{"id":"https://openalex.org/W4285210148","doi":"https://doi.org/10.1109/tvt.2022.3174735","title":"Traffic Anomaly Detection Using Deep Semi-Supervised Learning at the Mobile Edge","display_name":"Traffic Anomaly Detection Using Deep Semi-Supervised Learning at the Mobile Edge","publication_year":2022,"publication_date":"2022-05-12","ids":{"openalex":"https://openalex.org/W4285210148","doi":"https://doi.org/10.1109/tvt.2022.3174735"},"language":"en","primary_location":{"id":"doi:10.1109/tvt.2022.3174735","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tvt.2022.3174735","pdf_url":null,"source":{"id":"https://openalex.org/S10936095","display_name":"IEEE Transactions on Vehicular Technology","issn_l":"0018-9545","issn":["0018-9545","1939-9359"],"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 Vehicular Technology","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://zenodo.org/record/7334222","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5060884356","display_name":"Annalisa Pelati","orcid":null},"institutions":[{"id":"https://openalex.org/I177477856","display_name":"Polytechnic University of Turin","ror":"https://ror.org/00bgk9508","country_code":"IT","type":"education","lineage":["https://openalex.org/I177477856"]}],"countries":["IT"],"is_corresponding":true,"raw_author_name":"Annalisa Pelati","raw_affiliation_strings":["Department of Electronics and Telecommunications, Politecnico di Torino, Torino, Italy"],"affiliations":[{"raw_affiliation_string":"Department of Electronics and Telecommunications, Politecnico di Torino, Torino, Italy","institution_ids":["https://openalex.org/I177477856"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065722419","display_name":"Michela Meo","orcid":"https://orcid.org/0000-0001-7403-6266"},"institutions":[{"id":"https://openalex.org/I177477856","display_name":"Polytechnic University of Turin","ror":"https://ror.org/00bgk9508","country_code":"IT","type":"education","lineage":["https://openalex.org/I177477856"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Michela Meo","raw_affiliation_strings":["Department of Electronics and Telecommunications, Politecnico di Torino, Torino, Italy"],"affiliations":[{"raw_affiliation_string":"Department of Electronics and Telecommunications, Politecnico di Torino, Torino, Italy","institution_ids":["https://openalex.org/I177477856"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5055526140","display_name":"Paolo Dini","orcid":"https://orcid.org/0000-0001-6756-0289"},"institutions":[{"id":"https://openalex.org/I177477856","display_name":"Polytechnic University of Turin","ror":"https://ror.org/00bgk9508","country_code":"IT","type":"education","lineage":["https://openalex.org/I177477856"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Paolo Dini","raw_affiliation_strings":["Centre Tecnològic de Telecomunicacions de Catalunya (CTTC/CERCA), Politecnico di Torino, Torino, Italy"],"affiliations":[{"raw_affiliation_string":"Centre Tecnològic de Telecomunicacions de Catalunya (CTTC/CERCA), Politecnico di Torino, Torino, Italy","institution_ids":["https://openalex.org/I177477856"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5060884356"],"corresponding_institution_ids":["https://openalex.org/I177477856"],"apc_list":null,"apc_paid":null,"fwci":2.0699,"has_fulltext":true,"cited_by_count":16,"citation_normalized_percentile":{"value":0.88696331,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"71","issue":"8","first_page":"8919","last_page":"8932"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":1.0,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":1.0,"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/T10400","display_name":"Network Security and Intrusion Detection","score":0.9991999864578247,"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":0.9970999956130981,"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/anomaly-detection","display_name":"Anomaly detection","score":0.756522536277771},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.75409996509552},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.7079905867576599},{"id":"https://openalex.org/keywords/crowds","display_name":"Crowds","score":0.614725649356842},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5959829092025757},{"id":"https://openalex.org/keywords/recurrent-neural-network","display_name":"Recurrent neural