{"id":"https://openalex.org/W3137869959","doi":"https://doi.org/10.1109/blackseacom52164.2021.9527756","title":"Adversarial Machine Learning Security Problems for 6G: mmWave Beam Prediction Use-Case","display_name":"Adversarial Machine Learning Security Problems for 6G: mmWave Beam Prediction Use-Case","publication_year":2021,"publication_date":"2021-05-24","ids":{"openalex":"https://openalex.org/W3137869959","doi":"https://doi.org/10.1109/blackseacom52164.2021.9527756","mag":"3137869959"},"language":"en","primary_location":{"id":"doi:10.1109/blackseacom52164.2021.9527756","is_oa":false,"landing_page_url":"https://doi.org/10.1109/blackseacom52164.2021.9527756","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Black Sea Conference on Communications and Networking (BlackSeaCom)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2103.07268","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5002685259","display_name":"Evren \u00c7atak","orcid":"https://orcid.org/0000-0003-1359-7128"},"institutions":[{"id":"https://openalex.org/I204778367","display_name":"Norwegian University of Science and Technology","ror":"https://ror.org/05xg72x27","country_code":"NO","type":"education","lineage":["https://openalex.org/I204778367"]}],"countries":["NO"],"is_corresponding":false,"raw_author_name":"Evren Catak","raw_affiliation_strings":["Norwegian University of Science and Technology, Gjovik, Norway","Norwegian University of Science and Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Norwegian University of Science and Technology, Gjovik, Norway","institution_ids":["https://openalex.org/I204778367"]},{"raw_affiliation_string":"Norwegian University of Science and Technology","institution_ids":["https://openalex.org/I204778367"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5044259885","display_name":"Ferhat \u00d6zg\u00fcr \u00c7atak","orcid":"https://orcid.org/0000-0002-2434-9966"},"institutions":[{"id":"https://openalex.org/I2799829267","display_name":"Simula Research Laboratory","ror":"https://ror.org/00vn06n10","country_code":"NO","type":"facility","lineage":["https://openalex.org/I2799829267"]}],"countries":["NO"],"is_corresponding":false,"raw_author_name":"Ferhat Ozgur Catak","raw_affiliation_strings":["Simula Research Lab, Fornebu, Norway","Simula Research Laboratory;"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Simula Research Lab, Fornebu, Norway","institution_ids":["https://openalex.org/I2799829267"]},{"raw_affiliation_string":"Simula Research Laboratory;","institution_ids":["https://openalex.org/I2799829267"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5015408227","display_name":"Arild Moldsvor","orcid":null},"institutions":[{"id":"https://openalex.org/I204778367","display_name":"Norwegian University of Science and Technology","ror":"https://ror.org/05xg72x27","country_code":"NO","type":"education","lineage":["https://openalex.org/I204778367"]}],"countries":["NO"],"is_corresponding":false,"raw_author_name":"Arild Moldsvor","raw_affiliation_strings":["Norwegian University of Science and Technology, Gjovik, Norway","Norwegian University of Science and Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Norwegian University of Science and Technology, Gjovik, Norway","institution_ids":["https://openalex.org/I204778367"]},{"raw_affiliation_string":"Norwegian University of Science and Technology","institution_ids":["https://openalex.org/I204778367"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":2,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12131","display_name":"Wireless Signal Modulation Classification","score":0.9959999918937683,"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/T12131","display_name":"Wireless Signal Modulation Classification","score":0.9959999918937683,"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/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9797000288963318,"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/T10936","display_name":"Millimeter-Wave Propagation and Modeling","score":0.9786999821662903,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.7665021419525146},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7111431956291199},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7082511782646179},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.7029748558998108},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5927370190620422},{"id":"https://openalex.org/keywords/online-machine-learning","display_name":"Online machine learning","score":0.42538121342658997},{"id":"https://openalex.org/keywords/computer-engineering","display_name":"Computer engineering","score":0.3396996855735779},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.33473002910614014},{"id":"https://openalex.org/keywords/unsupervised-learning","display_name":"Unsupervised learning","score":0.2514216899871826}],"concepts":[{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.7665021419525146},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7111431956291199},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7082511782646179},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.7029748558998108},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5927370190620422},{"id":"https://openalex.org/C115903097","wikidata":"https://www.wikidata.org/wiki/Q7094097","display_name":"Online machine