{"id":"https://openalex.org/W4416251610","doi":"https://doi.org/10.1109/ijcnn64981.2025.11227995","title":"CopyQNN: Quantum Neural Network Extraction Attack under Varying Quantum Noise","display_name":"CopyQNN: Quantum Neural Network Extraction Attack under Varying Quantum Noise","publication_year":2025,"publication_date":"2025-06-30","ids":{"openalex":"https://openalex.org/W4416251610","doi":"https://doi.org/10.1109/ijcnn64981.2025.11227995"},"language":null,"primary_location":{"id":"doi:10.1109/ijcnn64981.2025.11227995","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn64981.2025.11227995","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 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/A5035286064","display_name":"Zhenxiao Fu","orcid":"https://orcid.org/0000-0001-9621-5572"},"institutions":[{"id":"https://openalex.org/I4210119109","display_name":"Indiana University Bloomington","ror":"https://ror.org/02k40bc56","country_code":"US","type":"education","lineage":["https://openalex.org/I4210119109","https://openalex.org/I592451"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zhenxiao Fu","raw_affiliation_strings":["Indiana University Bloomington"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Indiana University Bloomington","institution_ids":["https://openalex.org/I4210119109"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069991107","display_name":"Leyi Zhao","orcid":"https://orcid.org/0000-0002-3300-4847"},"institutions":[{"id":"https://openalex.org/I4210119109","display_name":"Indiana University Bloomington","ror":"https://ror.org/02k40bc56","country_code":"US","type":"education","lineage":["https://openalex.org/I4210119109","https://openalex.org/I592451"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Leyi Zhao","raw_affiliation_strings":["Indiana University Bloomington"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Indiana University Bloomington","institution_ids":["https://openalex.org/I4210119109"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101722405","display_name":"Xuhong Zhang","orcid":"https://orcid.org/0000-0002-1458-1825"},"institutions":[{"id":"https://openalex.org/I4210119109","display_name":"Indiana University Bloomington","ror":"https://ror.org/02k40bc56","country_code":"US","type":"education","lineage":["https://openalex.org/I4210119109","https://openalex.org/I592451"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xuhong Zhang","raw_affiliation_strings":["Indiana University Bloomington"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Indiana University Bloomington","institution_ids":["https://openalex.org/I4210119109"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052076681","display_name":"Yilun Xu","orcid":"https://orcid.org/0000-0002-0204-2103"},"institutions":[{"id":"https://openalex.org/I148283060","display_name":"Lawrence Berkeley National Laboratory","ror":"https://ror.org/02jbv0t02","country_code":"US","type":"facility","lineage":["https://openalex.org/I1330989302","https://openalex.org/I148283060","https://openalex.org/I39565521"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yilun Xu","raw_affiliation_strings":["Lawrence Berkeley National Laboratory"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Lawrence Berkeley National Laboratory","institution_ids":["https://openalex.org/I148283060"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100726056","display_name":"Gang Huang","orcid":"https://orcid.org/0000-0002-5786-7110"},"institutions":[{"id":"https://openalex.org/I148283060","display_name":"Lawrence Berkeley National Laboratory","ror":"https://ror.org/02jbv0t02","country_code":"US","type":"facility","lineage":["https://openalex.org/I1330989302","https://openalex.org/I148283060","https://openalex.org/I39565521"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Gang Huang","raw_affiliation_strings":["Lawrence Berkeley National Laboratory"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Lawrence Berkeley National Laboratory","institution_ids":["https://openalex.org/I148283060"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100322098","display_name":"Fan Chen","orcid":"https://orcid.org/0000-0003-0043-5111"},"institutions":[{"id":"https://openalex.org/I4210119109","display_name":"Indiana University