{"id":"https://openalex.org/W3015401978","doi":"https://doi.org/10.1007/978-3-030-53288-8_2","title":"Verification of Deep Convolutional Neural Networks Using ImageStars","display_name":"Verification of Deep Convolutional Neural Networks Using ImageStars","publication_year":2020,"publication_date":"2020-01-01","ids":{"openalex":"https://openalex.org/W3015401978","doi":"https://doi.org/10.1007/978-3-030-53288-8_2","mag":"3015401978"},"language":"en","primary_location":{"id":"doi:10.1007/978-3-030-53288-8_2","is_oa":true,"landing_page_url":"https://doi.org/10.1007/978-3-030-53288-8_2","pdf_url":"https://link.springer.com/content/pdf/10.1007%2F978-3-030-53288-8_2.pdf","source":{"id":"https://openalex.org/S106296714","display_name":"Lecture notes in computer science","issn_l":"0302-9743","issn":["0302-9743","1611-3349"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"book series"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Lecture Notes in Computer Science","raw_type":"book-chapter"},"type":"preprint","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://link.springer.com/content/pdf/10.1007%2F978-3-030-53288-8_2.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5023289374","display_name":"Hoang-Dung Tran","orcid":"https://orcid.org/0000-0001-6946-9526"},"institutions":[{"id":"https://openalex.org/I114395901","display_name":"University of Nebraska\u2013Lincoln","ror":"https://ror.org/043mer456","country_code":"US","type":"education","lineage":["https://openalex.org/I114395901"]},{"id":"https://openalex.org/I200719446","display_name":"Vanderbilt University","ror":"https://ror.org/02vm5rt34","country_code":"US","type":"education","lineage":["https://openalex.org/I200719446"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Hoang-Dung Tran","raw_affiliation_strings":["University of Nebraska, Lincoln, USA","Vanderbilt University, Nashville, USA","Univ. of Nebraska Lincoln (USA)"],"affiliations":[{"raw_affiliation_string":"University of Nebraska, Lincoln, USA","institution_ids":["https://openalex.org/I114395901"]},{"raw_affiliation_string":"Vanderbilt University, Nashville, USA","institution_ids":["https://openalex.org/I200719446"]},{"raw_affiliation_string":"Univ. of Nebraska Lincoln (USA)","institution_ids":["https://openalex.org/I114395901"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033330108","display_name":"Stanley Bak","orcid":"https://orcid.org/0000-0003-4947-9553"},"institutions":[{"id":"https://openalex.org/I59553526","display_name":"Stony Brook University","ror":"https://ror.org/05qghxh33","country_code":"US","type":"education","lineage":["https://openalex.org/I59553526"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Stanley Bak","raw_affiliation_strings":["Stony Brook University, Stony Brook, USA"],"affiliations":[{"raw_affiliation_string":"Stony Brook University, Stony Brook, USA","institution_ids":["https://openalex.org/I59553526"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090573416","display_name":"Weiming Xiang","orcid":"https://orcid.org/0000-0001-9065-8428"},"institutions":[{"id":"https://openalex.org/I25041050","display_name":"Augusta University","ror":"https://ror.org/012mef835","country_code":"US","type":"education","lineage":["https://openalex.org/I25041050"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Weiming Xiang","raw_affiliation_strings":["Augusta University, Augusta, USA"],"affiliations":[{"raw_affiliation_string":"Augusta University, Augusta, USA","institution_ids":["https://openalex.org/I25041050"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5067901159","display_name":"Taylor T. Johnson","orcid":"https://orcid.org/0000-0001-8021-9923"},"institutions":[{"id":"https://openalex.org/I200719446","display_name":"Vanderbilt University","ror":"https://ror.org/02vm5rt34","country_code":"US","type":"education","lineage":["https://openalex.org/I200719446"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Taylor T. Johnson","raw_affiliation_strings":["Vanderbilt University, Nashville, USA","Vanderbilt University, Nashville, USA;"],"affiliations":[{"raw_affiliation_string":"Vanderbilt University, Nashville, USA","institution_ids":["https://openalex.org/I200719446"]},{"raw_affiliation_string":"Vanderbilt University, Nashville, USA;","institution_ids":["https://openalex.org/I200719446"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5023289374"],"corresponding_institution_ids":["https://openalex.org/I114395901","https://openalex.org/I200719446"],"apc_list":{"value":5000,"currency":"EUR","value_usd":5392},"apc_paid":{"value":5000,"currency":"EUR","value_usd":5392},"fwci":1.925,"has_fulltext":true,"cited_by_count":8,"citation_normalized_percentile":{"value":0.88181297,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"18","last_page":"42"},"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/T14117","display_name":"Integrated Circuits and Semiconductor Failure Analysis","score":0.9672999978065491,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12122","display_name":"Physical Unclonable Functions (PUFs) and Hardware