network","score":0.5810444951057434},{"id":"https://openalex.org/keywords/handover","display_name":"Handover","score":0.5735146403312683},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5114878416061401},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.5004799365997314},{"id":"https://openalex.org/keywords/telecommunications-link","display_name":"Telecommunications link","score":0.4855653941631317},{"id":"https://openalex.org/keywords/anomaly","display_name":"Anomaly (physics)","score":0.4721534252166748},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.470237672328949},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.4542378783226013},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4322136342525482},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.3804309368133545},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3637779951095581},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.22960826754570007},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.09710648655891418}],"concepts":[{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.756522536277771},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.75409996509552},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.7079905867576599},{"id":"https://openalex.org/C2777852691","wikidata":"https://www.wikidata.org/wiki/Q13430821","display_name":"Crowds","level":2,"score":0.614725649356842},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5959829092025757},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.5810444951057434},{"id":"https://openalex.org/C111852164","wikidata":"https://www.wikidata.org/wiki/Q1414679","display_name":"Handover","level":2,"score":0.5735146403312683},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5114878416061401},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.5004799365997314},{"id":"https://openalex.org/C138660444","wikidata":"https://www.wikidata.org/wiki/Q5607897","display_name":"Telecommunications link","level":2,"score":0.4855653941631317},{"id":"https://openalex.org/C12997251","wikidata":"https://www.wikidata.org/wiki/Q567560","display_name":"Anomaly (physics)","level":2,"score":0.4721534252166748},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.470237672328949},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.4542378783226013},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4322136342525482},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3804309368133545},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3637779951095581},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.22960826754570007},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.09710648655891418},{"id":"https://openalex.org/C26873012","wikidata":"https://www.wikidata.org/wiki/Q214781","display_name":"Condensed matter physics","level":1,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tvt.2022.3174735","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tvt.2022.3174735","pdf_url":null,"source":{"id":"https://openalex.org/S10936095","display_name":"IEEE Transactions on Vehicular Technology","issn_l":"0018-9545","issn":["0018-9545","1939-9359"],"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 Vehicular Technology","raw_type":"journal-article"},{"id":"pmh:oai:zenodo.org:7334222","is_oa":true,"landing_page_url":"https://zenodo.org/record/7334222","pdf_url":"https://zenodo.org/record/7334222","source":{"id":"https://openalex.org/S4306400562","display_name":"Zenodo (CERN European Organization for Nuclear Research)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I67311998","host_organization_name":"European Organization for Nuclear Research","host_organization_lineage":["https://openalex.org/I67311998"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Trans. Veh. Technol. 71(8) 8919 - 8932","raw_type":"info:eu-repo/semantics/article"}],"best_oa_location":{"id":"pmh:oai:zenodo.org:7334222","is_oa":true,"landing_page_url":"https://zenodo.org/record/7334222","pdf_url":"https://zenodo.org/record/7334222","source":{"id":"https://openalex.org/S4306400562","display_name":"Zenodo (CERN European Organization for Nuclear Research)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I67311998","host_organization_name":"European Organization for Nuclear Research","host_organization_lineage":["https://openalex.org/I67311998"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Trans. Veh. Technol. 