{"id":"https://openalex.org/W4367016719","doi":"https://doi.org/10.1109/tccn.2023.3269764","title":"Embedding-Assisted Attentional Deep Learning for Real-World RF Fingerprinting of Bluetooth","display_name":"Embedding-Assisted Attentional Deep Learning for Real-World RF Fingerprinting of Bluetooth","publication_year":2023,"publication_date":"2023-04-25","ids":{"openalex":"https://openalex.org/W4367016719","doi":"https://doi.org/10.1109/tccn.2023.3269764"},"language":"en","primary_location":{"id":"doi:10.1109/tccn.2023.3269764","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tccn.2023.3269764","pdf_url":null,"source":{"id":"https://openalex.org/S2484188435","display_name":"IEEE Transactions on Cognitive Communications and Networking","issn_l":"2332-7731","issn":["2332-7731","2372-2045"],"is_oa":false,"is_in_doaj":false,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Cognitive Communications and Networking","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5076152765","display_name":"Anu Jagannath","orcid":"https://orcid.org/0000-0003-4459-5336"},"institutions":[{"id":"https://openalex.org/I12912129","display_name":"Northeastern University","ror":"https://ror.org/04t5xt781","country_code":"US","type":"education","lineage":["https://openalex.org/I12912129"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Anu Jagannath","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Northeastern University, Boston, MA, USA","Marconi-Rosenblatt AI/ML Innovation Laboratory, ANDRO Computational Solutions, LLC, Rome, NY, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Northeastern University, Boston, MA, USA","institution_ids":["https://openalex.org/I12912129"]},{"raw_affiliation_string":"Marconi-Rosenblatt AI/ML Innovation Laboratory, ANDRO Computational Solutions, LLC, Rome, NY, USA","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5068413452","display_name":"Jithin Jagannath","orcid":"https://orcid.org/0000-0002-4059-6481"},"institutions":[{"id":"https://openalex.org/I63190737","display_name":"University at Buffalo, State University of New York","ror":"https://ror.org/01y64my43","country_code":"US","type":"education","lineage":["https://openalex.org/I63190737"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jithin Jagannath","raw_affiliation_strings":["Department of Electrical Engineering, University at Buffalo, Buffalo, NY, USA","Marconi-Rosenblatt AI/ML Innovation Laboratory, ANDRO Computational Solutions, LLC, Rome, NY, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, University at Buffalo, Buffalo, NY, USA","institution_ids":["https://openalex.org/I63190737"]},{"raw_affiliation_string":"Marconi-Rosenblatt AI/ML Innovation Laboratory, ANDRO Computational Solutions, LLC, Rome, NY, USA","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5076152765"],"corresponding_institution_ids":["https://openalex.org/I12912129"],"apc_list":null,"apc_paid":null,"fwci":5.711,"has_fulltext":false,"cited_by_count":28,"citation_normalized_percentile":{"value":0.96415407,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":100},"biblio":{"volume":"9","issue":"4","first_page":"940","last_page":"949"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12801","display_name":"Bluetooth and Wireless Communication Technologies","score":0.9921000003814697,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T12801","display_name":"Bluetooth and Wireless Communication Technologies","score":0.9921000003814697,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T10986","display_name":"RFID technology advancements","score":0.989300012588501,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"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/T10326","display_name":"Indoor and Outdoor Localization Technologies","score":0.9886000156402588,"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/bluetooth","display_name":"Bluetooth","score":0.6763172745704651},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.603654146194458},{"id":"https://openalex.org/keywords/fingerprint","display_name":"Fingerprint (computing)","score":0.5691198706626892},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.5125606060028076},{"id":"https://openalex.org/keywords/dimensionality-reduction","display_name":"Dimensionality reduction","score":0.473716676235199},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.440208375453949},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4164401590824127},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.4123002290725708},{"id":"https://openalex.org/keywords/notation","display_name":"Notation","score":0.41060903668403625},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3211069107055664},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.20959526300430298},{"id":"https://openalex.org/keywords/arithmetic","display_name":"Arithmetic","score":0.14512905478477478},{"id":"https://openalex.org/keywords/wireless","display_name":"Wireless","score":0.09044218063354492}],"concepts":[{"id":"https://openalex.org/C546215728","wikidata":"https://www.wikidata.org/wiki/Q39531","display_name":"Bluetooth","level":3,"score":0.6763172745704651},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.603654146194458},{"id":"https://openalex.org/C2777826928","wikidata":"https://www.wikidata.org/wiki/Q3745713","display_name":"Fingerprint (computing)","level":2,"score":0.5691198706626892},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.5125606060028076},{"id":"https://openalex.org/C70518039","wikidata":"https://www.wikidata.org/wiki/Q16000077","display_name":"Dimensionality