{"id":"https://openalex.org/W4409156331","doi":"https://doi.org/10.1109/trustcom63139.2024.00124","title":"Boosting Transferability of Adversarial Examples by Joint Training and Dual Feature Mixup","display_name":"Boosting Transferability of Adversarial Examples by Joint Training and Dual Feature Mixup","publication_year":2024,"publication_date":"2024-12-17","ids":{"openalex":"https://openalex.org/W4409156331","doi":"https://doi.org/10.1109/trustcom63139.2024.00124"},"language":"en","primary_location":{"id":"doi:10.1109/trustcom63139.2024.00124","is_oa":false,"landing_page_url":"https://doi.org/10.1109/trustcom63139.2024.00124","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE 23rd International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom)","raw_type":"proceedings-article"},"type":"article","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/A5111286483","display_name":"Mengmeng Tang","orcid":null},"institutions":[{"id":"https://openalex.org/I37987034","display_name":"Guangzhou University","ror":"https://ror.org/05ar8rn06","country_code":"CN","type":"education","lineage":["https://openalex.org/I37987034"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Mengmeng Tang","raw_affiliation_strings":["Guangzhou University,School of Computer Science and Cyber Engineering,Guangzhou,China,510006"],"affiliations":[{"raw_affiliation_string":"Guangzhou University,School of Computer Science and Cyber Engineering,Guangzhou,China,510006","institution_ids":["https://openalex.org/I37987034"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010187139","display_name":"Shuhong Chen","orcid":"https://orcid.org/0000-0002-6120-6358"},"institutions":[{"id":"https://openalex.org/I37987034","display_name":"Guangzhou University","ror":"https://ror.org/05ar8rn06","country_code":"CN","type":"education","lineage":["https://openalex.org/I37987034"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuhong Chen","raw_affiliation_strings":["Guangzhou University,School of Computer Science and Cyber Engineering,Guangzhou,China,510006"],"affiliations":[{"raw_affiliation_string":"Guangzhou University,School of Computer Science and Cyber Engineering,Guangzhou,China,510006","institution_ids":["https://openalex.org/I37987034"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100386734","display_name":"Guojun Wang","orcid":"https://orcid.org/0000-0002-9815-749X"},"institutions":[{"id":"https://openalex.org/I37987034","display_name":"Guangzhou University","ror":"https://ror.org/05ar8rn06","country_code":"CN","type":"education","lineage":["https://openalex.org/I37987034"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guojun Wang","raw_affiliation_strings":["Guangzhou University,School of Computer Science and Cyber Engineering,Guangzhou,China,510006"],"affiliations":[{"raw_affiliation_string":"Guangzhou University,School of Computer Science and Cyber Engineering,Guangzhou,China,510006","institution_ids":["https://openalex.org/I37987034"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5071554167","display_name":"Hanjun Li","orcid":"https://orcid.org/0000-0002-7017-8782"},"institutions":[{"id":"https://openalex.org/I37987034","display_name":"Guangzhou University","ror":"https://ror.org/05ar8rn06","country_code":"CN","type":"education","lineage":["https://openalex.org/I37987034"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hanjun Li","raw_affiliation_strings":["Guangzhou University,School of Computer Science and Cyber Engineering,Guangzhou,China,510006"],"affiliations":[{"raw_affiliation_string":"Guangzhou University,School of Computer Science and Cyber Engineering,Guangzhou,China,510006","institution_ids":["https://openalex.org/I37987034"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Zhuyi Yao","orcid":null},"institutions":[{"id":"https://openalex.org/I37987034","display_name":"Guangzhou University","ror":"https://ror.org/05ar8rn06","country_code":"CN","type":"education","lineage":["https://openalex.org/I37987034"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhuyi Yao","raw_affiliation_strings":["Guangzhou University,School of Computer Science and Cyber Engineering,Guangzhou,China,510006"],"affiliations":[{"raw_affiliation_string":"Guangzhou University,School of Computer Science and Cyber Engineering,Guangzhou,China,510006","institution_ids":["https://openalex.org/I37987034"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5076576641","display_name":"Sheng Wen","orcid":"https://orcid.org/0000-0003-0655-666X"},"institutions":[{"id":"https://openalex.org/I57093077","display_name":"Swinburne University of Technology","ror":"https://ror.org/031rekg67","country_code":"AU","type":"education","lineage":["https://openalex.org/I57093077"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Sheng Wen","raw_affiliation_strings":["Swinburne University of Technology,Blockchain Innovation Lab,Victoria,Australia,3122"],"affiliations":[{"raw_affiliation_string":"Swinburne University of Technology,Blockchain Innovation Lab,Victoria,Australia,3122","institution_ids":["https://openalex.org/I57093077"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5111286483"],"corresponding_institution_ids":["https://openalex.org/I37987034"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.25940436,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"826","last_page":"833"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.995199978351593,"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":0.995199978351593,"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":0.9549000263214111,"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/T13114","display_name":"Image Processing Techniques and Applications","score":0.9434999823570251,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/boosting","display_name":"Boosting (machine learning)","score":0.8550119400024414},{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.8535439372062683},{"id":"https://openalex.org/keywords/transferability","display_name":"Transferability","score":0.8190395832061768},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6972826719284058},{"id":"https://openalex.org/keywords/dual","display_name":"Dual (grammatical number)","score":0.6350632905960083},{"id":"https://openalex.org/keywords/joint","display_name":"Joint (building)","score":0.6282349824905396},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.574176549911499},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5061039328575134},{"id":"https://openalex.org/keywords/training","display_name":"Training (meteorology)","score":0.49285364151000977},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4236885607242584},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.41423434019088745},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.4100000858306885},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.13341188430786133}],"concepts":[{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.8550119400024414},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.8535439372062683},{"id":"https://openalex.org/C61272859","wikidata":"https://www.wikidata.org/wiki/Q7834031","display_name":"Transferability","level":3,"score":0.8190395832061768},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6972826719284058},{"id":"https://openalex.org/C2780980858","wikidata":"https://www.wikidata.org/wiki/Q110022","display_name":"Dual (grammatical number)","level":2,"score":0.6350632905960083},{"id":"https://openalex.org/C18555067","wikidata":"https://www.wikidata.org/wiki/Q8375051","display_name":"Joint (building)","level":2,"score":0.6282349824905396},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.574176549911499},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5061039328575134},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.49285364151000977},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4236885607242584},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.41423434019088745},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.4100000858306885},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.13341188430786133},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"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/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C124952713","wikidata":"https://www.wikidata.org/wiki/Q8242","display_name":"Literature","level":1,"score":0.0},{"id":"https://openalex.org/C170154142","wikidata":"https://www.wikidata.org/wiki/Q150737","display_name":"Architectural engineering","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C140331021","wikidata":"https://www.wikidata.org/wiki/Q1868104","display_name":"Logit","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/trustcom63139.2024.00124","is_oa":false,"landing_page_url":"https://doi.org/10.1109/trustcom63139.2024.00124","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE 23rd International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":36,"referenced_works":["https://openalex.org/W2183341477","https://openalex.org/W2194775991","https://openalex.org/W2603766943","https://openalex.org/W2620038827","https://openalex.org/W2774018344","https://openalex.org/W2774644650","https://openalex.org/W2953303875","https://openalex.org/W2962847335","https://openalex.org/W2962898354","https://openalex.org/W2963037989","https://openalex.org/W2963542245","https://openalex.org/W2963771536","https://openalex.org/W2969542116","https://openalex.org/W3034190247","https://openalex.org/W3109877713","https://openalex.org/W3127807678","https://openalex.org/W3171288285","https://openalex.org/W3177184533","https://openalex.org/W4226378932","https://openalex.org/W4293846201","https://openalex.org/W4306317081","https://openalex.org/W4312790346","https://openalex.org/W4386065469","https://openalex.org/W4386081609","https://openalex.org/W6640425456","https://openalex.org/W6731927902","https://openalex.org/W6745136726","https://openalex.org/W6745272055","https://openalex.org/W6746402973","https://openalex.org/W6755430541","https://openalex.org/W6758684365","https://openalex.org/W6768366551","https://openalex.org/W6792024551","https://openalex.org/W6839623149","https://openalex.org/W6845892164","https://openalex.org/W6853649152"],"related_works":["https://openalex.org/W4288055406","https://openalex.org/W4200630034","https://openalex.org/W3137894200","https://openalex.org/W3092178728","https://openalex.org/W4226402597","https://openalex.org/W3132910851","https://openalex.org/W4377864639","https://openalex.org/W4392340763","https://openalex.org/W4283325551","https://openalex.org/W4403006689"],"abstract_inverted_index":{"The":[0,14,87],"transferability":[1,56,152],"of":[2,30,49,57,104,112,153,159],"adversarial":[3,32,38,113],"examples":[4,134,145],"is":[5],"pivotal":[6],"in":[7],"black-box":[8],"attacks":[9,17],"on":[10,20,45],"deep":[11],"learning":[12],"models.":[13],"existing":[15],"transfer-based":[16],"typically":[18],"rely":[19],"a":[21,36,66,121],"single":[22,37],"data":[23],"augmentation":[24],"technique,":[25],"which":[26,76],"hampers":[27],"the":[28,46,50,55,78,101,110,116,129,141,151,154,160],"diversity":[29,111],"generated":[31,51,155],"examples.":[33,59,114,156],"Additionally,":[34],"applying":[35],"noise":[39],"generation":[40],"path":[41],"may":[42],"impose":[43],"limitations":[44],"perturbation":[47],"strength":[48],"noise,":[52],"thereby":[53,149],"compromising":[54],"these":[58,62],"To":[60],"address":[61],"issues,":[63],"we":[64],"propose":[65],"framework":[67],"called":[68],"Joint":[69],"Training":[70],"and":[71,83,97,108,135,146,172],"Dual":[72],"Feature":[73],"Mixiup":[74],"(JFM),":[75],"comprises":[77],"dual":[79,88],"feature":[80,89,93,133],"mixup":[81,90],"module":[82,91,119],"joint":[84,117],"training":[85,118],"module.":[86],"performs":[92],"mixing":[94],"between":[95,131,143],"benign":[96,105,136,147],"augmented":[98,144],"images,":[99],"enabling":[100],"comprehensive":[102],"extraction":[103],"example":[106],"features":[107],"enhancing":[109,150],"Furthermore,":[115],"designs":[120],"dual-path":[122],"prediction":[123],"loss":[124,130,142],"function":[125],"that":[126,164],"incorporates":[127],"both":[128],"mixed":[132],"examples,":[137,148],"as":[138,140],"well":[139],"Empirical":[157],"evaluation":[158],"ImageNet-compatible":[161],"dataset":[162],"demonstrates":[163],"our":[165],"JFM":[166],"method":[167],"exhibits":[168],"superior":[169],"attack":[170],"capability":[171],"significantly":[173],"outperforms":[174],"state-of-the-art":[175],"methods.":[176]},"counts_by_year":[],"updated_date":"2026-04-21T08:09:41.155169","created_date":"2025-10-10T00:00:00"}