{"id":"https://openalex.org/W3083459508","doi":null,"title":"Adversarial Image Generation and Training for Deep Neural Networks","display_name":"Adversarial Image Generation and Training for Deep Neural Networks","publication_year":2020,"publication_date":"2020-06-05","ids":{"openalex":"https://openalex.org/W3083459508","mag":"3083459508"},"language":"en","primary_location":{"id":"mag:3083459508","doi":null,"is_oa":true,"landing_page_url":"http://export.arxiv.org/pdf/2006.03243","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"arXiv (Cornell University)","raw_type":null},"volume":null,"type":"preprint","is_traditional":true,"indexed_in":[],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"http://export.arxiv.org/pdf/2006.03243","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5058529379","display_name":"Hai Shu","orcid":"https://orcid.org/0000-0002-6968-4063","observed_orcids":["https://orcid.org/0000-0002-6968-4063"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hai Shu","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0002-6968-4063","affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078928747","display_name":"Ronghua Shi","orcid":"https://orcid.org/0000-0002-3464-132X","observed_orcids":["https://orcid.org/0000-0002-3464-132X"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ronghua Shi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5077961759","display_name":"Hongtu Zhu B","orcid":"https://orcid.org/0000-0002-6781-2690","observed_orcids":["https://orcid.org/0000-0002-6781-2690"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hongtu Zhu","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0002-6781-2690","affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5100715927","display_name":"Ziqi Chen","orcid":"https://orcid.org/0009-0005-8730-0659","observed_orcids":["https://orcid.org/0009-0005-8730-0659"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ziqi Chen","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0009-0005-8730-0659","affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"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":null,"last_page":null},"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/T10036","display_name":"Advanced Neural Network Applications","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"}}],"keywords":[{"id":"https://openalex.org/keywords/adversarial-examples","display_name":"adversarial examples","score":0.800000011920929},{"id":"https://openalex.org/keywords/adversarial-training","display_name":"adversarial training","score":0.925000011920929},{"id":"https://openalex.org/keywords/adversarial-attacks","display_name":"adversarial attacks","score":0.6990000009536743},{"id":"https://openalex.org/keywords/deep-neural-network-robustness","display_name":"deep neural network robustness","score":0.7820000052452087},{"id":"https://openalex.org/keywords/particle-swarm-optimization","display_name":"particle swarm optimization","score":0.9980000257492065},{"id":"https://openalex.org/keywords/targeted-attacks","display_name":"targeted attacks","score":0.8180000185966492},{"id":"https://openalex.org/keywords/adversarial-defense","display_name":"adversarial defense","score":0.6850000023841858}],"concepts":[{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.9343178868293762},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.6872996687889099},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.6582460999488831},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6420823335647583},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6414848566055298},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.5468496680259705},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.48797696828842163},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4813431203365326},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.4513281583786011},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.4504115581512451},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4489268660545349},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3705078363418579},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.19945856928825378},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","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},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"mag:3083459508","doi":null,"is_oa":true,"landing_page_url":"http://export.arxiv.org/pdf/2006.03243","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"arXiv (Cornell University)","raw_type":null}],"best_oa_location":{"id":"mag:3083459508","doi":null,"is_oa":true,"landing_page_url":"http://export.arxiv.org/pdf/2006.03243","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"arXiv (Cornell University)","raw_type":null},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":33,"referenced_works":["https://openalex.org/W1859314164","https://openalex.org/W1932198206","https://openalex.org/W1994445384","https://openalex.org/W2112126852","https://openalex.org/W2118023920","https://openalex.org/W2125237257","https://openalex.org/W2140609507","https://openalex.org/W2145113795","https://openalex.org/W2163605009","https://openalex.org/W2180612164","https://openalex.org/W2194775991","https://openalex.org/W2243397390","https://openalex.org/W2342840547","https://openalex.org/W2460937040","https://openalex.org/W2516574342","https://openalex.org/W2543580944","https://openalex.org/W2543927648","https://openalex.org/W2618043096","https://openalex.org/W2765424254","https://openalex.org/W2786622092","https://openalex.org/W2900298334","https://openalex.org/W2905409531","https://openalex.org/W2908286818","https://openalex.org/W2963207607","https://openalex.org/W2963446712","https://openalex.org/W2964153729","https://openalex.org/W2964253222","https://openalex.org/W2973849263","https://openalex.org/W2980361376","https://openalex.org/W2987644081","https://openalex.org/W2995755899","https://openalex.org/W2997532515","https://openalex.org/W3102068365"],"related_works":["https://openalex.org/W3033956253","https://openalex.org/W4287762840","https://openalex.org/W2963566318","https://openalex.org/W4403183301","https://openalex.org/W3016549807","https://openalex.org/W2793518327","https://openalex.org/W2980749867","https://openalex.org/W2979630692","https://openalex.org/W3005093931","https://openalex.org/W3066878117"],"abstract_inverted_index":{"Deep":[0],"neural":[1],"networks":[2],"(DNNs)":[3],"have":[4],"achieved":[5],"great":[6],"success":[7],"in":[8,137,149,166],"image":[9,32,72],"classification,":[10],"but":[11],"they":[12],"may":[13],"be":[14,135],"very":[15],"vulnerable":[16,118,150],"to":[17,23,37,51,66,116],"adversarial":[18,27,31,71,85,90,124,130,141,164],"attacks":[19,91],"with":[20,139],"small":[21],"perturbations":[22],"images.":[24],"Moreover,":[25],"the":[26,39,62,95,100,104,140],"training":[28,75,138],"based":[29,56],"on":[30,57],"samples":[33],"has":[34],"been":[35],"shown":[36],"improve":[38,67],"robustness":[40],"and":[41,61,74,103,108,114,120],"generalization":[42],"of":[43,47,70,84,94,97],"DNNs.":[44,77],"The":[45,78,126],"aim":[46],"this":[48],"paper":[49],"is":[50,81,111,128],"develop":[52],"a":[53,144],"novel":[54],"framework":[55],"information-geometry":[58],"sensitivity":[59],"analysis":[60],"particle":[63],"swarm":[64],"optimization":[65],"two":[68],"aspects":[69],"generation":[73,83],"for":[76,157],"first":[79],"one":[80],"customized":[82],"examples.":[86],"It":[87],"can":[88,134],"design":[89],"from":[92],"options":[93],"number":[96],"perturbed":[98],"pixels,":[99],"misclassification":[101],"probability,":[102],"targeted":[105,129,158],"incorrect":[106],"class,":[107],"hence":[109],"it":[110],"more":[112],"flexible":[113],"effective":[115,148],"locate":[117],"pixels":[119],"also":[121],"enjoys":[122],"certain":[123],"universality.":[125],"other":[127],"training.":[131],"DNN":[132],"models":[133],"improved":[136],"information":[142],"using":[143],"manifold-based":[145],"influence":[146],"measure":[147],"image/pixel":[151],"detection":[152],"as":[153,155],"well":[154],"allowing":[156],"attacks,":[159],"thereby":[160],"exhibiting":[161],"an":[162],"enhanced":[163],"defense":[165],"testing.":[167]},"counts_by_year":[{"year":2022,"cited_by_count":2}],"updated_date":"2026-10-17T09:40:24.721904","created_date":"2020-09-11T00:00:00"}
