{"id":"https://openalex.org/W3200717531","doi":"https://doi.org/10.1145/3474369.3486862","title":"Adversarial Transfer Attacks With Unknown Data and Class Overlap","display_name":"Adversarial Transfer Attacks With Unknown Data and Class Overlap","publication_year":2021,"publication_date":"2021-10-28","ids":{"openalex":"https://openalex.org/W3200717531","doi":"https://doi.org/10.1145/3474369.3486862","mag":"3200717531"},"language":"en","primary_location":{"id":"doi:10.1145/3474369.3486862","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3474369.3486862","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3474369.3486862","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 14th ACM Workshop on Artificial Intelligence and Security","raw_type":"proceedings-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3474369.3486862","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Luke E. Richards","orcid":null},"institutions":[{"id":"https://openalex.org/I1322124587","display_name":"Booz Allen Hamilton (United States)","ror":"https://ror.org/051rcp357","country_code":"US","type":"company","lineage":["https://openalex.org/I1322124587"]},{"id":"https://openalex.org/I79272384","display_name":"University of Maryland, Baltimore County","ror":"https://ror.org/02qskvh78","country_code":"US","type":"education","lineage":["https://openalex.org/I79272384"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Luke E. Richards","raw_affiliation_strings":["Booz Allen Hamilton &amp; University of Maryland, Baltimore County, Baltimore, MD, USA"],"affiliations":[{"raw_affiliation_string":"Booz Allen Hamilton &amp; University of Maryland, Baltimore County, Baltimore, MD, USA","institution_ids":["https://openalex.org/I79272384","https://openalex.org/I1322124587"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Andr\u00e9 Nguyen","orcid":null},"institutions":[{"id":"https://openalex.org/I1322124587","display_name":"Booz Allen Hamilton (United States)","ror":"https://ror.org/051rcp357","country_code":"US","type":"company","lineage":["https://openalex.org/I1322124587"]},{"id":"https://openalex.org/I79272384","display_name":"University of Maryland, Baltimore County","ror":"https://ror.org/02qskvh78","country_code":"US","type":"education","lineage":["https://openalex.org/I79272384"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Andr\u00e9 Nguyen","raw_affiliation_strings":["Booz Allen Hamilton &amp; University of Maryland, Baltimore County, Baltimore, MD, USA"],"affiliations":[{"raw_affiliation_string":"Booz Allen Hamilton &amp; University of Maryland, Baltimore County, Baltimore, MD, USA","institution_ids":["https://openalex.org/I79272384","https://openalex.org/I1322124587"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Ryan Capps","orcid":null},"institutions":[{"id":"https://openalex.org/I1322124587","display_name":"Booz Allen Hamilton (United States)","ror":"https://ror.org/051rcp357","country_code":"US","type":"company","lineage":["https://openalex.org/I1322124587"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ryan Capps","raw_affiliation_strings":["Booz Allen Hamilton, Washinton, DC, USA"],"affiliations":[{"raw_affiliation_string":"Booz Allen Hamilton, Washinton, DC, USA","institution_ids":["https://openalex.org/I1322124587"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Steven Forsyth","orcid":null},"institutions":[{"id":"https://openalex.org/I4210127875","display_name":"Nvidia (United States)","ror":"https://ror.org/03jdj4y14","country_code":"US","type":"company","lineage":["https://openalex.org/I4210127875"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Steven Forsyth","raw_affiliation_strings":["NVIDIA, Washinton, DC, USA"],"affiliations":[{"raw_affiliation_string":"NVIDIA, Washinton, DC, USA","institution_ids":["https://openalex.org/I4210127875"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Cynthia Matuszek","orcid":null},"institutions":[{"id":"https://openalex.org/I79272384","display_name":"University of Maryland, Baltimore County","ror":"https://ror.org/02qskvh78","country_code":"US","type":"education","lineage":["https://openalex.org/I79272384"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Cynthia Matuszek","raw_affiliation_strings":["University of Maryland, Baltimore County, Baltimore, MD, USA"],"affiliations":[{"raw_affiliation_string":"University