{"id":"https://openalex.org/W4316660635","doi":"https://doi.org/10.1109/tpami.2022.3194988","title":"Generalizable Black-Box Adversarial Attack With Meta Learning","display_name":"Generalizable Black-Box Adversarial Attack With Meta Learning","publication_year":2023,"publication_date":"2023-01-16","ids":{"openalex":"https://openalex.org/W4316660635","doi":"https://doi.org/10.1109/tpami.2022.3194988","pmid":"https://pubmed.ncbi.nlm.nih.gov/37021863"},"language":"en","primary_location":{"id":"doi:10.1109/tpami.2022.3194988","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.2022.3194988","pdf_url":null,"source":{"id":"https://openalex.org/S199944782","display_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","issn_l":"0162-8828","issn":["0162-8828","1939-3539","2160-9292"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","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 Pattern Analysis and Machine Intelligence","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/A5004461283","display_name":"Fei Yin","orcid":"https://orcid.org/0000-0002-5146-7685"},"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":"Fei Yin","raw_affiliation_strings":["Tsinghua Shenzhen International Graduate School, Tsinghua University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-5146-7685","affiliations":[{"raw_affiliation_string":"Tsinghua Shenzhen International Graduate School, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Yong Zhang","orcid":"https://orcid.org/0000-0003-2183-5990"},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yong Zhang","raw_affiliation_strings":["Tencent AI Lab, Shenzhen, Guangdong, China"],"raw_orcid":"https://orcid.org/0000-0003-2183-5990","affiliations":[{"raw_affiliation_string":"Tencent AI Lab, Shenzhen, Guangdong, China","institution_ids":["https://openalex.org/I2250653659"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Baoyuan Wu","orcid":"https://orcid.org/0000-0003-0066-3448"},"institutions":[{"id":"https://openalex.org/I4210099586","display_name":"Shenzhen Research Institute of Big Data","ror":"https://ror.org/00z1gwf89","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210099586"]},{"id":"https://openalex.org/I4210116924","display_name":"Chinese University of Hong Kong, Shenzhen","ror":"https://ror.org/02d5ks197","country_code":"CN","type":"education","lineage":["https://openalex.org/I177725633","https://openalex.org/I180726961","https://openalex.org/I4210116924"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Baoyuan Wu","raw_affiliation_strings":["School of Data Science, Shenzhen Research Institute of Big Data, Chinese University of Hong Kong, Shenzhen, China"],"raw_orcid":"https://orcid.org/0000-0003-0066-3448","affiliations":[{"raw_affiliation_string":"School of Data Science, Shenzhen Research Institute of Big Data, Chinese University of Hong Kong, Shenzhen, China","institution_ids":["https://openalex.org/I4210099586","https://openalex.org/I4210116924"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101581699","display_name":"Yan Feng","orcid":"https://orcid.org/0000-0002-8508-4973"},"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":"Yan Feng","raw_affiliation_strings":["Tsinghua Shenzhen International Graduate School, Tsinghua University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tsinghua Shenzhen International Graduate School, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075847982","display_name":"Jingyi Zhang","orcid":"https://orcid.org/0000-0003-1909-6332"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jingyi Zhang","raw_affiliation_strings":["Center for Future Media and the School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, China"],"raw_orcid":"https://orcid.org/0000-0003-1909-6332","affiliations":[{"raw_affiliation_string":"Center for Future Media and the School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5064391513","display_name":"Yanbo Fan","orcid":"https://orcid.org/0000-0002-8530-485X"},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yanbo Fan","raw_affiliation_strings":["Tencent AI Lab, Shenzhen, Guangdong, China"],"raw_orcid":"https://orcid.org/0000-0002-8530-485X","affiliations":[{"raw_affiliation_string":"Tencent AI Lab, Shenzhen, Guangdong, China","institution_ids":["https://openalex.org/I2250653659"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5020953714","display_name":"Yujiu Yang","orcid":"https://orcid.org/0000-0002-6427-1024"},"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":"Yujiu Yang","raw_affiliation_strings":["Tsinghua Shenzhen International Graduate School, Tsinghua University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-6427-1024","affiliations":[{"raw_affiliation_string":"Tsinghua Shenzhen International Graduate School, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":6.1541,"has_fulltext":false,"cited_by_count":47,"citation_normalized_percentile":{"value":0.97251444,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"46","issue":"3","first_page":"1804","last_page":"1818"},"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":0.9779000282287598,"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":0.9745000004768372,"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":0.843660295009613},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6782287359237671},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6452056765556335},{"id":"https://openalex.org/keywords/black-box","display_name":"Black box","score":0.6209810376167297},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.47721534967422485},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.3521212935447693}],"concepts":[{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.843660295009613},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6782287359237671},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6452056765556335},{"id":"https://openalex.org/C94966114","wikidata":"https://www.wikidata.org/wiki/Q29256","display_name":"Black