{"id":"https://openalex.org/W4312473983","doi":"https://doi.org/10.1109/access.2022.3224930","title":"A Methodology for Evaluating the Robustness of Anomaly Detectors to Adversarial Attacks in Industrial Scenarios","display_name":"A Methodology for Evaluating the Robustness of Anomaly Detectors to Adversarial Attacks in Industrial Scenarios","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4312473983","doi":"https://doi.org/10.1109/access.2022.3224930"},"language":"en","primary_location":{"id":"doi:10.1109/access.2022.3224930","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2022.3224930","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/09964189.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","datacite","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/09964189.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5076837396","display_name":"\u00c1ngel Luis Perales G\u00f3mez","orcid":"https://orcid.org/0000-0003-1004-881X"},"institutions":[{"id":"https://openalex.org/I80180929","display_name":"Universidad de Murcia","ror":"https://ror.org/03p3aeb86","country_code":"ES","type":"education","lineage":["https://openalex.org/I80180929"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Angel Luis Perales Gomez","raw_affiliation_strings":["Departamento de Ingeniería y Tecnología de Computadores, University of Murcia, Espinardo, Murcia, Spain"],"raw_orcid":"https://orcid.org/0000-0003-1004-881X","affiliations":[{"raw_affiliation_string":"Departamento de Ingeniería y Tecnología de Computadores, University of Murcia, Espinardo, Murcia, Spain","institution_ids":["https://openalex.org/I80180929"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5026124565","display_name":"Lorenzo Fern\u00e1ndez Maim\u00f3","orcid":"https://orcid.org/0000-0003-2027-4239"},"institutions":[{"id":"https://openalex.org/I80180929","display_name":"Universidad de Murcia","ror":"https://ror.org/03p3aeb86","country_code":"ES","type":"education","lineage":["https://openalex.org/I80180929"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Lorenzo Fernandez Maimo","raw_affiliation_strings":["Departamento de Ingeniería y Tecnología de Computadores, University of Murcia, Espinardo, Murcia, Spain"],"raw_orcid":"https://orcid.org/0000-0003-2027-4239","affiliations":[{"raw_affiliation_string":"Departamento de Ingeniería y Tecnología de Computadores, University of Murcia, Espinardo, Murcia, Spain","institution_ids":["https://openalex.org/I80180929"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057591697","display_name":"F\u00e9lix J. Garc\u00eda Clemente","orcid":"https://orcid.org/0000-0001-6181-5033"},"institutions":[{"id":"https://openalex.org/I80180929","display_name":"Universidad de Murcia","ror":"https://ror.org/03p3aeb86","country_code":"ES","type":"education","lineage":["https://openalex.org/I80180929"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Felix J. Garcia Clemente","raw_affiliation_strings":["Departamento de Ingeniería y Tecnología de Computadores, University of Murcia, Espinardo, Murcia, Spain"],"raw_orcid":"https://orcid.org/0000-0001-6181-5033","affiliations":[{"raw_affiliation_string":"Departamento de Ingeniería y Tecnología de Computadores, University of Murcia, Espinardo, Murcia, Spain","institution_ids":["https://openalex.org/I80180929"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5042958236","display_name":"Javier Alejandro Maroto Morales","orcid":"https://orcid.org/0000-0003-4206-9383"},"institutions":[{"id":"https://openalex.org/I5124864","display_name":"\u00c9cole Polytechnique F\u00e9d\u00e9rale de Lausanne","ror":"https://ror.org/02s376052","country_code":"CH","type":"education","lineage":["https://openalex.org/I2799323385","https://openalex.org/I5124864"]}],"countries":["CH"],"is_corresponding":false,"raw_author_name":"Javier Alejandro Maroto Morales","raw_affiliation_strings":["École polytechnique fédérale de Lausanne, Lausanne, Switzerland"],"raw_orcid":"https://orcid.org/0000-0003-4206-9383","affiliations":[{"raw_affiliation_string":"École polytechnique fédérale de Lausanne, Lausanne, Switzerland","institution_ids":["https://openalex.org/I5124864"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5063531116","display_name":"Alberto Huertas Celdr\u00e1n","orcid":"https://orcid.org/0000-0001-7125-1710"},"institutions":[{"id":"https://openalex.org/I202697423","display_name":"University of Zurich","ror":"https://ror.org/02crff812","country_code":"CH","type":"education","lineage":["https://openalex.org/I202697423"]}],"countries":["CH"],"is_corresponding":false,"raw_author_name":"Alberto Huertas Celdran","raw_affiliation_strings":["Department of Informatics (IfI), Communication Systems Group CSG, University of Zurich, Zürich, Switzerland"],"raw_orcid":"https://orcid.org/0000-0001-7125-1710","affiliations":[{"raw_affiliation_string":"Department of Informatics (IfI), Communication Systems Group CSG, University of Zurich, Zürich, Switzerland","institution_ids":["https://openalex.org/I202697423"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5070889566","display_name":"G\u00e9r\u00f4me