{"id":"https://openalex.org/W7160245267","doi":"https://doi.org/10.1145/3811823","title":"Boosting Targeted Adversarial Transferability with Feature Contrastive Optimization","display_name":"Boosting Targeted Adversarial Transferability with Feature Contrastive Optimization","publication_year":2026,"publication_date":"2026-05-02","ids":{"openalex":"https://openalex.org/W7160245267","doi":"https://doi.org/10.1145/3811823"},"language":"en","primary_location":{"id":"doi:10.1145/3811823","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3811823","pdf_url":null,"source":{"id":"https://openalex.org/S19610489","display_name":"ACM Transactions on Multimedia Computing Communications and Applications","issn_l":"1551-6857","issn":["1551-6857","1551-6865"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Multimedia Computing, Communications, and Applications","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://doi.org/10.1145/3811823","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5103025575","display_name":"Jingtian Wang","orcid":"https://orcid.org/0009-0004-5346-9117"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jingtian Wang","raw_affiliation_strings":["Institute of Information Science, Beijing Key Laboratory of Advanced Information Science and Network Technology, Beijing Jiaotong University, Beijing, China"],"raw_orcid":"https://orcid.org/0009-0003-9005-1337","affiliations":[{"raw_affiliation_string":"Institute of Information Science, Beijing Key Laboratory of Advanced Information Science and Network Technology, Beijing Jiaotong University, Beijing, China","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135362713","display_name":"Xiaolong Li","orcid":"https://orcid.org/0000-0002-6111-9000"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaolong Li","raw_affiliation_strings":["Institute of Information Science, Beijing Key Laboratory of Advanced Information Science and Network Technology, Beijing Jiaotong University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-6111-9000","affiliations":[{"raw_affiliation_string":"Institute of Information Science, Beijing Key Laboratory of Advanced Information Science and Network Technology, Beijing Jiaotong University, Beijing, China","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135401053","display_name":"Jian Li","orcid":"https://orcid.org/0000-0002-5182-2798"},"institutions":[{"id":"https://openalex.org/I152269853","display_name":"Qilu University of Technology","ror":"https://ror.org/04hyzq608","country_code":"CN","type":"education","lineage":["https://openalex.org/I152269853"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jian Li","raw_affiliation_strings":["Qilu University of Technology, Jinan, China"],"raw_orcid":"https://orcid.org/0000-0002-5182-2798","affiliations":[{"raw_affiliation_string":"Qilu University of Technology, Jinan, China","institution_ids":["https://openalex.org/I152269853"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135363926","display_name":"Bin Ma","orcid":"https://orcid.org/0000-0002-9030-7393"},"institutions":[{"id":"https://openalex.org/I152269853","display_name":"Qilu University of Technology","ror":"https://ror.org/04hyzq608","country_code":"CN","type":"education","lineage":["https://openalex.org/I152269853"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bin Ma","raw_affiliation_strings":["Qilu University of Technology, Jinan, China"],"raw_orcid":"https://orcid.org/0000-0002-9030-7393","affiliations":[{"raw_affiliation_string":"Qilu University of Technology, Jinan, China","institution_ids":["https://openalex.org/I152269853"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135328137","display_name":"Yao Zhao","orcid":"https://orcid.org/0000-0002-8581-9554"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yao Zhao","raw_affiliation_strings":["Institute of Information Science, Beijing Key Laboratory of Advanced Information Science and Network Technology, Beijing Jiaotong University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-8581-9554","affiliations":[{"raw_affiliation_string":"Institute of Information Science, Beijing Key Laboratory of Advanced Information Science and Network Technology, Beijing Jiaotong University, Beijing, China","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102738347","display_name":"Jinhua Zeng","orcid":"https://orcid.org/0000-0002-8740-669X"},"institutions":[{"id":"https://openalex.org/I4210139944","display_name":"Institute of Forensic Science","ror":"https://ror.org/04ry60e05","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210089256","https://openalex.org/I4210127390","https://openalex.org/I4210139944"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jinhua Zeng","raw_affiliation_strings":["Academy of Forensic Science, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0002-6371-6490","affiliations":[{"raw_affiliation_string":"Academy of Forensic Science, Shanghai, China","institution_ids":["https://openalex.org/I4210139944"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.53114893,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"22","issue":"6","first_page":"1","last_page":"21"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9916999936103821,"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":0.9916999936103821,"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":0.0012000000569969416,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.0008999999845400453,"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/transferability","display_name":"Transferability","score":0.9002000093460083},{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.8640999794006348},{"id":"https://openalex.org/keywords/boosting","display_name":"Boosting (machine learning)","score":0.6825000047683716},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.48669999837875366},{"id":"https://openalex.org/keywords/deep-neural-networks","display_name":"Deep neural networks","score":0.4726000130176544},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.39640000462532043},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.39570000767707825},{"id":"https://openalex.org/keywords/construct","display_name":"Construct (python