{"id":"https://openalex.org/W7225662973","doi":"https://doi.org/10.21203/rs.3.rs-11123003/v1","title":"TABLNet: Trustworthy Adaptive Broad Learning Network for Physical-Layer Device Authenticationin Intelligent IoT Networks","display_name":"TABLNet: Trustworthy Adaptive Broad Learning Network for Physical-Layer Device Authenticationin Intelligent IoT Networks","publication_year":2026,"publication_date":"2026-11-09","ids":{"openalex":"https://openalex.org/W7225662973","doi":"https://doi.org/10.21203/rs.3.rs-11123003/v1"},"language":"en","primary_location":{"id":"doi:10.21203/rs.3.rs-11123003/v1","doi":"https://doi.org/10.21203/rs.3.rs-11123003/v1","is_oa":true,"landing_page_url":"https://doi.org/10.21203/rs.3.rs-11123003/v1","pdf_url":"https://www.researchsquare.com/article/rs-11123003/latest.pdf","source":{"id":"https://openalex.org/S4306525896","display_name":"Research Square","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"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":"Research Square","raw_type":"posted-content"},"volume":null,"type":"preprint","is_traditional":true,"indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://www.researchsquare.com/article/rs-11123003/latest.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5161307180","display_name":"Xinyu xiang","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xinyu xiang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5161324530","display_name":"Xianyu Chen","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xianyu Chen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5161310859","display_name":"Jinwen Liao","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jinwen Liao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5161357551","display_name":"Dan Qin","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dan Qin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5161322093","display_name":"Yi Zhang","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yi Zhang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12131","display_name":"Wireless Signal Modulation Classification","score":0.989300012588501,"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":0.989300012588501,"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/T10964","display_name":"Wireless Communication Security Techniques","score":0.0071000000461936,"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/T11504","display_name":"Advanced Authentication Protocols Security","score":0.00039999998989515007,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/specific-emitter-identification","display_name":"specific emitter identification","score":0.7390000224113464},{"id":"https://openalex.org/keywords/rf-fingerprinting","display_name":"radio frequency fingerprinting","score":0.7609999775886536},{"id":"https://openalex.org/keywords/flat-network-architecture","display_name":"flat network architecture","score":0.5690000057220459},{"id":"https://openalex.org/keywords/lightweight-authentication","display_name":"lightweight authentication","score":0.46000000834465027},{"id":"https://openalex.org/keywords/edge-devices","display_name":"edge devices","score":0.49399998784065247}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7833999991416931},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5855000019073486},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4616999924182892},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.45190000534057617},{"id":"https://openalex.org/C193415008","wikidata":"https://www.wikidata.org/wiki/Q639681","display_name":"Network architecture","level":2,"score":0.444599986076355},{"id":"https://openalex.org/C2779960059","wikidata":"https://www.wikidata.org/wiki/Q7113681","display_name":"Overhead (engineering)","level":2,"score":0.4269999861717224},{"id":"https://openalex.org/C82876162","wikidata":"https://www.wikidata.org/wiki/Q17096504","display_name":"Latency (audio)","level":2,"score":0.41659998893737793},{"id":"https://openalex.org/C62611344","wikidata":"https://www.wikidata.org/wiki/Q1062658","display_name":"Node (physics)","level":2,"score":0.4020000100135803},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.38109999895095825},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.37950000166893005},{"id":"https://openalex.org/C132964779","wikidata":"https://www.wikidata.org/wiki/Q2110223","display_name":"Raw data","level":2,"score":0.36410000920295715},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.36010000109672546},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.36000001430511475},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.3553999960422516},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.3370000123977661},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3325999975204468},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.328000009059906},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.3237999975681305},{"id":"https://openalex.org/C138236772","wikidata":"https://www.wikidata.org/wiki/Q25098575","display_name":"Edge device","level":3,"score":0.30889999866485596},{"id":"https://openalex.org/C2778456923","wikidata":"https://www.wikidata.org/wiki/Q5337692","display_name":"Edge computing","level":3,"score":0.30649998784065247},{"id":"https://openalex.org/C153701036","wikidata":"https://www.wikidata.org/wiki/Q659974","display_name":"Trustworthiness","level":2,"score":0.3043999969959259},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.30390000343322754},{"id":"https://openalex.org/C178489894","wikidata":"https://www.wikidata.org/wiki/Q8789","display_name":"Cryptography","level":2,"score":0.29179999232292175},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2883000075817108},{"id":"https://openalex.org/C8642999","wikidata":"https://www.wikidata.org/wiki/Q4171168","display_name":"Hyperparameter","level":2,"score":0.28139999508857727},{"id":"https://openalex.org/C9628104","wikidata":"https://www.wikidata.org/wiki/Q788009","display_name":"Autonomous system (mathematics)","level":2,"score":0.27630001306533813},{"id":"https://openalex.org/C110875604","wikidata":"https://www.wikidata.org/wiki/Q75","display_name":"The