Bovet","orcid":"https://orcid.org/0000-0002-4534-3483"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gerome Bovet","raw_affiliation_strings":["Cyber-Defence Campus within armasuisse Science & Technology, Thun, Switzerland"],"raw_orcid":"https://orcid.org/0000-0002-4534-3483","affiliations":[{"raw_affiliation_string":"Cyber-Defence Campus within armasuisse Science & Technology, Thun, Switzerland","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.6965,"has_fulltext":true,"cited_by_count":6,"citation_normalized_percentile":{"value":0.74839709,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":"10","issue":null,"first_page":"124582","last_page":"124594"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9975000023841858,"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":0.9975000023841858,"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"}},{"id":"https://openalex.org/T12122","display_name":"Physical Unclonable Functions (PUFs) and Hardware Security","score":0.9912999868392944,"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":0.7449675798416138},{"id":"https://openalex.org/keywords/testbed","display_name":"Testbed","score":0.6500866413116455},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6484441757202148},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.5730205178260803},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5324816107749939},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.49491065740585327},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4736139476299286},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4471028745174408},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4239177107810974},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.380533903837204}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7449675798416138},{"id":"https://openalex.org/C31395832","wikidata":"https://www.wikidata.org/wiki/Q1318674","display_name":"Testbed","level":2,"score":0.6500866413116455},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6484441757202148},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.5730205178260803},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5324816107749939},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.49491065740585327},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4736139476299286},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4471028745174408},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4239177107810974},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.380533903837204},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"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/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0}],"mesh":[],"locations_count":5,"locations":[{"id":"doi:10.1109/access.2022.3224930","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2022.3224930","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/09964189.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:www.zora.uzh.ch:229616","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4306401281","display_name":"Zurich Open Repository and Archive (University of Zurich)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I202697423","host_organization_name":"University of Zurich","host_organization_lineage":["https://openalex.org/I202697423"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":"Perales G\u00f3mez, \u00c1ngel L; Maim\u00f3, Lorenzo Fern\u00e1ndez; Clemente, F\u00e9lix J Garc\u00eda; Morales, Javier A Maroto; Huertas Celdran, Alberto; Bovet, G\u00e9r\u00f4me (2022). A Methodology for Evaluating the Robustness of Anomaly Detectors to Adversarial Attacks in Industrial Scenarios. IEEE Access, 10:124582-124594.","raw_type":"info:eu-repo/semantics/article"},{"id":"pmh:oai:doaj.org/article:94e267dac1df4a22b09371f564527956","is_oa":true,"landing_page_url":"https://doaj.org/article/94e267dac1df4a22b09371f564527956","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 10, Pp 124582-124594 (2022)","raw_type":"article"},{"id":"pmh:oai:infoscience.epfl.ch:300173","is_oa":true,"landing_page_url":"https://infoscience.epfl.ch/handle/20.500.14299/194804","pdf_url":null,"source":{"id":"https://openalex.org/S4306400487","display_name":"Infoscience (Ecole Polytechnique F\u00e9d\u00e9rale de Lausanne)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"WoS","raw_type":"research article"},{"id":"doi:10.5167/uzh-229616","is_oa":true,"landing_page_url":"https://doi.org/10.5167/uzh-229616","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"JournalArticle"}],"best_oa_location":{"id":"doi:10.1109/access.2022.3224930","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2022.3224930","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/09964189.