{"id":"https://openalex.org/W7140170715","doi":"https://doi.org/10.48550/arxiv.2603.21596","title":"In-network Attack Detection with Federated Deep Learning in IoT Networks: Real Implementation and Analysis","display_name":"In-network Attack Detection with Federated Deep Learning in IoT Networks: Real Implementation and Analysis","publication_year":2026,"publication_date":"2026-03-23","ids":{"openalex":"https://openalex.org/W7140170715","doi":"https://doi.org/10.48550/arxiv.2603.21596"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.21596","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.21596","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":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2603.21596","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Chaudhary, Devashish","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chaudhary, Devashish","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Rajasegarar, Sutharshan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Rajasegarar, Sutharshan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Pokhrel, Shiva Raj","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Pokhrel, Shiva Raj","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Pan, Lei","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Pan, Lei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":null,"display_name":"D, Ruby","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"D, Ruby","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":false,"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/T10400","display_name":"Network Security and Intrusion Detection","score":0.6442999839782715,"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/T10400","display_name":"Network Security and Intrusion Detection","score":0.6442999839782715,"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/T11598","display_name":"Internet Traffic Analysis and Secure E-voting","score":0.09749999642372131,"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":0.07970000058412552,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/testbed","display_name":"Testbed","score":0.8339999914169312},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.7590000033378601},{"id":"https://openalex.org/keywords/software-deployment","display_name":"Software deployment","score":0.666100025177002},{"id":"https://openalex.org/keywords/overhead","display_name":"Overhead (engineering)","score":0.5374000072479248},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.49390000104904175},{"id":"https://openalex.org/keywords/internet-of-things","display_name":"Internet of Things","score":0.4896000027656555},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.44510000944137573},{"id":"https://openalex.org/keywords/edge-device","display_name":"Edge device","score":0.4390000104904175},{"id":"https://openalex.org/keywords/latency","display_name":"Latency (audio)","score":0.4269999861717224}],"concepts":[{"id":"https://openalex.org/C31395832","wikidata":"https://www.wikidata.org/wiki/Q1318674","display_name":"Testbed","level":2,"score":0.8339999914169312},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.7590000033378601},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7519000172615051},{"id":"https://openalex.org/C105339364","wikidata":"https://www.wikidata.org/wiki/Q2297740","display_name":"Software deployment","level":2,"score":0.666100025177002},{"id":"https://openalex.org/C2779960059","wikidata":"https://www.wikidata.org/wiki/Q7113681","display_name":"Overhead (engineering)","level":2,"score":0.5374000072479248},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.5284000039100647},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.49390000104904175},{"id":"https://openalex.org/C81860439","wikidata":"https://www.wikidata.org/wiki/Q251212","display_name":"Internet of Things","level":2,"score":0.4896000027656555},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.44510000944137573},{"id":"https://openalex.org/C138236772","wikidata":"https://www.wikidata.org/wiki/Q25098575","display_name":"Edge device","level":3,"score":0.4390000104904175},{"id":"https://openalex.org/C82876162","wikidata":"https://www.wikidata.org/wiki/Q17096504","display_name":"Latency (audio)","level":2,"score":0.4269999861717224},{"id":"https://openalex.org/C2778456923","wikidata":"https://www.wikidata.org/wiki/Q5337692","display_name":"Edge computing","level":3,"score":0.4171000123023987},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.39800000190734863},{"id":"https://openalex.org/C24590314","wikidata":"https://www.wikidata.org/wiki/Q336038","display_name":"Wireless sensor network","level":2,"score":0.3896999955177307},{"id":"https://openalex.org/C88796919","wikidata":"https://www.wikidata.org/wiki/Q1142907","display_name":"Backbone