Security","score":0.9584000110626221,"subfield":{"id":"https://openalex.org/subfields/1708","display_name":"Hardware and Architecture"},"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":0.7883337736129761},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7842517495155334},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6914485096931458},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6583889722824097},{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.6383160352706909},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.5480220913887024},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5271185040473938},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.48190099000930786},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4748944342136383},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4653656482696533},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.4534703195095062},{"id":"https://openalex.org/keywords/bounded-function","display_name":"Bounded function","score":0.43259352445602417},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.42642655968666077},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.10258850455284119}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7883337736129761},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7842517495155334},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6914485096931458},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6583889722824097},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.6383160352706909},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.5480220913887024},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5271185040473938},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.48190099000930786},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4748944342136383},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4653656482696533},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.4534703195095062},{"id":"https://openalex.org/C34388435","wikidata":"https://www.wikidata.org/wiki/Q2267362","display_name":"Bounded function","level":2,"score":0.43259352445602417},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.42642655968666077},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10258850455284119},{"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/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"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/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"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/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":5,"locations":[{"id":"doi:10.1007/978-3-030-53288-8_2","is_oa":true,"landing_page_url":"https://doi.org/10.1007/978-3-030-53288-8_2","pdf_url":"https://link.springer.com/content/pdf/10.1007%2F978-3-030-53288-8_2.pdf","source":{"id":"https://openalex.org/S106296714","display_name":"Lecture notes in computer science","issn_l":"0302-9743","issn":["0302-9743","1611-3349"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"book series"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Lecture Notes in Computer Science","raw_type":"book-chapter"},{"id":"pmh:oai:arXiv.org:2004.05511","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2004.05511","pdf_url":"https://arxiv.org/pdf/2004.05511","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"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":"","raw_type":"text"},{"id":"pmh:oai:pubmedcentral.nih.gov:7363231","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/7363231","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Computer Aided Verification","raw_type":"Text"},{"id":"doi:10.48550/arxiv.2004.05511","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2004.05511","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"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":"public-domain","license_id":"https://openalex.org/licenses/public-domain","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"},{"id":"mag:3015401978","is_oa":false,"landing_page_url":null,"pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":null}],"best_oa_location":{"id":"doi:10.1007/978-3-030-53288-8_2","is_oa":true,"landing_page_url":"https://doi.org/10.1007/978-3-030-53288-8_2","pdf_url":"https://link.springer.com/content/pdf/10.1007%2F978-3-030-53288-8_2.pdf","source":{"id":"https://openalex.org/S106296714","display_name":"Lecture notes in computer science","issn_l":"0302-9743","issn":["0302-9743","1611-3349"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"book series"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Lecture Notes in Computer