library)","score":0.37119999527931213},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.35749998688697815}],"concepts":[{"id":"https://openalex.org/C61272859","wikidata":"https://www.wikidata.org/wiki/Q7834031","display_name":"Transferability","level":3,"score":0.9002000093460083},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.8640999794006348},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8294000029563904},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.6825000047683716},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5985000133514404},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.48669999837875366},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.4726000130176544},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.460999995470047},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.39640000462532043},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.39570000767707825},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.37119999527931213},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.35749998688697815},{"id":"https://openalex.org/C147764199","wikidata":"https://www.wikidata.org/wiki/Q6865248","display_name":"Minification","level":2,"score":0.34950000047683716},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.34459999203681946},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.3255000114440918},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.31299999356269836},{"id":"https://openalex.org/C2778827112","wikidata":"https://www.wikidata.org/wiki/Q22245680","display_name":"Feature engineering","level":3,"score":0.3095000088214874},{"id":"https://openalex.org/C137836250","wikidata":"https://www.wikidata.org/wiki/Q984063","display_name":"Optimization problem","level":2,"score":0.30230000615119934},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.2980000078678131},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.29510000348091125},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.2944999933242798},{"id":"https://openalex.org/C117220453","wikidata":"https://www.wikidata.org/wiki/Q5172842","display_name":"Correlation","level":2,"score":0.29179999232292175},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.2822999954223633},{"id":"https://openalex.org/C18648836","wikidata":"https://www.wikidata.org/wiki/Q381892","display_name":"Compact space","level":2,"score":0.27489998936653137},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.2743000090122223},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.2718999981880188},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.25369998812675476}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3811823","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3811823","pdf_url":null,"source":{"id":"https://openalex.org/S19610489","display_name":"ACM Transactions on Multimedia Computing Communications and Applications","issn_l":"1551-6857","issn":["1551-6857","1551-6865"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Multimedia Computing, Communications, and Applications","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1145/3811823","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3811823","pdf_url":null,"source":{"id":"https://openalex.org/S19610489","display_name":"ACM Transactions on Multimedia Computing Communications and Applications","issn_l":"1551-6857","issn":["1551-6857","1551-6865"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Multimedia Computing, Communications, and Applications","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2676222800","display_name":null,"funder_award_id":"2024JDJH05","funder_id":"https://openalex.org/F4320328720","funder_display_name":"Qilu University of Technology"},{"id":"https://openalex.org/G7457925558","display_name":null,"funder_award_id":"62372037, U24B20179, 62272255, 62302248","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"},{"id":"https://openalex.org/F4320328720","display_name":"Qilu University of Technology","ror":"https://ror.org/04hyzq608"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W2183341477","https://openalex.org/W2194775991","https://openalex.org/W2531409750","https://openalex.org/W2774644650","https://openalex.org/W2962847335","https://openalex.org/W2962858109","https://openalex.org/W2962898354","https://openalex.org/W2963163009","https://openalex.org/W2963446712","https://openalex.org/W2963542245","https://openalex.org/W2969542116","https://openalex.org/W2969985801","https://openalex.org/W3035524453","https://openalex.org/W3035569111","https://openalex.org/W3171288285","https://openalex.org/W4214588794","https://openalex.org/W4214636423","https://openalex.org/W4214703392","https://openalex.org/W4312765682","https://openalex.org/W4380032277","https://openalex.org/W4386065604","https://openalex.org/W4386076145","https://openalex.org/W4390871946","https://openalex.org/W4398159858","https://openalex.org/W4400615477","https://openalex.org/W4401109681","https://openalex.org/W4402754002","https://openalex.org/W4414091831"],"related_works":[],"abstract_inverted_index":{"Transferable":[0],"adversarial":[1,68,134],"examples":[2],"(AEs)":[3],"have":[4],"attracted":[5],"considerable":[6],"attention":[7],"due":[8],"to":[9,12,49,85,93,98,141],"their":[10],"ability":[11],"expose":[13],"vulnerabilities":[14],"in":[15],"black-box":[16],"deep":[17],"neural":[18],"networks":[19],"(DNNs).":[20],"However,":[21],"achieving":[22],"superior":[23],"transferability":[24,69,169],"for":[25],"targeted":[26,57,99,168],"attacks":[27],"remains":[28],"a":[29,55,120,171],"challenge.":[30],"In":[31],"this":[32,128],"article,":[33],"inspired":[34],"by":[35,70],"the":[36,86,136,145,159],"observation":[37],"that":[38,96,163],"AEs":[39,138],"with":[40,144],"smaller":[41],"intra-class":[42,72],"distances":[43,47,73],"and":[44,74,89,106,115],"larger":[45],"inter-class":[46,76],"tend":[48],"exhibit":[50],"higher":[51],"transferability,":[52],"we":[53,79,109],"propose":[54,110],"novel":[56,121],"attack":[58,66],"based":[59],"on":[60,158],"Feature":[61,122],"Contrastive":[62,123],"Optimization":[63],"(FCO).":[64],"This":[65],"enhances":[67],"minimizing":[71],"maximizing":[75],"distances.":[77],"Specifically,":[78],"first":[80],"define":[81],"positive":[82,105],"samples":[83,91],"(belonging":[84,92],"target":[87,146],"class)":[88],"negative":[90,107],"non-target":[94,154],"classes)":[95],"correspond":[97],"AEs.":[100],"Subsequently,":[101],"leveraging":[102],"these":[103],"defined":[104],"samples,":[108],"two":[111],"metrics\u2014Intra-class":[112],"Compactness":[113],"(IC)":[114],"Inter-class":[116],"Separability":[117],"(IS)\u2014to":[118],"construct":[119],"(FC)":[124],"loss.":[125],"By":[126],"integrating":[127],"plug-and-play":[129],"FC":[130],"loss":[131],"into":[132],"standard":[133],"objectives,":[135],"generated":[137],"are":[139],"encouraged":[140],"better":[142],"align":[143],"class":[147],"distribution":[148],"while":[149],"diverging":[150],"from":[151],"those":[152],"of":[153,174],"classes.":[155],"Extensive":[156],"experiments":[157],"ImageNet-compatible":[160],"dataset":[161],"demonstrate":[162],"our":[164],"approach":[165],"consistently":[166],"improves":[167],"across":[170],"broad":[172],"range":[173],"DNN":[175],"architectures.":[176]},"counts_by_year":[],"updated_date":"2026-05-22T06:13:13.366637","created_date":"2026-05-06T00:00:00"}