145],"L<sub>2</sub>":[147],"norm":[148],"perturbations,":[150],"ensuring":[151],"that":[152],"generated":[154],"deviate":[157],"significantly":[158],"benign":[161],"ones.":[162],"These":[163],"strategies":[164],"are":[165],"designed":[166],"be":[168],"harmoniously":[169],"compatible.":[170],"Combining":[171],"them":[172],"can":[173],"enhance":[174],"jointly":[177],"considering":[178],"patch-based":[179],"Moreover,":[186],"proposed":[188,223],"combined":[189],"seamlessly":[191],"integrates":[192],"with":[193],"existing":[194],"providing":[197],"an":[198],"additional":[199],"boost":[200],"transferability.":[202],"We":[203],"conduct":[204],"experiments":[205],"ImageNet":[207],"Kinetics-400":[209],"image":[211],"video":[213],"ViTs,":[214],"respectively.":[215],"Experimental":[216],"results":[217],"demonstrate":[218],"effectiveness":[220],"method.":[224]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":8},{"year":2024,"cited_by_count":4}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
