{"id":"https://openalex.org/W4385482785","doi":"https://doi.org/10.1109/ijcnn54540.2023.10191679","title":"Generating Adversarial Examples with Better Transferability via Masking Unimportant Parameters of Surrogate Model","display_name":"Generating Adversarial Examples with Better Transferability via Masking Unimportant Parameters of Surrogate Model","publication_year":2023,"publication_date":"2023-06-18","ids":{"openalex":"https://openalex.org/W4385482785","doi":"https://doi.org/10.1109/ijcnn54540.2023.10191679"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn54540.2023.10191679","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn54540.2023.10191679","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5000883962","display_name":"Dingcheng Yang","orcid":"https://orcid.org/0000-0001-5313-4481"},"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":"Dingcheng Yang","raw_affiliation_strings":["BNRist, Tsinghua University,Dept. Computer Science &#x0026; Tech.,Beijing,China","RealAI"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"BNRist, Tsinghua University,Dept. Computer Science &#x0026; Tech.,Beijing,China","institution_ids":["https://openalex.org/I99065089"]},{"raw_affiliation_string":"RealAI","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053437305","display_name":"Wenjian Yu","orcid":"https://orcid.org/0000-0003-4897-7251"},"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":"Wenjian Yu","raw_affiliation_strings":["BNRist, Tsinghua University,Dept. Computer Science &#x0026; Tech.,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"BNRist, Tsinghua University,Dept. Computer Science &#x0026; Tech.,Beijing,China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065750423","display_name":"Zihao Xiao","orcid":"https://orcid.org/0000-0002-2240-2778"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zihao Xiao","raw_affiliation_strings":["RealAI"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"RealAI","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5088401907","display_name":"Jiaqi Luo","orcid":"https://orcid.org/0000-0001-6903-8515"},"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":"Jiaqi Luo","raw_affiliation_strings":["BNRist, Tsinghua University,Dept. Computer Science &#x0026; Tech.,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"BNRist, Tsinghua University,Dept. Computer Science &#x0026; Tech.,Beijing,China","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"01","last_page":"08"},"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":0.972000002861023,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.9491815567016602},{"id":"https://openalex.org/keywords/transferability","display_name":"Transferability","score":0.8910032510757446},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7760738134384155},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.615967333316803},{"id":"https://openalex.org/keywords/surrogate-model","display_name":"Surrogate model","score":0.5463708639144897},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5438646674156189},{"id":"https://openalex.org/keywords/masking","display_name":"Masking (illustration)","score":0.5434281229972839},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4701816141605377},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.06255728006362915}],"concepts":[{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.9491815567016602},{"id":"https://openalex.org/C61272859","wikidata":"https://www.wikidata.org/wiki/Q7834031","display_name":"Transferability","level":3,"score":0.8910032510757446},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7760738134384155},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.615967333316803},{"id":"https://openalex.org/C131675550","wikidata":"https://www.wikidata.org/wiki/Q7646884","display_name":"Surrogate model","level":2,"score":0.5463708639144897},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5438646674156189},{"id":"https://openalex.org/C2777402240","wikidata":"https://www.wikidata.org/wiki/Q6783436","display_name":"Masking (illustration)","level":2,"score":0.5434281229972839},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4701816141605377},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.06255728006362915},{"id":"https://openalex.org/C140331021","wikidata":"https://www.wikidata.org/wiki/Q1868104","display_name":"Logit","level":2,"score":0.0},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"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/C153349607","wikidata":"https://www.wikidata.org/wiki/Q36649","display_name":"Visual arts","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn54540.2023.10191679","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn54540.2023.10191679","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G6122589074","display_name":null,"funder_award_id":"2020AAA0103502","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":33,"referenced_works":["https://openalex.org/W1673923490","https://openalex.org/W1686810756","https://openalex.org/W1945616565","https://openalex.org/W2095705004","https://openalex.org/W2119144962","https://openalex.org/W2183341477","https://openalex.org/W2620038827","https://openalex.org/W2707890836","https://openalex.org/W2774018344","https://openalex.org/W2774644650","https://openalex.org/W2962847335","https://openalex.org/W2962965870","https://openalex.org/W2963542245","https://openalex.org/W2963744840","https://openalex.org/W2963920068","https://openalex.org/W2964350391","https://openalex.org/W2969542116","https://openalex.org/W2976752987","https://openalex.org/W2997583194","https://openalex.org/W3118608800","https://openalex.org/W3127807678","https://openalex.org/W4281760954","https://openalex.org/W6637162671","https://openalex.org/W6637373629","https://openalex.org/W6640425456","https://openalex.org/W6674330103","https://openalex.org/W6677103964","https://openalex.org/W6677580257","https://openalex.org/W6726275242","https://openalex.org/W6739917289","https://openalex.org/W6746402973","https://openalex.org/W6768366551","https://openalex.org/W6838510352"],"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":{"Deep":[0],"neural":[1],"networks":[2],"(DNNs)":[3],"have":[4],"been":[5],"shown":[6],"to":[7,10,46,53,67,89,95,110,160],"be":[8,134],"vulnerable":[9],"adversarial":[11,18,30,49,60,72,126,144,154],"examples.":[12,61,127,155],"Moreover,":[13],"the":[14,17,47,55,58,69,75,91,97,112,117,123,149,152,162,165],"transferability":[15,56,70,150],"of":[16,57,71,125,151,164],"examples":[19,31,73],"has":[20],"received":[21],"broad":[22],"attention":[23],"in":[24,74,86],"recent":[25],"years,":[26],"which":[27,51],"means":[28],"that":[29],"crafted":[32],"by":[33],"a":[34,104],"surrogate":[35,93],"model":[36],"can":[37,133],"also":[38],"attack":[39,77],"unknown":[40],"models.":[41],"This":[42,128],"phenomenon":[43],"gave":[44],"birth":[45],"transfer-based":[48,76,98],"attacks,":[50],"aim":[52],"improve":[54,68],"generated":[59,153],"In":[62],"this":[63,102],"paper,":[64],"we":[65],"propose":[66],"via":[78],"masking":[79],"unimportant":[80,118],"parameters":[81,119],"(MUP).":[82],"The":[83],"key":[84],"idea":[85],"MUP":[87],"is":[88,108,130],"refine":[90],"pretrained":[92],"models":[94],"boost":[96],"attack.":[99],"Based":[100],"on":[101],"idea,":[103],"Taylor":[105],"expansion-based":[106],"metric":[107],"used":[109],"evaluate":[111],"parameter":[113],"importance":[114],"score":[115],"and":[116],"are":[120,158],"masked":[121],"during":[122],"generation":[124],"process":[129],"simple,":[131],"yet":[132],"naturally":[135],"combined":[136],"with":[137],"various":[138],"existing":[139],"gradient-based":[140],"optimizers":[141],"for":[142],"generating":[143],"examples,":[145],"thus":[146],"further":[147],"improving":[148],"Extensive":[156],"experiments":[157],"conducted":[159],"validate":[161],"effectiveness":[163],"proposed":[166],"MUP-based":[167],"methods.":[168]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":3}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
