{"id":"https://openalex.org/W2976595746","doi":"https://doi.org/10.1145/3351917.3351987","title":"Unsupervised Adversarial Perturbation Eliminating via Disentangled Representations","display_name":"Unsupervised Adversarial Perturbation Eliminating via Disentangled Representations","publication_year":2019,"publication_date":"2019-07-19","ids":{"openalex":"https://openalex.org/W2976595746","doi":"https://doi.org/10.1145/3351917.3351987","mag":"2976595746"},"language":"en","primary_location":{"id":"doi:10.1145/3351917.3351987","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3351917.3351987","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2019 4th International Conference on Automation, Control and Robotics Engineering","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/A5091258921","display_name":"Lingyun Jiang","orcid":"https://orcid.org/0000-0001-5967-3021"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Lingyun Jiang","raw_affiliation_strings":["National Digital Switching System Engineering and Technological Research Center, Zhengzhou China"],"affiliations":[{"raw_affiliation_string":"National Digital Switching System Engineering and Technological Research Center, Zhengzhou China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032832863","display_name":"Kai Qiao","orcid":"https://orcid.org/0000-0001-7057-9562"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kai Qiao","raw_affiliation_strings":["National Digital Switching System Engineering and Technological Research Center, Zhengzhou China"],"affiliations":[{"raw_affiliation_string":"National Digital Switching System Engineering and Technological Research Center, Zhengzhou China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061617562","display_name":"Ruoxi Qin","orcid":"https://orcid.org/0000-0003-0836-8179"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ruoxi Qin","raw_affiliation_strings":["National Digital Switching System Engineering and Technological Research Center, Zhengzhou China"],"affiliations":[{"raw_affiliation_string":"National Digital Switching System Engineering and Technological Research Center, Zhengzhou China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100326436","display_name":"Jian Chen","orcid":"https://orcid.org/0000-0002-1599-0831"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jian Chen","raw_affiliation_strings":["National Digital Switching System Engineering and Technological Research Center, Zhengzhou China"],"affiliations":[{"raw_affiliation_string":"National Digital Switching System Engineering and Technological Research Center, Zhengzhou China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040087975","display_name":"Haibing Bu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Haibing Bu","raw_affiliation_strings":["National Digital Switching System Engineering and Technological Research Center, Zhengzhou China"],"affiliations":[{"raw_affiliation_string":"National Digital Switching System Engineering and Technological Research Center, Zhengzhou China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5112729746","display_name":"Bin Yan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bin Yan","raw_affiliation_strings":["National Digital Switching System Engineering and Technological Research Center, Zhengzhou China"],"affiliations":[{"raw_affiliation_string":"National Digital Switching System Engineering and Technological Research Center, Zhengzhou China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5091258921"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.14,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.57233409,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9574999809265137,"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":0.9362999796867371,"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":0.9572503566741943},{"id":"https://openalex.org/keywords/mnist-database","display_name":"MNIST database","score":0.8913827538490295},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6731834411621094},{"id":"https://openalex.org/keywords/perturbation","display_name":"Perturbation (astronomy)","score":0.6529501676559448},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5534718036651611},{"id":"https://openalex.org/keywords/deep-neural-networks","display_name":"Deep neural networks","score":0.5174482464790344},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.48290514945983887},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4099523425102234},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.40332815051078796},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.33200979232788086}],"concepts":[{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.9572503566741943},{"id":"https://openalex.org/C190502265","wikidata":"https://www.wikidata.org/wiki/Q17069496","display_name":"MNIST database","level":3,"score":0.8913827538490295},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6731834411621094},{"id":"https://openalex.org/C177918212","wikidata":"https://www.wikidata.org/wiki/Q803623","display_name":"Perturbation (astronomy)","level":2,"score":0.6529501676559448},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5534718036651611},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.5174482464790344},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.48290514945983887},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4099523425102234},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.40332815051078796},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.33200979232788086},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3351917.3351987","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3351917.3351987","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2019 4th International Conference on Automation, Control and Robotics Engineering","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.6499999761581421}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W1686810756","https://openalex.org/W2112796928","https://openalex.org/W2160815625","https://openalex.org/W2194775991","https://openalex.org/W2460937040","https://openalex.org/W2885192629","https://openalex.org/W2962793481","https://openalex.org/W2963667985","https://openalex.org/W3159890710","https://openalex.org/W6600208142","https://openalex.org/W6603639717","https://openalex.org/W6610671653"],"related_works":["https://openalex.org/W2950183588","https://openalex.org/W3080754722","https://openalex.org/W4383221314","https://openalex.org/W3093978547","https://openalex.org/W2953536436","https://openalex.org/W3203790781","https://openalex.org/W4313346231","https://openalex.org/W2738001131","https://openalex.org/W4285785480","https://openalex.org/W2997056298"],"abstract_inverted_index":{"Although":[0],"deep":[1],"neural":[2],"networks":[3],"(DNNs)":[4],"could":[5],"achieve":[6,66],"state-of-the-art":[7],"performance":[8],"while":[9],"recognizing":[10],"images,":[11],"they":[12],"often":[13],"vulnerable":[14],"to":[15,21,31,44,87,116],"adversarial":[16,41,59,67,78,111,129,153],"examples":[17,42,79],"where":[18],"input":[19],"intended":[20],"be":[22],"added":[23],"the":[24,45,72,89,149],"small":[25],"magnitude":[26],"perturbations":[27],"may":[28],"mislead":[29],"them":[30],"incorrect":[32],"results.":[33],"It":[34],"is":[35,147],"worth":[36],"researching":[37],"on":[38,62,100,113,139],"defending":[39],"against":[40],"due":[43],"potential":[46],"security":[47],"threats.":[48],"In":[49],"this":[50],"paper,":[51],"we":[52,69,93],"propose":[53,70],"an":[54,110],"unsupervised":[55],"method":[56,126],"for":[57],"eliminating":[58],"perturbation":[60,75,84,105,130],"based":[61,99],"disentangled":[63,101],"representations.":[64],"To":[65],"defense,":[68],"extracting":[71],"content":[73,81],"and":[74,83,103,144],"features":[76],"of":[77,151],"by":[80],"encoders":[82],"encoders.":[85],"Meanwhile,":[86],"handle":[88],"unpaired":[90],"training":[91,133],"data,":[92],"introduce":[94],"a":[95,104],"cross-cycle":[96],"consistency":[97],"loss":[98,112],"representations":[102],"branch.":[106],"We":[107,135],"also":[108],"add":[109],"recovered":[114],"images":[115],"make":[117],"DNNs":[118],"predict":[119],"right.":[120],"Qualitative":[121],"results":[122],"show":[123],"that":[124],"our":[125],"can":[127],"eliminate":[128],"without":[131],"paired":[132],"data.":[134],"perform":[136],"extensive":[137],"experiments":[138],"two":[140],"public":[141],"datasets":[142],"MNIST":[143],"CIFAR10,":[145],"which":[146],"shown":[148],"efficiency":[150],"resisting":[152],"examples.":[154]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2020,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}