box","level":2,"score":0.6209810376167297},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.47721534967422485},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.3521212935447693}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tpami.2022.3194988","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.2022.3194988","pdf_url":null,"source":{"id":"https://openalex.org/S199944782","display_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","issn_l":"0162-8828","issn":["0162-8828","1939-3539","2160-9292"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","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 Pattern Analysis and Machine Intelligence","raw_type":"journal-article"},{"id":"pmid:37021863","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/37021863","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 pattern analysis and machine intelligence","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1669161342","display_name":null,"funder_award_id":"62076213","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3931585407","display_name":null,"funder_award_id":"U1903213","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"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":72,"referenced_works":["https://openalex.org/W2070792261","https://openalex.org/W2117539524","https://openalex.org/W2183341477","https://openalex.org/W2302255633","https://openalex.org/W2408141691","https://openalex.org/W2543927648","https://openalex.org/W2612637113","https://openalex.org/W2746600820","https://openalex.org/W2774644650","https://openalex.org/W2905311601","https://openalex.org/W2950808778","https://openalex.org/W2962847335","https://openalex.org/W2962971773","https://openalex.org/W2963446712","https://openalex.org/W2963542245","https://openalex.org/W2963857521","https://openalex.org/W2964137095","https://openalex.org/W2964205597","https://openalex.org/W2969542116","https://openalex.org/W2972986629","https://openalex.org/W2977099891","https://openalex.org/W2984699060","https://openalex.org/W2998106940","https://openalex.org/W3015625436","https://openalex.org/W3034619610","https://openalex.org/W3034892461","https://openalex.org/W3035447895","https://openalex.org/W3080297477","https://openalex.org/W3105976275","https://openalex.org/W3106412272","https://openalex.org/W3107235539","https://openalex.org/W3118608800","https://openalex.org/W3171288285","https://openalex.org/W3202707779","https://openalex.org/W4214502238","https://openalex.org/W4288083516","https://openalex.org/W4293846201","https://openalex.org/W4294646197","https://openalex.org/W4312513141","https://openalex.org/W4382318428","https://openalex.org/W6631190155","https://openalex.org/W6637373629","https://openalex.org/W6640425456","https://openalex.org/W6714069269","https://openalex.org/W6731927902","https://openalex.org/W6741036071","https://openalex.org/W6745272055","https://openalex.org/W6746608116","https://openalex.org/W6750254146","https://openalex.org/W6750404860","https://openalex.org/W6752985256","https://openalex.org/W6753044988","https://openalex.org/W6759158001","https://openalex.org/W6759424558","https://openalex.org/W6759580348","https://openalex.org/W6761100157","https://openalex.org/W6761833289","https://openalex.org/W6763151900","https://openalex.org/W6763511984","https://openalex.org/W6764550947","https://openalex.org/W6767666165","https://openalex.org/W6768366551","https://openalex.org/W6769581535","https://openalex.org/W6771543752","https://openalex.org/W6771809012","https://openalex.org/W6771961379","https://openalex.org/W6773713311","https://openalex.org/W6776690448","https://openalex.org/W6780986092","https://openalex.org/W6784025586","https://openalex.org/W6787972765","https://openalex.org/W6788235018"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4306674287","https://openalex.org/W4387369504","https://openalex.org/W3046775127","https://openalex.org/W4394896187","https://openalex.org/W3170094116","https://openalex.org/W4386462264","https://openalex.org/W3009622996","https://openalex.org/W3107602296","https://openalex.org/W3037859390"],"abstract_inverted_index":{"In":[0],"the":[1,7,14,33,59,72,104,113,117,133,151,164,167,174],"scenario":[2],"of":[3,116,177],"black-box":[4,39],"adversarial":[5,21,67,147,178],"attack,":[6],"target":[8,168],"model's":[9],"parameters":[10],"are":[11],"unknown,":[12],"and":[13],"attacker":[15],"aims":[16],"to":[17,32,57,91,127,139,149,162,190],"find":[18],"a":[19,28,83,88,100,123,141,155],"successful":[20],"perturbation":[22],"based":[23,111],"on":[24,74,95,112,154],"query":[25,29,53],"feedback":[26,35,60,114],"under":[27],"budget.":[30],"Due":[31],"limited":[34],"information,":[36],"existing":[37],"query-based":[38,187],"attack":[40,73,165,188],"methods":[41,189],"often":[42],"require":[43],"many":[44,137],"queries":[45,138],"for":[46],"attacking":[47,99],"each":[48,75],"benign":[49,76,96,102],"example.":[50],"To":[51],"reduce":[52],"cost,":[54],"we":[55,81,144],"propose":[56],"utilize":[58,145],"information":[61,115],"across":[62],"historical":[63,125],"attacks,":[64],"dubbed":[65],"example-level":[66],"transferability.":[68],"Specifically,":[69],"by":[70,86,197],"treating":[71],"example":[77],"as":[78,120,122],"one":[79],"task,":[80],"develop":[82],"meta-learning":[84],"framework":[85,172],"training":[87],"meta":[89,105,152],"generator":[90,106,153],"produce":[92,128],"perturbations":[93],"conditioned":[94],"examples.":[97],"When":[98],"new":[101,118],"example,":[103],"can":[107,180],"be":[108,181],"quickly":[109],"fine-tuned":[110],"task":[119],"well":[121],"few":[124],"attacks":[126],"effective":[129],"perturbations.":[130],"Moreover,":[131],"since":[132],"meta-train":[134],"procedure":[135],"consumes":[136],"learn":[140],"generalizable":[142],"generator,":[143],"model-level":[146],"transferability":[148,179],"train":[150],"white-box":[156],"surrogate":[157],"model,":[158],"then":[159],"transfer":[160],"it":[161],"help":[163],"against":[166],"model.":[169],"The":[170,200],"proposed":[171],"with":[173,184],"two":[175],"types":[176],"naturally":[182],"combined":[183],"any":[185],"off-the-shelf":[186],"boost":[191],"their":[192],"performance,":[193],"which":[194],"is":[195,203],"verified":[196],"extensive":[198],"experiments.":[199],"source":[201],"code":[202],"available":[204],"at":[205],"https://github.com/SCLBD/MCG-Blackbox.":[206]},"counts_by_year":[{"year":2026,"cited_by_count":10},{"year":2025,"cited_by_count":21},{"year":2024,"cited_by_count":16}],"updated_date":"2026-07-29T09:40:50.615796","created_date":"2025-10-10T00:00:00"}