reduction","level":2,"score":0.473716676235199},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.440208375453949},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4164401590824127},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.4123002290725708},{"id":"https://openalex.org/C45357846","wikidata":"https://www.wikidata.org/wiki/Q2001982","display_name":"Notation","level":2,"score":0.41060903668403625},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3211069107055664},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.20959526300430298},{"id":"https://openalex.org/C94375191","wikidata":"https://www.wikidata.org/wiki/Q11205","display_name":"Arithmetic","level":1,"score":0.14512905478477478},{"id":"https://openalex.org/C555944384","wikidata":"https://www.wikidata.org/wiki/Q249","display_name":"Wireless","level":2,"score":0.09044218063354492},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tccn.2023.3269764","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tccn.2023.3269764","pdf_url":null,"source":{"id":"https://openalex.org/S2484188435","display_name":"IEEE Transactions on Cognitive Communications and Networking","issn_l":"2332-7731","issn":["2332-7731","2372-2045"],"is_oa":false,"is_in_doaj":false,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Cognitive Communications and Networking","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":37,"referenced_works":["https://openalex.org/W1677182931","https://openalex.org/W1874399837","https://openalex.org/W1985671681","https://openalex.org/W2006208855","https://openalex.org/W2038836370","https://openalex.org/W2132952395","https://openalex.org/W2278572312","https://openalex.org/W2604481500","https://openalex.org/W2746956234","https://openalex.org/W2748719146","https://openalex.org/W2749424833","https://openalex.org/W2774212884","https://openalex.org/W2797804613","https://openalex.org/W2903139904","https://openalex.org/W2914940294","https://openalex.org/W2956459828","https://openalex.org/W2962834855","https://openalex.org/W2963660578","https://openalex.org/W2984025449","https://openalex.org/W2995065926","https://openalex.org/W3007071731","https://openalex.org/W3035078899","https://openalex.org/W3045693983","https://openalex.org/W3047279638","https://openalex.org/W3085631338","https://openalex.org/W3091886083","https://openalex.org/W3092863397","https://openalex.org/W3106557886","https://openalex.org/W3154439874","https://openalex.org/W3167948099","https://openalex.org/W3172135703","https://openalex.org/W3182500101","https://openalex.org/W3207406191","https://openalex.org/W4283516443","https://openalex.org/W4288057775","https://openalex.org/W4308655556","https://openalex.org/W4320029361"],"related_works":["https://openalex.org/W4220926637","https://openalex.org/W2362681120","https://openalex.org/W4376643979","https://openalex.org/W2376320007","https://openalex.org/W4312465446","https://openalex.org/W2389079374","https://openalex.org/W2372429262","https://openalex.org/W2903653170","https://openalex.org/W2351967314","https://openalex.org/W2994280181"],"abstract_inverted_index":{"A":[0],"scalable":[1],"and":[2,34,40,90,105,124,149,168,192,221],"computationally":[3],"efficient":[4],"framework":[5,18,204],"is":[6,29,43],"designed":[7],"to":[8,62,144,181,189],"fingerprint":[9],"real-world":[10,96,234],"Bluetooth":[11,24,97],"devices.":[12,25],"We":[13],"propose":[14],"an":[15],"embedding-assisted":[16],"attentional":[17],"(Mbed-ATN)":[19],"suitable":[20],"for":[21,67],"fingerprinting":[22,93],"actual":[23],"Its":[26],"generalization":[27],"capability":[28,94],"analyzed":[30],"in":[31,79,206],"different":[32,102],"settings":[33],"the":[35,56,71,76,85,88,145,154,201,232],"effect":[36],"of":[37,87,139,198],"sample":[38,137,196],"length":[39,138],"anti-aliasing":[41,190],"decimation":[42,191],"demonstrated.":[44],"The":[45],"embedding":[46],"module":[47],"serves":[48],"as":[49],"a":[50,63,101,116,136,158,207],"dimensionality":[51],"reduction":[52],"unit":[53],"that":[54,186],"maps":[55],"high":[57],"dimensional":[58],"3D":[59],"input":[60,195],"tensor":[61],"1D":[64],"feature":[65],"vector":[66],"further":[68],"processing":[69],"by":[70],"ATN":[72],"module.":[73],"Furthermore,":[74],"unlike":[75],"prior":[77],"research":[78],"this":[80],"field,":[81],"we":[82,184],"closely":[83],"evaluate":[84],"complexity":[86],"model":[89],"test":[91],"its":[92],"with":[95],"dataset":[98],"collected":[99],"under":[100,231],"time":[103],"frame":[104],"experimental":[106],"setting":[107],"while":[108],"being":[109],"trained":[110],"on":[111],"another.":[112],"Our":[113],"study":[114],"reveals":[115],"<inline-formula":[117,125,159,169,208,222],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[118,126,160,170,209,223],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">":[119,127,161,171,210,224],"<tex-math":[120,128,162,172,211,225],"notation=\"LaTeX\">$9.17\\times":[121],"$":[122,130,164,174,213,227],"</tex-math></inline-formula>":[123,131,165,175,214,228],"notation=\"LaTeX\">$65.2\\times":[129],"lesser":[132,176],"memory":[133],"usage":[134],"at":[135,193],"100":[140],"kS":[141],"when":[142,179,187],"compared":[143,180],"benchmark":[146],"-":[147],"GRU":[148],"Oracle":[150],"models":[151],"respectively.":[152],"Further,":[153],"proposed":[155,202],"Mbed-ATN":[156,203],"showcases":[157],"notation=\"LaTeX\">$16.9\\times":[163],"fewer":[166,218],"FLOPs":[167],"notation=\"LaTeX\">$7.5\\times":[173],"trainable":[177],"parameters":[178],"Oracle.":[182],"Finally,":[183],"show":[185],"subject":[188],"greater":[194],"lengths":[197],"1":[199],"MS,":[200],"results":[205],"notation=\"LaTeX\">$5.32\\times":[212],"higher":[215,229],"TPR,":[216],"37.9%":[217],"false":[219],"alarms,":[220],"notation=\"LaTeX\">$6.74\\times":[226],"accuracy":[230],"challenging":[233],"setting.":[235]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":15},{"year":2024,"cited_by_count":9},{"year":2023,"cited_by_count":3}],"updated_date":"2026-03-09T08:58:05.943551","created_date":"2025-10-10T00:00:00"}