Science","raw_type":"book-chapter"},"sustainable_development_goals":[{"score":0.4699999988079071,"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3015401978.pdf","grobid_xml":"https://content.openalex.org/works/W3015401978.grobid-xml"},"referenced_works_count":60,"referenced_works":["https://openalex.org/W1686810756","https://openalex.org/W1963882359","https://openalex.org/W2112796928","https://openalex.org/W2144354855","https://openalex.org/W2163605009","https://openalex.org/W2243397390","https://openalex.org/W2594877703","https://openalex.org/W2721006554","https://openalex.org/W2734705105","https://openalex.org/W2735607295","https://openalex.org/W2760733685","https://openalex.org/W2766462876","https://openalex.org/W2777417342","https://openalex.org/W2789017165","https://openalex.org/W2794609696","https://openalex.org/W2796083356","https://openalex.org/W2798164686","https://openalex.org/W2798356176","https://openalex.org/W2799107510","https://openalex.org/W2869036160","https://openalex.org/W2890472662","https://openalex.org/W2899116309","https://openalex.org/W2900153411","https://openalex.org/W2902630996","https://openalex.org/W2905431656","https://openalex.org/W2936674544","https://openalex.org/W2938701611","https://openalex.org/W2955364893","https://openalex.org/W2957311447","https://openalex.org/W2962692913","https://openalex.org/W2963054787","https://openalex.org/W2963207607","https://openalex.org/W2963334980","https://openalex.org/W2963424284","https://openalex.org/W2963540169","https://openalex.org/W2963565751","https://openalex.org/W2964079458","https://openalex.org/W2964130946","https://openalex.org/W2969980813","https://openalex.org/W2971839749","https://openalex.org/W2974147052","https://openalex.org/W2980176594","https://openalex.org/W2980176926","https://openalex.org/W2980264580","https://openalex.org/W2999818223","https://openalex.org/W3009821482","https://openalex.org/W3021958118","https://openalex.org/W3024917158","https://openalex.org/W3037629243","https://openalex.org/W3046272654","https://openalex.org/W3098919244","https://openalex.org/W6600109629","https://openalex.org/W6601013545","https://openalex.org/W6601379991","https://openalex.org/W6609410732","https://openalex.org/W6633963571","https://openalex.org/W6809662878","https://openalex.org/W6819283011","https://openalex.org/W6820154040","https://openalex.org/W6945320227"],"related_works":["https://openalex.org/W2799208032","https://openalex.org/W2793518327","https://openalex.org/W2924179447","https://openalex.org/W2968452475","https://openalex.org/W3081288214","https://openalex.org/W2901632455","https://openalex.org/W2243397390","https://openalex.org/W2123872146","https://openalex.org/W2754782327","https://openalex.org/W2903917280","https://openalex.org/W3108203649","https://openalex.org/W2905878277","https://openalex.org/W3213033076","https://openalex.org/W2573336281","https://openalex.org/W3207237444","https://openalex.org/W2963314614","https://openalex.org/W2995972302","https://openalex.org/W2891627818","https://openalex.org/W2911089685","https://openalex.org/W2982695658"],"abstract_inverted_index":{"Convolutional":[0],"Neural":[1],"Networks":[2],"(CNN)":[3],"have":[4,81,115],"redefined":[5],"state-of-the-art":[6],"in":[7,43,46,84,160],"many":[8],"real-world":[9,107],"applications,":[10],"such":[11,109,186],"as":[12,110,187],"facial":[13],"recognition,":[14],"image":[15],"classification,":[16],"human":[17],"pose":[18],"estimation,":[19],"and":[20,112,136,165,201,206],"semantic":[21],"segmentation.":[22],"Despite":[23],"their":[24,36,44],"success,":[25],"CNNs":[26],"are":[27],"vulnerable":[28],"to":[29,35,40,68,175],"adversarial":[30,61,184],"attacks,":[31,62,185],"where":[32],"slight":[33],"changes":[34,42],"inputs":[37],"may":[38],"lead":[39],"sharp":[41],"output":[45],"even":[47],"well-trained":[48],"networks.":[49],"Set-based":[50],"analysis":[51,138,145],"methods":[52],"can":[53,64,92,166],"detect":[54],"or":[55],"prove":[56],"the":[57,70,87,130,168,188],"absence":[58],"of":[59,72,86,89,139,170,179],"bounded":[60],"which":[63,132],"then":[65],"be":[66,93],"used":[67],"evaluate":[69],"effectiveness":[71],"neural":[73],"network":[74],"training":[75],"methodology.":[76],"Unfortunately,":[77],"existing":[78,204],"verification":[79],"approaches":[80],"limited":[82],"scalability":[83],"terms":[85],"size":[88],"networks":[90,172],"that":[91,103,114,195],"analyzed.":[94],"In":[95],"this":[96],"paper,":[97],"we":[98],"describe":[99],"a":[100,125,161,176],"set-based":[101,144],"framework":[102],"successfully":[104],"deals":[105],"with":[106,152,173],"CNNs,":[108],"VGG16":[111],"VGG19,":[113],"high":[116],"accuracy":[117],"on":[118,124,149],"ImageNet.":[119],"Our":[120,156],"approach":[121,157,197],"is":[122,158,198],"based":[123],"new":[126],"set":[127,178],"representation":[128],"called":[129,163],"ImageStar,":[131],"enables":[133],"efficient":[134,143],"exact":[135],"over-approximative":[137],"CNNs.":[140],"ImageStars":[141],"perform":[142],"by":[146],"combining":[147],"operations":[148],"concrete":[150],"images":[151],"linear":[153],"programming":[154],"(LP).":[155],"implemented":[159],"tool":[162],"NNV,":[164],"verify":[167],"robustness":[169],"VGG":[171],"respect":[174],"small":[177],"input":[180],"states,":[181],"derived":[182],"from":[183],"DeepFool":[189],"attack.":[190],"The":[191],"experimental":[192],"results":[193],"show":[194],"our":[196],"less":[199],"conservative":[200],"faster":[202],"than":[203],"zonotope":[205],"polytope":[207],"methods.":[208]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":2}],"updated_date":"2026-04-21T08:09:41.155169","created_date":"2025-10-10T00:00:00"}