Bloomington","ror":"https://ror.org/02k40bc56","country_code":"US","type":"education","lineage":["https://openalex.org/I4210119109","https://openalex.org/I592451"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Fan Chen","raw_affiliation_strings":["Indiana University Bloomington"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Indiana University Bloomington","institution_ids":["https://openalex.org/I4210119109"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10682","display_name":"Quantum Computing Algorithms and Architecture","score":0.4616999924182892,"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/T10682","display_name":"Quantum Computing Algorithms and Architecture","score":0.4616999924182892,"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/T10020","display_name":"Quantum Information and Cryptography","score":0.2531000077724457,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.07999999821186066,"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/noise","display_name":"Noise (video)","score":0.6643999814987183},{"id":"https://openalex.org/keywords/quantum","display_name":"Quantum","score":0.5981000065803528},{"id":"https://openalex.org/keywords/limiting","display_name":"Limiting","score":0.5838000178337097},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5595999956130981},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.517799973487854},{"id":"https://openalex.org/keywords/property","display_name":"Property (philosophy)","score":0.49619999527931213},{"id":"https://openalex.org/keywords/quantum-computer","display_name":"Quantum computer","score":0.4803999960422516},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.37720000743865967},{"id":"https://openalex.org/keywords/quantum-noise","display_name":"Quantum noise","score":0.35659998655319214}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.746999979019165},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.6643999814987183},{"id":"https://openalex.org/C84114770","wikidata":"https://www.wikidata.org/wiki/Q46344","display_name":"Quantum","level":2,"score":0.5981000065803528},{"id":"https://openalex.org/C188198153","wikidata":"https://www.wikidata.org/wiki/Q1613840","display_name":"Limiting","level":2,"score":0.5838000178337097},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5595999956130981},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.517799973487854},{"id":"https://openalex.org/C189950617","wikidata":"https://www.wikidata.org/wiki/Q937228","display_name":"Property (philosophy)","level":2,"score":0.49619999527931213},{"id":"https://openalex.org/C58053490","wikidata":"https://www.wikidata.org/wiki/Q176555","display_name":"Quantum computer","level":3,"score":0.4803999960422516},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4375999867916107},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.4034000039100647},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.37720000743865967},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.36730000376701355},{"id":"https://openalex.org/C111996192","wikidata":"https://www.wikidata.org/wiki/Q7269075","display_name":"Quantum noise","level":3,"score":0.35659998655319214},{"id":"https://openalex.org/C137019171","wikidata":"https://www.wikidata.org/wiki/Q2623817","display_name":"Quantum algorithm","level":3,"score":0.3547999858856201},{"id":"https://openalex.org/C2781170535","wikidata":"https://www.wikidata.org/wiki/Q30587856","display_name":"Noisy data","level":2,"score":0.34630000591278076},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.34040001034736633},{"id":"https://openalex.org/C2781162219","wikidata":"https://www.wikidata.org/wiki/Q26250693","display_name":"Replicate","level":2,"score":0.3278000056743622},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3237999975681305},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.2994999885559082},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.29910001158714294},{"id":"https://openalex.org/C186468114","wikidata":"https://www.wikidata.org/wiki/Q836478","display_name":"Quantum network","level":4,"score":0.2944999933242798},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2930000126361847},{"id":"https://openalex.org/C29265498","wikidata":"https://www.wikidata.org/wiki/Q7047719","display_name":"Noise