{"id":"https://openalex.org/W4290945651","doi":"https://doi.org/10.1145/3534678.3539257","title":"MetaV","display_name":"MetaV","publication_year":2022,"publication_date":"2022-08-12","ids":{"openalex":"https://openalex.org/W4290945651","doi":"https://doi.org/10.1145/3534678.3539257"},"language":"en","primary_location":{"id":"doi:10.1145/3534678.3539257","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3534678.3539257","pdf_url":null,"source":{"id":"https://openalex.org/S4363608767","display_name":"Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","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/A5074846459","display_name":"Xudong Pan","orcid":"https://orcid.org/0000-0003-1394-0395"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xudong Pan","raw_affiliation_strings":["Fudan University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101925931","display_name":"Yifan Yan","orcid":"https://orcid.org/0000-0002-0273-3967"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yifan Yan","raw_affiliation_strings":["Fudan University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101652939","display_name":"Mi Zhang","orcid":"https://orcid.org/0000-0003-3567-3478"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mi Zhang","raw_affiliation_strings":["Fudan University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5052437722","display_name":"Min Yang","orcid":"https://orcid.org/0000-0001-9714-5545"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Min Yang","raw_affiliation_strings":["Fudan University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I24943067"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":20,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1327","last_page":"1336"},"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/T12357","display_name":"Digital Media Forensic Detection","score":0.9926999807357788,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9811000227928162,"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/computer-science","display_name":"Computer science","score":0.8531812429428101},{"id":"https://openalex.org/keywords/generality","display_name":"Generality","score":0.6639153957366943},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6224747896194458},{"id":"https://openalex.org/keywords/fingerprint","display_name":"Fingerprint (computing)","score":0.5925065875053406},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5544106364250183},{"id":"https://openalex.org/keywords/suspect","display_name":"Suspect","score":0.5130795240402222},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.4483812153339386},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.43453463912010193},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.35378265380859375}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8531812429428101},{"id":"https://openalex.org/C2780767217","wikidata":"https://www.wikidata.org/wiki/Q5532421","display_name":"Generality","level":2,"score":0.6639153957366943},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6224747896194458},{"id":"https://openalex.org/C2777826928","wikidata":"https://www.wikidata.org/wiki/Q3745713","display_name":"Fingerprint (computing)","level":2,"score":0.5925065875053406},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5544106364250183},{"id":"https://openalex.org/C2778223634","wikidata":"https://www.wikidata.org/wiki/Q224952","display_name":"Suspect","level":2,"score":0.5130795240402222},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.4483812153339386},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.43453463912010193},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.35378265380859375},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C542102704","wikidata":"https://www.wikidata.org/wiki/Q183257","display_name":"Psychotherapist","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3534678.3539257","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3534678.3539257","pdf_url":null,"source":{"id":"https://openalex.org/S4363608767","display_name":"Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions","score":0.5}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":10,"referenced_works":["https://openalex.org/W2063280109","https://openalex.org/W2243397390","https://openalex.org/W2350778671","https://openalex.org/W2579318729","https://openalex.org/W2581082771","https://openalex.org/W2806082141","https://openalex.org/W2963453233","https://openalex.org/W2965658867","https://openalex.org/W3126682091","https://openalex.org/W3148576306"],"related_works":["https://openalex.org/W3197016913","https://openalex.org/W2045049461","https://openalex.org/W1978893398","https://openalex.org/W2201908702","https://openalex.org/W4381094582","https://openalex.org/W2389153751","https://openalex.org/W2369625323","https://openalex.org/W2364579609","https://openalex.org/W1977906818","https://openalex.org/W1522139108"],"abstract_inverted_index":{"Protecting":[0],"the":[1,33,37,49,54,58,70,90,108,135,139,147,160,164,168,177,184,188,194,210,217,223,270],"intellectual":[2],"property":[3],"(IP)":[4],"of":[5,72,104,119,163,174,214,226,257],"deep":[6],"neural":[7],"networks":[8],"(DNN)":[9],"becomes":[10],"an":[11,262],"urgent":[12],"concern":[13],"for":[14,32,228,238],"IT":[15],"corporations.":[16],"For":[17,232],"model":[18,22,35,44,51,93,155,166,185],"piracy":[19],"forensics,":[20],"previous":[21,126],"fingerprinting":[23,94,98,219,235],"schemes":[24,127,220],"are":[25,142],"commonly":[26],"based":[27,158],"on":[28,57,69,99,159,167,183,234,252],"adversarial":[29],"examples":[30,60],"constructed":[31],"owner's":[34],"as":[36],"fingerprint,":[38],"and":[39,112,138,197,203,221,248],"verify":[40],"whether":[41,152],"a":[42,100,117,153,172,253],"suspect":[43,154,165,259],"is":[45,156],"indeed":[46],"pirated":[47],"from":[48,107],"original":[50],"by":[52],"matching":[53],"behavioral":[55],"pattern":[56],"fingerprint":[59,137],"between":[61],"one":[62],"another.":[63],"However,":[64],"these":[65],"methods":[66],"heavily":[67],"rely":[68],"characteristics":[71],"classification":[73],"tasks":[74],"which":[75,96,141],"inhibits":[76],"their":[77],"application":[78],"to":[79,150],"more":[80],"general":[81],"scenarios.":[82],"To":[83],"address":[84],"this":[85],"issue,":[86],"we":[87,124],"present":[88],"MetaV,":[89],"first":[91],"task-agnostic":[92,230],"framework":[95],"enables":[97],"much":[101],"wider":[102],"range":[103],"DNNs":[105],"independent":[106],"downstream":[109],"learning":[110],"task,":[111],"exhibits":[113],"strong":[114],"robustness":[115],"against":[116],"variety":[118],"ownership":[120],"obfuscation":[121],"techniques.":[122],"Specifically,":[123],"generalize":[125],"into":[128],"two":[129],"critical":[130],"design":[131],"components":[132],"in":[133,187,267],"MetaV:":[134],"adaptive":[136,169],"meta-verifier,":[140],"jointly":[143],"optimized":[144],"such":[145],"that":[146],"meta-verifier":[148],"learns":[149],"determine":[151],"stolen":[157],"concatenated":[161],"outputs":[162],"fingerprint.":[170],"As":[171],"key":[173],"being":[175],"task-agnostic,":[176],"full":[178],"process":[179],"makes":[180],"no":[181],"assumption":[182],"internals":[186],"ensemble":[189],"only":[190],"if":[191],"they":[192],"have":[193],"same":[195],"input":[196],"output":[198],"dimensions.":[199],"Spanning":[200],"classification,":[201],"regression":[202],"generative":[204],"modeling,":[205],"extensive":[206],"experimental":[207],"results":[208],"validate":[209],"substantially":[211],"improved":[212],"performance":[213],"MetaV":[215,227,242],"over":[216,269],"state-of-the-art":[218],"demonstrate":[222],"enhanced":[224],"generality":[225],"providing":[229],"fingerprinting.":[231],"example,":[233],"ResNet-18":[236],"trained":[237],"skin":[239],"cancer":[240],"diagnosis,":[241],"achieves":[243],"simultaneously":[244],"100%":[245,249],"true":[246,250],"positives":[247],"negatives":[251],"diverse":[254],"test":[255],"set":[256],"70":[258],"models,":[260],"achieving":[261],"about":[263],"220%":[264],"relative":[265],"improvement":[266],"ARUC":[268],"optimal":[271],"baseline.":[272]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":8},{"year":2024,"cited_by_count":7},{"year":2023,"cited_by_count":3}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2022-08-13T00:00:00"}