learning","level":3,"score":0.42538121342658997},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.3396996855735779},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.33473002910614014},{"id":"https://openalex.org/C8038995","wikidata":"https://www.wikidata.org/wiki/Q1152135","display_name":"Unsupervised learning","level":2,"score":0.2514216899871826}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1109/blackseacom52164.2021.9527756","is_oa":false,"landing_page_url":"https://doi.org/10.1109/blackseacom52164.2021.9527756","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Black Sea Conference on Communications and Networking (BlackSeaCom)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2103.07268","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2103.07268","pdf_url":"https://arxiv.org/pdf/2103.07268","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":null,"raw_type":"text"},{"id":"mag:3137869959","is_oa":true,"landing_page_url":"http://export.arxiv.org/pdf/2103.07268","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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"arXiv (Cornell University)","raw_type":null},{"id":"doi:10.48550/arxiv.2103.07268","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2103.07268","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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2103.07268","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2103.07268","pdf_url":"https://arxiv.org/pdf/2103.07268","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":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3137869959.pdf","grobid_xml":"https://content.openalex.org/works/W3137869959.grobid-xml"},"referenced_works_count":23,"referenced_works":["https://openalex.org/W1833911422","https://openalex.org/W2104074482","https://openalex.org/W2195693430","https://openalex.org/W2562947506","https://openalex.org/W2791279818","https://openalex.org/W2914949576","https://openalex.org/W2919984499","https://openalex.org/W2962819920","https://openalex.org/W2962883549","https://openalex.org/W2963031347","https://openalex.org/W2963389226","https://openalex.org/W2963408914","https://openalex.org/W3002562626","https://openalex.org/W3003651800","https://openalex.org/W3011067038","https://openalex.org/W3011676575","https://openalex.org/W3013192867","https://openalex.org/W3093545357","https://openalex.org/W3120948833","https://openalex.org/W3126961449","https://openalex.org/W3127355490","https://openalex.org/W4233152543","https://openalex.org/W6729756640"],"related_works":["https://openalex.org/W3197012778","https://openalex.org/W3009964342","https://openalex.org/W3041431454","https://openalex.org/W2962700793","https://openalex.org/W3000456103","https://openalex.org/W2899811703","https://openalex.org/W3011678299","https://openalex.org/W2963178695","https://openalex.org/W2861867928","https://openalex.org/W2984300342","https://openalex.org/W3172840776","https://openalex.org/W3174263212","https://openalex.org/W2967057388","https://openalex.org/W3036512644","https://openalex.org/W3123175594","https://openalex.org/W2562947506","https://openalex.org/W2754537581","https://openalex.org/W3017800064","https://openalex.org/W3091959706","https://openalex.org/W3191721576"],"abstract_inverted_index":{"6G":[0,37,103,138,154],"is":[1,48,72,85,126],"the":[2,6,27,40,52,59,77,81,90,108,147,172,181],"next":[3],"generation":[4],"for":[5,67,98,107,137,140,153],"communication":[7],"systems.":[8],"In":[9],"recent":[10],"years,":[11],"machine":[12,62,104,123],"learning":[13,45,63,105,124,135,149],"algorithms":[14,32],"have":[15],"been":[16],"applied":[17],"widely":[18],"in":[19,36,80,156],"various":[20],"fields":[21],"such":[22],"as":[23],"health,":[24],"transportation,":[25],"and":[26],"autonomous":[28],"car.":[29],"The":[30,116,167],"predictive":[31],"will":[33],"be":[34],"used":[35],"problems.":[38],"With":[39],"rapid":[41],"developments":[42],"of":[43,89,171],"deep":[44,134],"techniques,":[46],"it":[47],"critical":[49],"to":[50,76,127,180],"take":[51],"security":[53,71,84,155],"concern":[54],"into":[55],"account":[56],"when":[57],"applying":[58],"algorithms.":[60,91],"While":[61],"offers":[64],"significant":[65],"advantages":[66],"6G,":[68],"AI":[69],"models\u2019":[70],"normally":[73],"ignored.":[74],"Due":[75],"many":[78],"applications":[79,139],"real":[82],"world,":[83],"a":[86,95],"vital":[87],"part":[88],"This":[92],"paper":[93],"proposes":[94],"mitigation":[96,150],"method":[97,165],"adversarial":[99,114,120,148],"attacks":[100,121],"against":[101,122],"proposed":[102],"models":[106,125,136],"millimeter-wave":[109,157],"(mmWave)":[110],"beam":[111,142,158],"prediction":[112,159],"using":[113],"learning.":[115],"main":[117],"idea":[118],"behind":[119],"produce":[128],"faulty":[129],"results":[130],"by":[131],"manipulating":[132],"trained":[133],"mmWave":[141],"prediction.":[143],"We":[144],"also":[145],"present":[146],"method\u2019s":[151],"performance":[152],"application":[160],"with":[161],"fast":[162],"gradient":[163],"sign":[164],"attack.":[166,185],"mean":[168],"square":[169],"errors":[170],"defended":[173],"model":[174,183],"under":[175],"attack":[176],"are":[177],"very":[178],"close":[179],"undefended":[182],"without":[184]},"counts_by_year":[{"year":2022,"cited_by_count":2}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
