{"id":"https://openalex.org/W4414360232","doi":"https://doi.org/10.24963/ijcai.2025/843","title":"Misclassification-driven Fingerprinting for DNNs Using Frequency-aware GANs","display_name":"Misclassification-driven Fingerprinting for DNNs Using Frequency-aware GANs","publication_year":2025,"publication_date":"2025-09-01","ids":{"openalex":"https://openalex.org/W4414360232","doi":"https://doi.org/10.24963/ijcai.2025/843"},"language":"en","primary_location":{"id":"doi:10.24963/ijcai.2025/843","is_oa":false,"landing_page_url":"https://doi.org/10.24963/ijcai.2025/843","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence","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/A5006767078","display_name":"Weixing Liu","orcid":"https://orcid.org/0009-0000-7604-637X"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Weixing Liu","raw_affiliation_strings":["Shenzhen University"],"affiliations":[{"raw_affiliation_string":"Shenzhen University","institution_ids":["https://openalex.org/I180726961"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5086801574","display_name":"Sheng-hua Zhong","orcid":"https://orcid.org/0000-0002-7524-5999"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shenghua Zhong","raw_affiliation_strings":["Shenzhen University"],"affiliations":[{"raw_affiliation_string":"Shenzhen University","institution_ids":["https://openalex.org/I180726961"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5006767078"],"corresponding_institution_ids":["https://openalex.org/I180726961"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.2602389,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"7580","last_page":"7588"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12740","display_name":"Gait Recognition and Analysis","score":0.8949000239372253,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12740","display_name":"Gait Recognition and Analysis","score":0.8949000239372253,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12702","display_name":"Brain Tumor Detection and Classification","score":0.8877999782562256,"subfield":{"id":"https://openalex.org/subfields/2808","display_name":"Neurology"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/fingerprint","display_name":"Fingerprint (computing)","score":0.631600022315979},{"id":"https://openalex.org/keywords/property","display_name":"Property (philosophy)","score":0.5196999907493591},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.4690000116825104},{"id":"https://openalex.org/keywords/source-code","display_name":"Source code","score":0.46560001373291016},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.459199994802475},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4214000105857849},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.4171999990940094}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.801800012588501},{"id":"https://openalex.org/C2777826928","wikidata":"https://www.wikidata.org/wiki/Q3745713","display_name":"Fingerprint (computing)","level":2,"score":0.631600022315979},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5412999987602234},{"id":"https://openalex.org/C189950617","wikidata":"https://www.wikidata.org/wiki/Q937228","display_name":"Property (philosophy)","level":2,"score":0.5196999907493591},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.4690000116825104},{"id":"https://openalex.org/C43126263","wikidata":"https://www.wikidata.org/wiki/Q128751","display_name":"Source code","level":2,"score":0.46560001373291016},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.459199994802475},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4422000050544739},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4214000105857849},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.4171999990940094},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.37720000743865967},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.37709999084472656},{"id":"https://openalex.org/C168406668","wikidata":"https://www.wikidata.org/wiki/Q178022","display_name":"Fingerprint recognition","level":3,"score":0.31929999589920044},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.29249998927116394},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.2687999904155731},{"id":"https://openalex.org/C40305131","wikidata":"https://www.wikidata.org/wiki/Q2616305","display_name":"Obfuscation","level":2,"score":0.2603999972343445},{"id":"https://openalex.org/C2778790127","wikidata":"https://www.wikidata.org/wiki/Q484885","display_name":"Erasure","level":2,"score":0.2547000050544739},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.2500999867916107}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.24963/ijcai.2025/843","is_oa":false,"landing_page_url":"https://doi.org/10.24963/ijcai.2025/843","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Deep":[0],"neural":[1],"networks":[2],"(DNNs)":[3],"have":[4],"become":[5],"valuable":[6],"assets":[7],"due":[8],"to":[9,32,46,53,79],"their":[10,16],"success":[11],"in":[12],"various":[13],"tasks,":[14],"but":[15,36,94],"high":[17,102],"training":[18,41],"costs":[19],"also":[20,95],"make":[21],"them":[22],"targets":[23],"for":[24,136],"model":[25,34],"theft.":[26],"Fingerprinting":[27],"techniques":[28],"are":[29],"commonly":[30],"used":[31],"verify":[33],"ownership,":[35],"existing":[37,126],"methods":[38,127],"either":[39],"require":[40],"many":[42],"additional":[43],"models,":[44],"leading":[45],"increased":[47],"costs,":[48],"or":[49],"rely":[50],"on":[51,117,145],"GANs":[52],"generate":[54],"fingerprints":[55],"near":[56],"decision":[57],"boundaries,":[58],"which":[59],"may":[60],"compromise":[61],"image":[62],"quality.":[63],"To":[64],"address":[65],"these":[66],"challenges,":[67],"we":[68],"propose":[69],"a":[70,111],"GAN-based":[71],"fingerprint":[72,97],"generation":[73],"method":[74,109],"that":[75,107],"applies":[76],"frequency-domain":[77],"perturbations":[78],"normal":[80],"samples,":[81],"effectively":[82],"creating":[83],"fingerprints.":[84],"This":[85],"approach":[86],"not":[87],"only":[88],"resists":[89],"intellectual":[90],"property":[91],"(IP)":[92],"threats,":[93],"improves":[96],"acquisition":[98],"efficiency":[99],"while":[100],"maintaining":[101],"imperceptibility.":[103],"Extensive":[104],"experiments":[105],"demonstrate":[106],"our":[108],"achieves":[110,132],"state-of-the-art":[112],"(SOTA)":[113],"AUC":[114],"of":[115,139],"0.98":[116],"the":[118,133,146],"Tiny-ImageNet":[119],"dataset":[120],"under":[121],"IP":[122,140],"removal":[123],"attacks,":[124],"outperforming":[125],"by":[128],"8%,":[129],"and":[130,142],"consistently":[131],"best":[134],"ABP":[135],"three":[137],"types":[138],"detection":[141],"erasure":[143],"attacks":[144],"GTSRB":[147],"dataset.":[148],"Our":[149],"source":[150],"code":[151],"is":[152],"available":[153],"at":[154],"https://github.com/wason981/Frequency-Fingerprinting.":[155]},"counts_by_year":[],"updated_date":"2026-03-07T16:01:11.037858","created_date":"2025-10-10T00:00:00"}