of Maryland, Baltimore County, Baltimore, MD, USA","institution_ids":["https://openalex.org/I79272384"]}]},{"author_position":"last","author":{"id":null,"display_name":"Edward Raff","orcid":null},"institutions":[{"id":"https://openalex.org/I1322124587","display_name":"Booz Allen Hamilton (United States)","ror":"https://ror.org/051rcp357","country_code":"US","type":"company","lineage":["https://openalex.org/I1322124587"]},{"id":"https://openalex.org/I79272384","display_name":"University of Maryland, Baltimore County","ror":"https://ror.org/02qskvh78","country_code":"US","type":"education","lineage":["https://openalex.org/I79272384"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Edward Raff","raw_affiliation_strings":["Booz Allen Hamilton &amp; University of Maryland, Baltimore County, Balitmore, MD, USA"],"affiliations":[{"raw_affiliation_string":"Booz Allen Hamilton &amp; University of Maryland, Baltimore County, Balitmore, MD, USA","institution_ids":["https://openalex.org/I1322124587","https://openalex.org/I79272384"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I1322124587","https://openalex.org/I79272384"],"apc_list":null,"apc_paid":null,"fwci":0.5599,"has_fulltext":true,"cited_by_count":4,"citation_normalized_percentile":{"value":0.73616069,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"13","last_page":"24"},"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":0.9786999821662903,"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":0.9117000102996826,"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":0.8209999799728394},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.7028999924659729},{"id":"https://openalex.org/keywords/imperfect","display_name":"Imperfect","score":0.6674000024795532},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.6078000068664551},{"id":"https://openalex.org/keywords/attack-model","display_name":"Attack model","score":0.5379999876022339},{"id":"https://openalex.org/keywords/transfer-of-learning","display_name":"Transfer of learning","score":0.4113999903202057},{"id":"https://openalex.org/keywords/gradient-descent","display_name":"Gradient descent","score":0.397599995136261}],"concepts":[{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.8209999799728394},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7487999796867371},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.7028999924659729},{"id":"https://openalex.org/C2780310539","wikidata":"https://www.wikidata.org/wiki/Q12547192","display_name":"Imperfect","level":2,"score":0.6674000024795532},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.6078000068664551},{"id":"https://openalex.org/C65856478","wikidata":"https://www.wikidata.org/wiki/Q3991682","display_name":"Attack model","level":2,"score":0.5379999876022339},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4878999888896942},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.4738999903202057},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.4113999903202057},{"id":"https://openalex.org/C153258448","wikidata":"https://www.wikidata.org/wiki/Q1199743","display_name":"Gradient descent","level":3,"score":0.397599995136261},{"id":"https://openalex.org/C2778403875","wikidata":"https://www.wikidata.org/wiki/Q20312394","display_name":"Adversarial machine learning","level":3,"score":0.3930000066757202},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3901999890804291},{"id":"https://openalex.org/C140547941","wikidata":"https://www.wikidata.org/wiki/Q7797194","display_name":"Threat model","level":2,"score":0.3734000027179718},{"id":"https://openalex.org/C2776175482","wikidata":"https://www.wikidata.org/wiki/Q1195816","display_name":"Transfer (computing)","level":2,"score":0.364300012588501},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.35120001435279846},{"id":"https://openalex.org/C182365436","wikidata":"https://www.wikidata.org/wiki/Q50701","display_name":"Variable (mathematics)","level":2,"score":0.3434000015258789},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.33160001039505005}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3474369.3486862","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3474369.3486862","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3474369.3486862","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 14th ACM Workshop on