network","level":2,"score":0.38119998574256897},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.36649999022483826},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.3531000018119812},{"id":"https://openalex.org/C93996380","wikidata":"https://www.wikidata.org/wiki/Q44127","display_name":"Server","level":2,"score":0.34540000557899475},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.3366999924182892},{"id":"https://openalex.org/C2992525071","wikidata":"https://www.wikidata.org/wiki/Q50818671","display_name":"Federated learning","level":2,"score":0.3287999927997589},{"id":"https://openalex.org/C110875604","wikidata":"https://www.wikidata.org/wiki/Q75","display_name":"The Internet","level":2,"score":0.32019999623298645},{"id":"https://openalex.org/C35525427","wikidata":"https://www.wikidata.org/wiki/Q745881","display_name":"Intrusion detection system","level":2,"score":0.30480000376701355},{"id":"https://openalex.org/C182590292","wikidata":"https://www.wikidata.org/wiki/Q989632","display_name":"Network security","level":2,"score":0.29660001397132874},{"id":"https://openalex.org/C2985745059","wikidata":"https://www.wikidata.org/wiki/Q245","display_name":"Raspberry pi","level":3,"score":0.29269999265670776},{"id":"https://openalex.org/C70061542","wikidata":"https://www.wikidata.org/wiki/Q989016","display_name":"Distributed database","level":2,"score":0.28839999437332153},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.28200000524520874},{"id":"https://openalex.org/C157764524","wikidata":"https://www.wikidata.org/wiki/Q1383412","display_name":"Throughput","level":3,"score":0.27559998631477356},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.27000001072883606},{"id":"https://openalex.org/C38822068","wikidata":"https://www.wikidata.org/wiki/Q131406","display_name":"Denial-of-service attack","level":3,"score":0.2644999921321869},{"id":"https://openalex.org/C46637626","wikidata":"https://www.wikidata.org/wiki/Q6693015","display_name":"Low latency (capital markets)","level":2,"score":0.25360000133514404},{"id":"https://openalex.org/C12997251","wikidata":"https://www.wikidata.org/wiki/Q567560","display_name":"Anomaly (physics)","level":2,"score":0.2524000108242035},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.2524000108242035}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.21596","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.21596","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":"doi:10.48550/arxiv.2603.21596","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.21596","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":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"The":[0,117,137],"rapid":[1],"expansion":[2],"of":[3,6,19,33],"the":[4,17,127,148],"Internet":[5],"Things":[7],"(IoT)":[8],"and":[9,42,68,89,113,124],"its":[10,130],"integration":[11],"with":[12],"backbone":[13],"networks":[14],"have":[15],"heightened":[16],"risk":[18],"security":[20],"breaches.":[21],"Traditional":[22],"centralized":[23,149],"approaches":[24],"to":[25,35,75,110,147],"anomaly":[26,51,120],"detection,":[27],"which":[28],"require":[29],"transferring":[30],"large":[31],"volumes":[32],"data":[34,66],"central":[36,97],"servers,":[37],"suffer":[38],"from":[39],"privacy,":[40],"scalability,":[41],"latency":[43],"limitations.":[44],"This":[45],"paper":[46],"proposes":[47],"a":[48,96],"lightweight":[49],"autoencoder-based":[50],"detection":[52,63,121],"framework":[53],"designed":[54],"for":[55],"deployment":[56],"on":[57,86,126],"resource-constrained":[58],"edge":[59,87],"devices,":[60,81],"enabling":[61],"real-time":[62],"while":[64,143],"minimizing":[65],"transfer":[67],"preserving":[69],"privacy.":[70],"Federated":[71],"learning":[72],"is":[73],"employed":[74],"train":[76],"models":[77],"collaboratively":[78],"across":[79],"distributed":[80],"where":[82],"local":[83],"training":[84],"occurs":[85],"nodes":[88,107],"only":[90],"model":[91],"weights":[92],"are":[93],"aggregated":[94],"at":[95],"server.":[98],"A":[99],"real-world":[100],"IoT":[101],"testbed":[102],"using":[103],"Raspberry":[104],"Pi":[105],"sensor":[106],"was":[108,140],"developed":[109],"collect":[111],"normal":[112],"attack":[114],"traffic":[115],"data.":[116],"proposed":[118],"federated":[119],"system,":[122],"implemented":[123],"evaluated":[125],"testbed,":[128],"demonstrates":[129],"effectiveness":[131],"in":[132],"accurately":[133],"identifying":[134],"network":[135],"attacks.":[136],"communication":[138],"overhead":[139],"reduced":[141],"significantly":[142],"achieving":[144],"comparable":[145],"performance":[146],"method.":[150]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-03-25T00:00:00"}