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure","score":0.6299999952316284}],"awards":[{"id":"https://openalex.org/G2224388298","display_name":null,"funder_award_id":"RTI2018-095855-B-I00","funder_id":"https://openalex.org/F4320315062","funder_display_name":"Ministerio de Ciencia, Innovaci\u00f3n y Universidades"},{"id":"https://openalex.org/G8181105605","display_name":null,"funder_award_id":"RTI2018","funder_id":"https://openalex.org/F4320315062","funder_display_name":"Ministerio de Ciencia, Innovaci\u00f3n y Universidades"}],"funders":[{"id":"https://openalex.org/F4320315062","display_name":"Ministerio de Ciencia, Innovaci\u00f3n y Universidades","ror":null}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4312473983.pdf","grobid_xml":"https://content.openalex.org/works/W4312473983.grobid-xml"},"referenced_works_count":40,"referenced_works":["https://openalex.org/W2004186751","https://openalex.org/W2066296745","https://openalex.org/W2243397390","https://openalex.org/W2303531378","https://openalex.org/W2686240873","https://openalex.org/W2761401473","https://openalex.org/W2765204009","https://openalex.org/W2896370767","https://openalex.org/W2904171273","https://openalex.org/W2946344298","https://openalex.org/W2962756933","https://openalex.org/W2963096987","https://openalex.org/W2963416329","https://openalex.org/W2983044655","https://openalex.org/W2983358147","https://openalex.org/W2994725566","https://openalex.org/W2995121266","https://openalex.org/W3007882214","https://openalex.org/W3015481738","https://openalex.org/W3022595769","https://openalex.org/W3034214559","https://openalex.org/W3048094199","https://openalex.org/W3086419524","https://openalex.org/W3088412845","https://openalex.org/W3090117266","https://openalex.org/W3138207087","https://openalex.org/W3161403725","https://openalex.org/W3163438416","https://openalex.org/W3165857918","https://openalex.org/W3202566927","https://openalex.org/W4206049592","https://openalex.org/W4293846201","https://openalex.org/W6739868092","https://openalex.org/W6740005241","https://openalex.org/W6740106602","https://openalex.org/W6748458661","https://openalex.org/W6752654261","https://openalex.org/W6769760169","https://openalex.org/W6771565871","https://openalex.org/W6784030240"],"related_works":["https://openalex.org/W2883256816","https://openalex.org/W2171408034","https://openalex.org/W3003320923","https://openalex.org/W2106140982","https://openalex.org/W4226493464","https://openalex.org/W4312417841","https://openalex.org/W3193565141","https://openalex.org/W3133861977","https://openalex.org/W3167935049","https://openalex.org/W3029198973"],"abstract_inverted_index":{"Anomaly":[0,42,113],"Detection":[1,43,114],"systems":[2],"based":[3],"on":[4,99,182],"Machine":[5],"and":[6,124,175],"Deep":[7],"learning":[8],"are":[9,23],"the":[10,18,39,45,100,110,145,148,164,213,227],"most":[11],"promising":[12],"solutions":[13],"to":[14,25,37,62,72,81,108,134,166,218,232],"detect":[15],"cyberattacks":[16],"in":[17,44,57,116,225],"industry.":[19],"However,":[20,47],"these":[21],"techniques":[22,33],"vulnerable":[24],"adversarial":[26,138,220],"attacks":[27],"that":[28,192],"downgrade":[29],"predictions":[30],"performance.":[31],"Several":[32],"haven":[34],"been":[35],"proposed":[36],"measure":[38],"robustness":[40,111,209,235],"of":[41,67,112,128,155,206,210,212,236],"literature.":[46],"they":[48],"do":[49],"not":[50],"consider":[51],"that,":[52],"although":[53],"a":[54,91,106,126,152,156,168,204],"small":[55],"perturbation":[56,85,205,228],"an":[58,63,83,137],"anomalous":[59],"sample":[60,139,215],"belonging":[61],"attack,":[64],"i.e.,":[65],"Denial":[66],"Service,":[68],"could":[69],"cause":[70],"it":[71,89],"be":[73],"misclassified":[74],"as":[75],"normal":[76,93],"while":[77],"retaining":[78],"its":[79],"ability":[80],"damage,":[82],"excessive":[84],"might":[86],"also":[87],"transform":[88],"into":[90],"truly":[92],"sample,":[94],"with":[95],"no":[96],"real":[97],"impact":[98],"industrial":[101,117],"system.":[102],"This":[103],"paper":[104],"presents":[105],"methodology":[107,120,165],"calculate":[109],"models":[115,130,133],"scenarios.":[118],"The":[119,189],"comprises":[121],"four":[122],"steps":[123],"use":[125],"set":[127],"additional":[129],"called":[131],"support":[132],"determine":[135],"if":[136],"remains":[140],"anomalous.":[141],"We":[142],"carried":[143],"out":[144],"validation":[146],"using":[147],"Tennessee":[149],"Eastman":[150],"process,":[151],"simulated":[153],"testbed":[154],"chemical":[157],"process.":[158],"In":[159],"such":[160],"scenario,":[161],"we":[162],"applied":[163],"both":[167],"Long-Short":[169],"Term":[170],"Memory":[171],"(LSTM)":[172],"neural":[173],"network":[174],"1-dimensional":[176],"Convolutional":[177],"Neural":[178],"Network":[179],"(1D-CNN)":[180],"focused":[181],"detecting":[183],"anomalies":[184],"produced":[185],"by":[186],"different":[187],"cyberattacks.":[188],"experiments":[190],"showed":[191],"1D-CNN":[193,226],"is":[194,216],"significantly":[195],"more":[196],"robust":[197],"than":[198],"LSTM":[199],"for":[200,222],"our":[201],"testbed.":[202],"Specifically,":[203],"60%":[207],"(empirical":[208,234],"0.6)":[211],"original":[214],"needed":[217],"generate":[219],"samples":[221],"LSTM,":[223],"whereas":[224],"required":[229],"increases":[230],"up":[231],"111%":[233],"1.11).":[237]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":1}],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2025-10-10T00:00:00"}