Artificial Intelligence and Security","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2109.11125","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2109.11125","pdf_url":"https://arxiv.org/pdf/2109.11125","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"doi:10.1145/3474369.3486862","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3474369.3486862","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3474369.3486862","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 14th ACM Workshop on Artificial Intelligence and Security","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3200717531.pdf","grobid_xml":"https://content.openalex.org/works/W3200717531.grobid-xml"},"referenced_works_count":36,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1978963692","https://openalex.org/W2038296020","https://openalex.org/W2090495691","https://openalex.org/W2144906988","https://openalex.org/W2146994234","https://openalex.org/W2514847810","https://openalex.org/W2533631783","https://openalex.org/W2603766943","https://openalex.org/W2640329709","https://openalex.org/W2774644650","https://openalex.org/W2783112941","https://openalex.org/W2783141341","https://openalex.org/W2787708942","https://openalex.org/W2791683151","https://openalex.org/W2793931959","https://openalex.org/W2797142180","https://openalex.org/W2798159728","https://openalex.org/W2904331652","https://openalex.org/W2906963924","https://openalex.org/W2910721469","https://openalex.org/W2912454742","https://openalex.org/W2913770005","https://openalex.org/W2962911949","https://openalex.org/W2963165251","https://openalex.org/W2969542116","https://openalex.org/W2996564870","https://openalex.org/W3035578002","https://openalex.org/W3036930808","https://openalex.org/W3036952806","https://openalex.org/W3037422790","https://openalex.org/W4247200422","https://openalex.org/W6687483927","https://openalex.org/W6729756640","https://openalex.org/W6741036071","https://openalex.org/W6755430541"],"related_works":[],"abstract_inverted_index":{"The":[0,28],"ability":[1,29],"to":[2,11,30,88,125,166,173,202],"transfer":[3,53],"adversarial":[4,81],"attacks":[5,82],"from":[6],"one":[7,151],"model":[8,13,122,136,178],"(the":[9,14],"surrogate)":[10],"another":[12],"victim)":[15],"has":[16,56,65],"been":[17],"an":[18,36,57],"issue":[19],"of":[20,39,79,105,177,190],"concern":[21],"within":[22],"the":[23,61,63,66,72,76,85,97,108,114,149,174,200],"machine":[24],"learning":[25],"(ML)":[26],"community.":[27],"successfully":[31],"evade":[32],"unseen":[33],"models":[34],"represents":[35],"uncomfortable":[37],"level":[38,104],"ease":[40],"toward":[41],"implementing":[42],"attacks.":[43],"In":[44],"this":[45,133,184],"work":[46],"we":[47],"note":[48],"that":[49,194],"as":[50,71],"studied,":[51],"current":[52],"attack":[54,137],"research":[55],"unrealistic":[58],"advantage":[59],"for":[60,162],"attacker:":[62],"attacker":[64,89,163,201],"exact":[67,109],"same":[68],"training":[69],"data":[70,86,110,144],"victim.":[73],"We":[74,182],"present":[75],"first":[77],"study":[78,176],"transferring":[80],"focusing":[83],"on":[84,207],"available":[87],"and":[90,130,154,164,171,180],"victim":[91],"under":[92],"imperfect":[93],"settings":[94],"without":[95],"querying":[96],"victim,":[98],"where":[99],"there":[100],"is":[101,123,140],"some":[102],"variable":[103],"overlap":[106,147],"in":[107,113,127,148],"used":[111],"or":[112,145],"classes":[115],"learned":[116],"by":[117,185],"each":[118,169],"model.":[119],"This":[120,158],"threat":[121,135],"relevant":[124],"applications":[126],"medicine,":[128],"malware,":[129],"others.":[131],"Under":[132],"new":[134],"success":[138],"rate":[139],"not":[141],"correlated":[142],"with":[143,156],"class":[146,196],"way":[150],"would":[152],"expect,":[153],"varies":[155],"dataset.":[157],"makes":[159],"it":[160],"difficult":[161],"defender":[165],"reason":[167],"about":[168],"other":[170],"contributes":[172],"broader":[175],"robustness":[179],"security.":[181],"remedy":[183],"developing":[186],"a":[187,205],"masked":[188],"version":[189],"Projected":[191],"Gradient":[192],"Descent":[193],"simulates":[195],"disparity,":[197],"which":[198],"enables":[199],"reliably":[203],"estimate":[204],"lower-bound":[206],"their":[208],"attack's":[209],"success.":[210]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2021-09-27T00:00:00"}
