{"id":"https://openalex.org/W4300960561","doi":"https://doi.org/10.1007/s44163-022-00035-3","title":"An improved real time detection of data poisoning attacks in deep learning vision systems","display_name":"An improved real time detection of data poisoning attacks in deep learning vision systems","publication_year":2022,"publication_date":"2022-10-03","ids":{"openalex":"https://openalex.org/W4300960561","doi":"https://doi.org/10.1007/s44163-022-00035-3"},"language":"en","primary_location":{"id":"doi:10.1007/s44163-022-00035-3","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s44163-022-00035-3","pdf_url":"https://link.springer.com/content/pdf/10.1007/s44163-022-00035-3.pdf","source":{"id":"https://openalex.org/S4210220416","display_name":"Discover Artificial Intelligence","issn_l":"2731-0809","issn":["2731-0809"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Discover Artificial Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://link.springer.com/content/pdf/10.1007/s44163-022-00035-3.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5081828365","display_name":"Vijay Raghavan","orcid":null},"institutions":[{"id":"https://openalex.org/I193531525","display_name":"George Washington University","ror":"https://ror.org/00y4zzh67","country_code":"US","type":"education","lineage":["https://openalex.org/I193531525"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Vijay Raghavan","raw_affiliation_strings":["Department of Engineering Management and Systems Engineering, The George Washington University, 2121 I St NW, Washington, DC 20052, USA","Department of Engineering Management and Systems Engineering, The George Washington University, 2121 I St NW, Washington, DC, 20052, USA"],"affiliations":[{"raw_affiliation_string":"Department of Engineering Management and Systems Engineering, The George Washington University, 2121 I St NW, Washington, DC 20052, USA","institution_ids":["https://openalex.org/I193531525"]},{"raw_affiliation_string":"Department of Engineering Management and Systems Engineering, The George Washington University, 2121 I St NW, Washington, DC, 20052, USA","institution_ids":["https://openalex.org/I193531525"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050432319","display_name":"Thomas A. Mazzuchi","orcid":"https://orcid.org/0000-0002-4584-4018"},"institutions":[{"id":"https://openalex.org/I193531525","display_name":"George Washington University","ror":"https://ror.org/00y4zzh67","country_code":"US","type":"education","lineage":["https://openalex.org/I193531525"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Thomas Mazzuchi","raw_affiliation_strings":["Department of Engineering Management and Systems Engineering, The George Washington University, 2121 I St NW, Washington, DC 20052, USA","Department of Engineering Management and Systems Engineering, The George Washington University, 2121 I St NW, Washington, DC, 20052, USA"],"affiliations":[{"raw_affiliation_string":"Department of Engineering Management and Systems Engineering, The George Washington University, 2121 I St NW, Washington, DC 20052, USA","institution_ids":["https://openalex.org/I193531525"]},{"raw_affiliation_string":"Department of Engineering Management and Systems Engineering, The George Washington University, 2121 I St NW, Washington, DC, 20052, USA","institution_ids":["https://openalex.org/I193531525"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5109336689","display_name":"Shahram Sarkani","orcid":null},"institutions":[{"id":"https://openalex.org/I193531525","display_name":"George Washington University","ror":"https://ror.org/00y4zzh67","country_code":"US","type":"education","lineage":["https://openalex.org/I193531525"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shahram Sarkani","raw_affiliation_strings":["Department of Engineering Management and Systems Engineering, The George Washington University, 2121 I St NW, Washington, DC 20052, USA","Department of Engineering Management and Systems Engineering, The George Washington University, 2121 I St NW, Washington, DC, 20052, USA"],"affiliations":[{"raw_affiliation_string":"Department of Engineering Management and Systems Engineering, The George Washington University, 2121 I St NW, Washington, DC 20052, USA","institution_ids":["https://openalex.org/I193531525"]},{"raw_affiliation_string":"Department of Engineering Management and Systems Engineering, The George Washington University, 2121 I St NW, Washington, DC, 20052, USA","institution_ids":["https://openalex.org/I193531525"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5081828365"],"corresponding_institution_ids":["https://openalex.org/I193531525"],"apc_list":{"value":990,"currency":"EUR","value_usd":1067},"apc_paid":{"value":990,"currency":"EUR","value_usd":1067},"fwci":1.6552,"has_fulltext":true,"cited_by_count":13,"citation_normalized_percentile":{"value":0.86428516,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"2","issue":"1","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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.996999979019165,"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/T11241","display_name":"Advanced Malware Detection Techniques","score":0.9922000169754028,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/deep-learning","display_name":"Deep learning","score":0.8451106548309326},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7106826305389404},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6704525947570801},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6601845622062683},{"id":"https://openalex.org/keywords/countermeasure","display_name":"Countermeasure","score":0.6233712434768677},{"id":"https://openalex.org/keywords/reliability","display_name":"Reliability (semiconductor)","score":0.5312165021896362},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.5141220688819885},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.48831579089164734},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4672638773918152},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.16141793131828308}],"concepts":[{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.8451106548309326},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7106826305389404},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6704525947570801},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6601845622062683},{"id":"https://openalex.org/C21593369","wikidata":"https://www.wikidata.org/wiki/Q1032176","display_name":"Countermeasure","level":2,"score":0.6233712434768677},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.5312165021896362},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.5141220688819885},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.48831579089164734},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4672638773918152},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.16141793131828308},{"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/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.0},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1007/s44163-022-00035-3","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s44163-022-00035-3","pdf_url":"https://link.springer.com/content/pdf/10.1007/s44163-022-00035-3.pdf","source":{"id":"https://openalex.org/S4210220416","display_name":"Discover Artificial Intelligence","issn_l":"2731-0809","issn":["2731-0809"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Discover Artificial Intelligence","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:471b8febf19f4e80961e3745b8ef1cb2","is_oa":true,"landing_page_url":"https://doaj.org/article/471b8febf19f4e80961e3745b8ef1cb2","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Discover Artificial Intelligence, Vol 2, Iss 1, Pp 1-17 (2022)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1007/s44163-022-00035-3","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s44163-022-00035-3","pdf_url":"https://link.springer.com/content/pdf/10.1007/s44163-022-00035-3.pdf","source":{"id":"https://openalex.org/S4210220416","display_name":"Discover Artificial Intelligence","issn_l":"2731-0809","issn":["2731-0809"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Discover Artificial Intelligence","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Life in Land","id":"https://metadata.un.org/sdg/15","score":0.5899999737739563}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4300960561.pdf","grobid_xml":"https://content.openalex.org/works/W4300960561.grobid-xml"},"referenced_works_count":35,"referenced_works":["https://openalex.org/W1583837637","https://openalex.org/W1676470423","https://openalex.org/W2071082401","https://openalex.org/W2124659975","https://openalex.org/W2493916176","https://openalex.org/W2605253252","https://openalex.org/W2618530766","https://openalex.org/W2761114781","https://openalex.org/W2797558164","https://openalex.org/W2900438754","https://openalex.org/W2911495555","https://openalex.org/W2919115771","https://openalex.org/W2949007385","https://openalex.org/W2951832089","https://openalex.org/W2962763344","https://openalex.org/W2962843773","https://openalex.org/W2966284335","https://openalex.org/W3005880794","https://openalex.org/W3008516500","https://openalex.org/W3011727199","https://openalex.org/W3013173293","https://openalex.org/W3016493309","https://openalex.org/W3021596612","https://openalex.org/W3034302825","https://openalex.org/W3037921969","https://openalex.org/W3049190448","https://openalex.org/W3104788453","https://openalex.org/W3112787034","https://openalex.org/W3162560068","https://openalex.org/W3195179567","https://openalex.org/W3213515577","https://openalex.org/W3216348338","https://openalex.org/W4229971152","https://openalex.org/W4243072198","https://openalex.org/W6686207219"],"related_works":["https://openalex.org/W2378749186","https://openalex.org/W2364088131","https://openalex.org/W4226493464","https://openalex.org/W4312417841","https://openalex.org/W3193565141","https://openalex.org/W3133861977","https://openalex.org/W2951211570","https://openalex.org/W3103566983","https://openalex.org/W3167935049","https://openalex.org/W3029198973"],"abstract_inverted_index":{"Abstract":[0],"The":[1,220],"practice":[2],"of":[3,65,105,147,157,173,217,233],"using":[4],"deep":[5,27,54,83,93,163,190],"learning":[6,28,84,164,191],"methods":[7,29],"in":[8,101,114,133,223],"safety":[9],"critical":[10],"vision":[11,23,56,165,192],"systems":[12,24,39,85,108,125,166],"such":[13],"as":[14],"autonomous":[15],"driving":[16],"has":[17],"come":[18,41],"a":[19,62,76,103,183,189,196,230],"long":[20],"way.":[21],"As":[22,45],"supported":[25],"by":[26,37,182,240],"become":[30],"ubiquitous,":[31],"the":[32,80,119,134,144,148,155,179,215,218,237,242],"possible":[33],"security":[34,120],"threats":[35,121,139],"faced":[36],"these":[38,53,124,131,138,171],"have":[40,96,109],"into":[42],"greater":[43],"focus.":[44],"it":[46],"is":[47],"with":[48,201],"any":[49],"artificial":[50],"intelligence":[51],"system,":[52],"neural":[55,94],"networks":[57,95],"are":[58,73,86,126,245],"first":[59],"trained":[60],"on":[61,188,229],"data":[63,89,111,158,185,244],"set":[64],"interest,":[66],"once":[67],"they":[68,72],"start":[69],"performing":[70],"well,":[71],"deployed":[74],"to":[75,88,98,143],"real-world":[77,184],"environment.":[78],"In":[79,117,150,175],"training":[81,123,162,243],"stage,":[82],"susceptible":[87],"poisoning":[90,159,186,241],"attacks.":[91,174],"While":[92],"proved":[97],"be":[99,227],"versatile":[100],"solving":[102],"host":[104],"challenges.":[106],"These":[107],"complex":[110],"ecosystems":[112],"especially":[113],"computer":[115],"vision.":[116],"practice,":[118],"when":[122,161],"often":[127],"ignored":[128],"while":[129],"deploying":[130],"models":[132],"real":[135],"world.":[136],"However,":[137],"pose":[140],"significant":[141],"risks":[142,238],"overall":[145],"reliability":[146,216],"system.":[149,219],"this":[151,224],"paper,":[152],"we":[153,177],"present":[154,195],"fundamentals":[156],"attacks":[160],"and":[167,194,205],"discuss":[168],"countermeasures":[169],"against":[170],"types":[172],"addition,":[176],"simulate":[178],"risk":[180],"posed":[181,239],"attack":[187],"system":[193],"novel":[197],"algorithm":[198],"MOVCE\u2014Model":[199],"verification":[200],"Convolutional":[202],"Neural":[203],"Network":[204],"Word":[206],"Embeddings":[207],"which":[208],"provides":[209],"an":[210],"effective":[211],"countermeasure":[212,221],"for":[213],"maintaining":[214],"described":[222],"paper":[225],"can":[226],"used":[228],"wide":[231],"variety":[232],"use":[234],"cases":[235],"where":[236],"similar.":[246]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":8},{"year":2023,"cited_by_count":2}],"updated_date":"2026-03-27T14:29:43.386196","created_date":"2025-10-10T00:00:00"}