71(8) 8919 - 8932","raw_type":"info:eu-repo/semantics/article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","score":0.8299999833106995,"display_name":"Sustainable cities and communities"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4285210148.pdf","grobid_xml":"https://content.openalex.org/works/W4285210148.grobid-xml"},"referenced_works_count":46,"referenced_works":["https://openalex.org/W1946238955","https://openalex.org/W2115026336","https://openalex.org/W2122646361","https://openalex.org/W2189625117","https://openalex.org/W2281611560","https://openalex.org/W2412816217","https://openalex.org/W2535642622","https://openalex.org/W2562947506","https://openalex.org/W2571254578","https://openalex.org/W2579086357","https://openalex.org/W2756489700","https://openalex.org/W2787753888","https://openalex.org/W2795138333","https://openalex.org/W2886490782","https://openalex.org/W2887051675","https://openalex.org/W2890707978","https://openalex.org/W2892375480","https://openalex.org/W2898622970","https://openalex.org/W2903500163","https://openalex.org/W2910068345","https://openalex.org/W2911526229","https://openalex.org/W2942521752","https://openalex.org/W2962883549","https://openalex.org/W2963035276","https://openalex.org/W2971381425","https://openalex.org/W2974594474","https://openalex.org/W2980602384","https://openalex.org/W3007075806","https://openalex.org/W3007395614","https://openalex.org/W3019688365","https://openalex.org/W3038397330","https://openalex.org/W3048942180","https://openalex.org/W3190673667","https://openalex.org/W3195632635","https://openalex.org/W3206937771","https://openalex.org/W3207006537","https://openalex.org/W4206755733","https://openalex.org/W4241996101","https://openalex.org/W4295011194","https://openalex.org/W6677088747","https://openalex.org/W6682845405","https://openalex.org/W6686980507","https://openalex.org/W6732475852","https://openalex.org/W6754784373","https://openalex.org/W6756184183","https://openalex.org/W6758101687"],"related_works":["https://openalex.org/W4240200267","https://openalex.org/W1511510665","https://openalex.org/W1524661185","https://openalex.org/W2078823605","https://openalex.org/W2500095415","https://openalex.org/W4233026749","https://openalex.org/W2282342021","https://openalex.org/W2097922264","https://openalex.org/W4248106174","https://openalex.org/W627242580"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"we":[3],"design":[4],"an":[5,73,78],"Anomaly":[6],"Detection":[7],"(AD)":[8],"framework":[9,90,137,148],"for":[10],"mobile":[11],"data":[12],"traffic,":[13],"capable":[14],"of":[15,19,42,54,72,119,122,134,157],"identifying":[16],"different":[17,43],"types":[18],"anomalous":[20,150],"events":[21],"generated":[22],"by":[23],"flash":[24],"crowds":[25],"in":[26,82,86],"metropolitan":[27],"areas.":[28],"We":[29],"state":[30],"the":[31,39,51,64,120,123,131,146],"problem":[32],"using":[33],"a":[34],"semi-supervised":[35],"approach":[36],"and":[37,102,111,116,143,155],"exploit":[38],"great":[40],"performance":[41,133],"Recurrent":[44],"Neural":[45],"Network":[46],"(RNN)":[47],"models":[48],"to":[49,93,98,109,139],"learn":[50],"temporal":[52],"context":[53],"input":[55],"sequences.":[56],"Our":[57],"proposal":[58],"processes":[59],"real":[60],"traffic":[61],"traces":[62],"from":[63],"unencrypted":[65],"LTE":[66],"Physical":[67],"Downlink":[68],"Control":[69],"Channel":[70],"(PDCCH)":[71],"operative":[74],"network,":[75],"gathered":[76],"during":[77],"extensive":[79],"measurement":[80],"campaign":[81],"two":[83],"major":[84],"cities":[85],"Spain.":[87],"The":[88],"AD":[89,136,141],"is":[91],"designed":[92],"perform:":[94],"i)":[95],"a-posteriori":[96],"analysis":[97,108],"understand":[99],"users\u2019":[100],"behavior":[101],"urban":[103,114],"environment":[104],"variations;":[105],"ii)":[106],"real-time":[107],"automatically":[110],"on-the-fly":[112],"alert":[113],"anomalies;":[115],"iii)":[117],"estimation":[118],"duration":[121],"periods":[124],"identified":[125],"as":[126],"anomalous.":[127],"Numerical":[128],"results":[129],"show":[130],"higher":[132],"our":[135],"compared":[138],"classic":[140],"algorithms":[142],"confirm":[144],"that":[145],"proposed":[147],"predicts":[149],"behaviours":[151],"with":[152],"high":[153],"accuracy":[154],"regardless":[156],"their":[158],"cause.":[159]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":1}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}