measurement","level":3,"score":0.27799999713897705},{"id":"https://openalex.org/C2779014939","wikidata":"https://www.wikidata.org/wiki/Q6510239","display_name":"Learning with errors","level":3,"score":0.2581000030040741},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.25690001249313354},{"id":"https://openalex.org/C4725764","wikidata":"https://www.wikidata.org/wiki/Q844704","display_name":"Extraction (chemistry)","level":2,"score":0.25440001487731934},{"id":"https://openalex.org/C18762648","wikidata":"https://www.wikidata.org/wiki/Q42213","display_name":"Work (physics)","level":2,"score":0.25440001487731934},{"id":"https://openalex.org/C2776175482","wikidata":"https://www.wikidata.org/wiki/Q1195816","display_name":"Transfer (computing)","level":2,"score":0.2531999945640564}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn64981.2025.11227995","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn64981.2025.11227995","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 International Joint Conference on Neural Networks (IJCNN)","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":19,"referenced_works":["https://openalex.org/W1587454308","https://openalex.org/W1988147940","https://openalex.org/W2015811642","https://openalex.org/W2119046658","https://openalex.org/W2161381512","https://openalex.org/W2524016845","https://openalex.org/W2761090343","https://openalex.org/W2808195004","https://openalex.org/W2945680873","https://openalex.org/W2980456669","https://openalex.org/W3007318395","https://openalex.org/W3035524453","https://openalex.org/W3141189820","https://openalex.org/W4213212652","https://openalex.org/W4287947470","https://openalex.org/W4307823382","https://openalex.org/W4372342398","https://openalex.org/W4402351418","https://openalex.org/W4410770377"],"related_works":[],"abstract_inverted_index":{"Quantum":[0],"Neural":[1],"Networks":[2],"(QNNs)":[3],"have":[4,64],"shown":[5],"significant":[6],"value":[7],"across":[8,166],"domains,":[9],"with":[10,178],"well-trained":[11],"QNNs":[12,53,131],"representing":[13],"critical":[14],"intellectual":[15],"property":[16],"often":[17],"deployed":[18],"via":[19],"cloud-based":[20,59],"QNN-as-a-Service":[21],"(QNNaaS)":[22],"platforms.":[23],"Recent":[24],"work":[25],"has":[26],"examined":[27],"QNN":[28,156],"model":[29],"extraction":[30,157],"attacks":[31,39],"using":[32,132],"classical":[33],"and":[34,119],"emerging":[35],"quantum":[36,71,77,124],"strategies.":[37],"These":[38],"involve":[40],"adversaries":[41],"querying":[42],"QNNaaS":[43],"platforms":[44],"to":[45,102],"obtain":[46],"labeled":[47],"data":[48,99,105],"for":[49],"training":[50,128],"local":[51],"substitute":[52,130],"that":[54,147],"replicate":[55],"the":[56,67,92,115,123,171],"functionality":[57],"of":[58,69,117,129,138,151,164,173],"models.":[60],"However,":[61],"existing":[62],"approaches":[63],"largely":[65],"over-looked":[66],"impact":[68],"varying":[70],"noise":[72,109],"inherent":[73],"in":[74,83,183],"noisy":[75,104],"intermediate-scale":[76],"(NISQ)":[78],"computers,":[79],"limiting":[80],"their":[81],"effectiveness":[82],"real-world":[84],"settings.":[85],"To":[86],"address":[87],"this":[88],"limitation,":[89],"we":[90],"propose":[91],"CopyQNN":[93,152],"framework,":[94],"which":[95],"employs":[96],"a":[97,133,148,180],"three-step":[98],"cleaning":[100],"method":[101],"eliminate":[103],"based":[106],"on":[107,143],"its":[108],"sensitivity.":[110],"This":[111],"is":[112],"followed":[113],"by":[114,176],"integration":[116],"contrastive":[118],"transfer":[120],"learning":[121],"within":[122],"domain,":[125],"enabling":[126],"efficient":[127],"limited":[134],"but":[135],"cleaned":[136],"set":[137],"queried":[139],"data.":[140],"Experimental":[141],"results":[142],"NISQ":[144],"computers":[145],"demonstrate":[146],"practical":[149],"implementation":[150],"significantly":[153],"outperforms":[154],"state-of-the-art":[155],"attacks,":[158],"achieving":[159],"an":[160],"average":[161],"performance":[162],"improvement":[163],"8.73%":[165],"all":[167],"tasks":[168],"while":[169],"reducing":[170],"number":[172],"required":[174],"queries":[175],"90\u00d7,":[177],"only":[179],"modest":[181],"increase":[182],"hardware":[184],"overhead.":[185]},"counts_by_year":[{"year":2026,"cited_by_count":2}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-11-14T00:00:00"}