{"id":"https://openalex.org/W3100995366","doi":"https://doi.org/10.48550/arxiv.2009.02470","title":"Dual Manifold Adversarial Robustness: Defense against Lp and non-Lp Adversarial Attacks","display_name":"Dual Manifold Adversarial Robustness: Defense against Lp and non-Lp Adversarial Attacks","publication_year":2020,"publication_date":"2020-09-05","ids":{"openalex":"https://openalex.org/W3100995366","doi":"https://doi.org/10.48550/arxiv.2009.02470","mag":"3100995366"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2009.02470","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2009.02470","pdf_url":"https://arxiv.org/pdf/2009.02470","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"volume":null,"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2009.02470","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5102311216","display_name":"Wei-An Lin","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I66946132","display_name":"University of Maryland, College Park","ror":"https://ror.org/047s2c258","country_code":"US","type":"education","lineage":["https://openalex.org/I66946132"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Lin, Wei-An","raw_affiliation_strings":["University of Maryland , College Park","University of Maryland, College Park, College Park, United States"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Maryland , College Park","institution_ids":["https://openalex.org/I66946132"]},{"raw_affiliation_string":"University of Maryland, College Park, College Park, United States","institution_ids":["https://openalex.org/I66946132"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5041734550","display_name":"Chun Pong Lau","orcid":"https://orcid.org/0000-0003-3748-4160","observed_orcids":["https://orcid.org/0000-0003-3748-4160"]},"institutions":[{"id":"https://openalex.org/I66946132","display_name":"University of Maryland, College Park","ror":"https://ror.org/047s2c258","country_code":"US","type":"education","lineage":["https://openalex.org/I66946132"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Lau, Chun Pong","raw_affiliation_strings":["University of Maryland , College Park","University of Maryland, College Park, College Park, United States"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Maryland , College Park","institution_ids":["https://openalex.org/I66946132"]},{"raw_affiliation_string":"University of Maryland, College Park, College Park, United States","institution_ids":["https://openalex.org/I66946132"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001820023","display_name":"Alexander Levine","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I66946132","display_name":"University of Maryland, College Park","ror":"https://ror.org/047s2c258","country_code":"US","type":"education","lineage":["https://openalex.org/I66946132"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Levine, Alexander","raw_affiliation_strings":["University of Maryland , College Park","University of Maryland, College Park, College Park, United States"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Maryland , College Park","institution_ids":["https://openalex.org/I66946132"]},{"raw_affiliation_string":"University of Maryland, College Park, College Park, United States","institution_ids":["https://openalex.org/I66946132"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102762707","display_name":"Rama Chellappa","orcid":"https://orcid.org/0000-0002-7638-1650","observed_orcids":["https://orcid.org/0000-0002-7638-1650"]},"institutions":[{"id":"https://openalex.org/I66946132","display_name":"University of Maryland, College Park","ror":"https://ror.org/047s2c258","country_code":"US","type":"education","lineage":["https://openalex.org/I66946132"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Chellappa, Rama","raw_affiliation_strings":["University of Maryland , College Park","University of Maryland, College Park, College Park, United States"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Maryland , College Park","institution_ids":["https://openalex.org/I66946132"]},{"raw_affiliation_string":"University of Maryland, College Park, College Park, United States","institution_ids":["https://openalex.org/I66946132"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5025450606","display_name":"Soheil Feizi","orcid":"https://orcid.org/0000-0003-0944-8242","observed_orcids":["https://orcid.org/0000-0003-0944-8242","https://orcid.org/0000-0003-0493-4938"]},"institutions":[{"id":"https://openalex.org/I66946132","display_name":"University of Maryland, College Park","ror":"https://ror.org/047s2c258","country_code":"US","type":"education","lineage":["https://openalex.org/I66946132"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Feizi, Soheil","raw_affiliation_strings":["University of Maryland , College Park","University of Maryland, College Park, College Park, United States"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Maryland , College Park","institution_ids":["https://openalex.org/I66946132"]},{"raw_affiliation_string":"University of Maryland, College Park, College Park, United States","institution_ids":["https://openalex.org/I66946132"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I66946132"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":32,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"33","issue":null,"first_page":"3487","last_page":"3498"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":1.0,"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":1.0,"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":0.0,"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/T11424","display_name":"Security and Verification in Computing","score":0.0,"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/adversarial-robustness","display_name":"adversarial robustness","score":0.996999979019165},{"id":"https://openalex.org/keywords/adversarial-training","display_name":"adversarial training","score":0.8069999814033508},{"id":"https://openalex.org/keywords/image-manifolds","display_name":"image manifolds","score":0.597000002861023},{"id":"https://openalex.org/keywords/latent-space-perturbation","display_name":"latent space perturbation","score":0.7509999871253967}],"concepts":[{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.8306863307952881},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.7483583688735962},{"id":"https://openalex.org/C529865628","wikidata":"https://www.wikidata.org/wiki/Q1790740","display_name":"Manifold (fluid