Internet","level":2,"score":0.27000001072883606},{"id":"https://openalex.org/C148417208","wikidata":"https://www.wikidata.org/wiki/Q4825882","display_name":"Authentication (law)","level":2,"score":0.26899999380111694},{"id":"https://openalex.org/C2778355321","wikidata":"https://www.wikidata.org/wiki/Q17079427","display_name":"Identity (music)","level":2,"score":0.2669999897480011},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.2599000036716461},{"id":"https://openalex.org/C20136886","wikidata":"https://www.wikidata.org/wiki/Q749647","display_name":"Interoperability","level":2,"score":0.2549999952316284},{"id":"https://openalex.org/C2776650193","wikidata":"https://www.wikidata.org/wiki/Q264661","display_name":"Obstacle","level":2,"score":0.25459998846054077},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.2535000145435333},{"id":"https://openalex.org/C125014702","wikidata":"https://www.wikidata.org/wiki/Q4680749","display_name":"Adaptive learning","level":2,"score":0.25029999017715454}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.21203/rs.3.rs-11123003/v1","doi":"https://doi.org/10.21203/rs.3.rs-11123003/v1","is_oa":true,"landing_page_url":"https://doi.org/10.21203/rs.3.rs-11123003/v1","pdf_url":"https://www.researchsquare.com/article/rs-11123003/latest.pdf","source":{"id":"https://openalex.org/S4306525896","display_name":"Research Square","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"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":"Research Square","raw_type":"posted-content"}],"best_oa_location":{"id":"doi:10.21203/rs.3.rs-11123003/v1","doi":"https://doi.org/10.21203/rs.3.rs-11123003/v1","is_oa":true,"landing_page_url":"https://doi.org/10.21203/rs.3.rs-11123003/v1","pdf_url":"https://www.researchsquare.com/article/rs-11123003/latest.pdf","source":{"id":"https://openalex.org/S4306525896","display_name":"Research Square","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"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":"Research Square","raw_type":"posted-content"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7225662973.pdf","grobid_xml":"https://content.openalex.org/works/W7225662973.grobid-xml"},"referenced_works_count":23,"referenced_works":["https://openalex.org/W2304380770","https://openalex.org/W2624953603","https://openalex.org/W2738226240","https://openalex.org/W2884159461","https://openalex.org/W2899086481","https://openalex.org/W2916238263","https://openalex.org/W2938144699","https://openalex.org/W2977014769","https://openalex.org/W2981392034","https://openalex.org/W2984025449","https://openalex.org/W3003174479","https://openalex.org/W3016147814","https://openalex.org/W3088383832","https://openalex.org/W3096285193","https://openalex.org/W3119535973","https://openalex.org/W3119569744","https://openalex.org/W3136322890","https://openalex.org/W3153070384","https://openalex.org/W3170485195","https://openalex.org/W3172466280","https://openalex.org/W3194740358","https://openalex.org/W3205971195","https://openalex.org/W4281641120"],"related_works":["https://openalex.org/W7167571892","https://openalex.org/W7225375962","https://openalex.org/W2907410281","https://openalex.org/W4413273042","https://openalex.org/W4391759703","https://openalex.org/W4413833618","https://openalex.org/W6948095902","https://openalex.org/W7162088693","https://openalex.org/W4389779322","https://openalex.org/W4407214537"],"abstract_inverted_index":{"Abstract":[0],"Securing":[1],"the":[2,31,35,100,128],"expanding":[3],"internet":[4],"of":[5,37],"things":[6],"(IoT)":[7],"ecosystem":[8],"demands":[9,54],"lightweightauthentication":[10],"mechanisms":[11],"compatible":[12],"with":[13],"hardware-constrained":[14],"edge":[15],"end-points.":[16],"Specific":[17],"emitter":[18],"identification":[19],"(SEI)":[20],"exploits":[21],"manufacturing-induced":[22],"radiofrequency":[23],"(RF)":[24],"fingerprints":[25],"to":[26,74,99],"verify":[27],"device":[28],"identity":[29],"at":[30],"physical":[32],"layer,":[33],"cir-cumventing":[34],"overhead":[36],"upper-layer":[38],"cryptographic":[39],"schemes.":[40],"Nevertheless,contemporary":[41],"deep":[42,78,158],"generative":[43,94],"architectures":[44],"employed":[45],"for":[46],"automated":[47],"RF":[48,139],"fin-gerprint":[49],"synthesis":[50],"impose":[51],"prohibitive":[52],"computational":[53],"that":[55],"hinder":[56],"theirdeployment":[57],"on":[58,105,136],"resource-limited":[59],"platforms.":[60],"In":[61],"this":[62],"paper,":[63],"a":[64,83],"trustworthy":[65],"adap-tive":[66],"broad":[67],"learning":[68,159],"network":[69,129],"(TABLNet)":[70],"framework":[71],"is":[72],"proposed":[73],"overcomethese":[75],"limitations.":[76],"Unlike":[77],"hierarchical":[79],"models,":[80],"TABLNet":[81,142],"adopts":[82],"lat-erally":[84],"expandable":[85],"flat":[86],"architecture":[87],"wherein":[88],"raw":[89],"signal":[90],"samples":[91],"are":[92],"projectedonto":[93],"feature":[95],"nodes":[96],"directly":[97],"connected":[98],"decision":[101],"layer.":[102],"Weightoptimization":[103],"relies":[104],"pseudoinverse":[106],"computation":[107],"rather":[108],"than":[109],"iterative":[110],"back-propagation,":[111],"thereby":[112],"suppressing":[113],"gradient":[114],"instability":[115],"and":[116],"substantially":[117],"curtailingtraining":[118],"duration.":[119],"Moreover,":[120],"an":[121,150],"autonomous":[122],"node":[123],"expansion":[124],"mechanism":[125],"dynam-ically":[126],"calibrates":[127],"width,":[130],"eliminating":[131],"manual":[132],"hyperparameter":[133],"search.Comprehensive":[134],"experiments":[135],"two":[137],"hardware-captured":[138],"datasets":[140],"demonstratethat":[141],"achieves":[143],"competitive":[144],"or":[145],"superior":[146],"classification":[147],"accuracy":[148],"whiledelivering":[149],"order-of-magnitude":[151],"reduction":[152],"in":[153],"training":[154],"latency":[155],"compared":[156],"withprevailing":[157],"baselines.":[160]},"counts_by_year":[],"updated_date":"2026-11-11T12:16:26.678958","created_date":"2026-11-10T00:00:00"}