mechanics)","level":2,"score":0.7437363862991333},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6248950362205505},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.532626211643219},{"id":"https://openalex.org/C34388435","wikidata":"https://www.wikidata.org/wiki/Q2267362","display_name":"Bounded function","level":2,"score":0.5081839561462402},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.29925858974456787},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","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/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"pmh:oai:arXiv.org:2009.02470","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2009.02470","pdf_url":"https://arxiv.org/pdf/2009.02470","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2009.02470","doi":"https://doi.org/10.48550/arxiv.2009.02470","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2009.02470","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},{"id":"mag:3100995366","doi":null,"is_oa":false,"landing_page_url":"https://proceedings.neurips.cc/paper/2020/file/23937b42f9273974570fb5a56a6652ee-Paper.pdf","pdf_url":null,"source":{"id":"https://openalex.org/S4363606243","display_name":"neural information processing systems","issn_l":"1049-5258","issn":["1049-5258"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core","norway-2"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":"Neural Information Processing Systems","raw_type":null}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2009.02470","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2009.02470","pdf_url":"https://arxiv.org/pdf/2009.02470","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3100995366.pdf","grobid_xml":"https://content.openalex.org/works/W3100995366.grobid-xml"},"referenced_works_count":43,"referenced_works":["https://openalex.org/W1536680647","https://openalex.org/W1834627138","https://openalex.org/W2112796928","https://openalex.org/W2160815625","https://openalex.org/W2163605009","https://openalex.org/W2516574342","https://openalex.org/W2607219512","https://openalex.org/W2618043096","https://openalex.org/W2734358244","https://openalex.org/W2750384547","https://openalex.org/W2766462876","https://openalex.org/W2774644650","https://openalex.org/W2778624544","https://openalex.org/W2783692467","https://openalex.org/W2787496614","https://openalex.org/W2787708942","https://openalex.org/W2892354372","https://openalex.org/W2893749619","https://openalex.org/W2897355816","https://openalex.org/W2902031012","https://openalex.org/W2904367110","https://openalex.org/W2911634294","https://openalex.org/W2913266441","https://openalex.org/W2914897181","https://openalex.org/W2934375473","https://openalex.org/W2946376184","https://openalex.org/W2947028053","https://openalex.org/W2947590261","https://openalex.org/W2962785568","https://openalex.org/W2963207607","https://openalex.org/W2963557656","https://openalex.org/W2964153729","https://openalex.org/W2964238361","https://openalex.org/W2964253222","https://openalex.org/W2969454448","https://openalex.org/W2970115835","https://openalex.org/W2995056242","https://openalex.org/W2995327724","https://openalex.org/W2996564870","https://openalex.org/W2998293245","https://openalex.org/W3012226457","https://openalex.org/W3037906261","https://openalex.org/W4289147935"],"related_works":["https://openalex.org/W3130614919","https://openalex.org/W4281395817","https://openalex.org/W2902031012","https://openalex.org/W2884169041","https://openalex.org/W4394640801","https://openalex.org/W4403533843","https://openalex.org/W3150919918","https://openalex.org/W4405306719","https://openalex.org/W4383221525","https://openalex.org/W4409369554"],"abstract_inverted_index":{"Adversarial":[0,145],"training":[1,108,178],"is":[2,99],"a":[3],"popular":[4],"defense":[5,27,132],"strategy":[6],"against":[7,179,194,243],"attack":[8],"threat":[9],"models":[10,41,187,219,242],"with":[11],"bounded":[12],"Lp":[13,137,180],"norms.":[14],"However,":[15,124],"it":[16],"often":[17],"degrades":[18],"the":[19,26,36,49,59,67,83,87,95,110,131,161,175,217,229],"model":[20],"performance":[21,166],"on":[22,167,222],"normal":[23,168],"images":[24,114,199],"and":[25,45,119,154,170],"does":[28],"not":[29,58],"generalize":[30],"well":[31],"to":[32,121,174],"novel":[33,195,247],"attacks.":[34,123,139,181,249],"Given":[35],"success":[37],"of":[38,52,113,207,232,239,246],"deep":[39,240],"generative":[40],"such":[42],"as":[43],"GANs":[44],"VAEs":[46],"in":[47,109,151,159,236],"characterizing":[48],"underlying":[50,68,96],"manifold":[51,69,88,97,234],"images,":[53,169],"we":[54,74,103,184],"investigate":[55],"whether":[56],"or":[57,204],"aforementioned":[60],"problems":[61],"can":[62,133],"be":[63,134],"remedied":[64],"by":[65,81,90,136,189,200],"exploiting":[66],"information.":[70],"To":[71],"this":[72,93],"end,":[73],"construct":[75],"an":[76],"\"On-Manifold":[77],"ImageNet\"":[78],"(OM-ImageNet)":[79],"dataset":[80],"projecting":[82],"ImageNet":[84],"samples":[85],"onto":[86],"learned":[89],"StyleGSN.":[91],"For":[92],"dataset,":[94],"information":[98,235],"exact.":[100],"Using":[101],"OM-ImageNet,":[102],"first":[104],"show":[105],"that":[106,186],"adversarial":[107,138,149,177,248],"latent":[111,153],"space":[112],"improves":[115,165],"both":[116,152],"standard":[117,176],"accuracy":[118],"robustness":[120,173,193,238],"on-manifold":[122],"since":[125],"no":[126],"out-of-manifold":[127,223],"perturbations":[128,150],"are":[129,157,213,220],"realized,":[130],"broken":[135],"We":[140],"further":[141],"propose":[142],"Dual":[143],"Manifold":[144],"Training":[146],"(DMAT)":[147],"where":[148],"image":[155,208],"spaces":[156],"used":[158],"robustifying":[160],"model.":[162],"Our":[163],"DMAT":[164,190],"achieves":[171],"comparable":[172],"In":[182],"addition,":[183],"observe":[185],"defended":[188,218],"achieve":[191],"improved":[192],"attacks":[196],"which":[197],"manipulate":[198],"global":[201],"color":[202],"shifts":[203],"various":[205,244],"types":[206,245],"filtering.":[209],"Interestingly,":[210],"similar":[211],"improvements":[212],"also":[214],"achieved":[215],"when":[216],"tested":[221],"natural":[224],"images.":[225],"These":[226],"results":[227],"demonstrate":[228],"potential":[230],"benefits":[231],"using":[233],"enhancing":[237],"learning":[241]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":12},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":6},{"year":2021,"cited_by_count":6}],"updated_date":"2026-11-04T10:54:05.112534","created_date":"2020-11-23T00:00:00"}