{"id":"https://openalex.org/W4388925691","doi":"https://doi.org/10.1145/3605758.3623492","title":"Granular IoT Device Identification Using TF-IDF and Cosine Similarity","display_name":"Granular IoT Device Identification Using TF-IDF and Cosine Similarity","publication_year":2023,"publication_date":"2023-11-23","ids":{"openalex":"https://openalex.org/W4388925691","doi":"https://doi.org/10.1145/3605758.3623492"},"language":"en","primary_location":{"id":"doi:10.1145/3605758.3623492","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3605758.3623492","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3605758.3623492","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 5th Workshop on CPS&IoT Security and Privacy","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3605758.3623492","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5065826523","display_name":"Ashley Andrews","orcid":"https://orcid.org/0000-0001-8657-3448"},"institutions":[{"id":"https://openalex.org/I36234482","display_name":"University of Bristol","ror":"https://ror.org/0524sp257","country_code":"GB","type":"education","lineage":["https://openalex.org/I36234482"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Ashley Andrews","raw_affiliation_strings":["University of Bristol, Bristol, United Kingdom"],"raw_orcid":"https://orcid.org/0000-0001-8657-3448","affiliations":[{"raw_affiliation_string":"University of Bristol, Bristol, United Kingdom","institution_ids":["https://openalex.org/I36234482"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072981915","display_name":"George Oikonomou","orcid":"https://orcid.org/0000-0002-1684-6989"},"institutions":[{"id":"https://openalex.org/I36234482","display_name":"University of Bristol","ror":"https://ror.org/0524sp257","country_code":"GB","type":"education","lineage":["https://openalex.org/I36234482"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"George Oikonomou","raw_affiliation_strings":["University of Bristol, Bristol, United Kingdom"],"raw_orcid":"https://orcid.org/0000-0002-1684-6989","affiliations":[{"raw_affiliation_string":"University of Bristol, Bristol, United Kingdom","institution_ids":["https://openalex.org/I36234482"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5082279856","display_name":"Simon Armour","orcid":"https://orcid.org/0009-0008-6319-9789"},"institutions":[{"id":"https://openalex.org/I36234482","display_name":"University of Bristol","ror":"https://ror.org/0524sp257","country_code":"GB","type":"education","lineage":["https://openalex.org/I36234482"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Simon Armour","raw_affiliation_strings":["University of Bristol, Bristol, United Kingdom"],"raw_orcid":"https://orcid.org/0009-0008-6319-9789","affiliations":[{"raw_affiliation_string":"University of Bristol, Bristol, United Kingdom","institution_ids":["https://openalex.org/I36234482"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103210919","display_name":"Paul Thomas","orcid":null},"institutions":[{"id":"https://openalex.org/I36234482","display_name":"University of Bristol","ror":"https://ror.org/0524sp257","country_code":"GB","type":"education","lineage":["https://openalex.org/I36234482"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Paul Thomas","raw_affiliation_strings":["University of Bristol, Bristol, United Kingdom"],"raw_orcid":"https://orcid.org/0009-0003-5538-0338","affiliations":[{"raw_affiliation_string":"University of Bristol, Bristol, United Kingdom","institution_ids":["https://openalex.org/I36234482"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5038672273","display_name":"Thomas Cattermole","orcid":"https://orcid.org/0009-0001-2069-4922"},"institutions":[{"id":"https://openalex.org/I45129253","display_name":"University College London","ror":"https://ror.org/02jx3x895","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I45129253"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Thomas Cattermole","raw_affiliation_strings":["University College London, London, United Kingdom"],"raw_orcid":"https://orcid.org/0009-0001-2069-4922","affiliations":[{"raw_affiliation_string":"University College London, London, United Kingdom","institution_ids":["https://openalex.org/I45129253"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5065826523"],"corresponding_institution_ids":["https://openalex.org/I36234482"],"apc_list":null,"apc_paid":null,"fwci":0.852,"has_fulltext":true,"cited_by_count":5,"citation_normalized_percentile":{"value":0.79403757,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"91","last_page":"99"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11598","display_name":"Internet Traffic Analysis and Secure E-voting","score":0.9998999834060669,"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/T11598","display_name":"Internet Traffic Analysis and Secure E-voting","score":0.9998999834060669,"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":0.9998000264167786,"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/T11241","display_name":"Advanced Malware Detection Techniques","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/firmware","display_name":"Firmware","score":0.9091328382492065},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.856225848197937},{"id":"https://openalex.org/keywords/cosine-similarity","display_name":"Cosine similarity","score":0.6977096796035767},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.6785928010940552},{"id":"https://openalex.org/keywords/granularity","display_name":"Granularity","score":0.6504524946212769},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.5728760957717896},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.5636301040649414},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.47804123163223267},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4734860360622406},{"id":"https://openalex.org/keywords/encryption","display_name":"Encryption","score":0.4126940369606018},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.35143646597862244},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.32668519020080566},{"id":"https://openalex.org/keywords/computer-hardware","display_name":"Computer hardware","score":0.15101459622383118},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.09282076358795166},{"id":"https://openalex.org/keywords/operating-system","display_name":"Operating system","score":0.09020954370498657}],"concepts":[{"id":"https://openalex.org/C67212190","wikidata":"https://www.wikidata.org/wiki/Q104851","display_name":"Firmware","level":2,"score":0.9091328382492065},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.856225848197937},{"id":"https://openalex.org/C2780762811","wikidata":"https://www.wikidata.org/wiki/Q1784941","display_name":"Cosine similarity","level":3,"score":0.6977096796035767},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.6785928010940552},{"id":"https://openalex.org/C177774035","wikidata":"https://www.wikidata.org/wiki/Q1246948","display_name":"Granularity","level":2,"score":0.6504524946212769},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.5728760957717896},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.5636301040649414},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.47804123163223267},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4734860360622406},{"id":"https://openalex.org/C148730421","wikidata":"https://www.wikidata.org/wiki/Q141090","display_name":"Encryption","level":2,"score":0.4126940369606018},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.35143646597862244},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.32668519020080566},{"id":"https://openalex.org/C9390403","wikidata":"https://www.wikidata.org/wiki/Q3966","display_name":"Computer hardware","level":1,"score":0.15101459622383118},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.09282076358795166},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.09020954370498657},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1145/3605758.3623492","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3605758.3623492","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3605758.3623492","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 5th Workshop on CPS&IoT Security and Privacy","raw_type":"proceedings-article"},{"id":"pmh:oai:research-information.bris.ac.uk:openaire/b7127db3-ae18-4786-b076-3005c8eb5323","is_oa":true,"landing_page_url":"https://hdl.handle.net/1983/b7127db3-ae18-4786-b076-3005c8eb5323","pdf_url":null,"source":{"id":"https://openalex.org/S7407055359","display_name":"Explore Bristol Research","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"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":"Andrews, A, Oikonomou, G, Armour, S M D, Thomas, P & Cattermole, T 2023, Granular IoT Device Identification Using TF-IDF and Cosine Similarity. in CPSIoTSec '23 : Proceedings of the 5th Workshop on CPS &IoT Security and Privacy. Association for Computing Machinery, pp. 91-99. https://doi.org/10.1145/3605758.3623492","raw_type":"contributionToPeriodical"},{"id":"pmh:oai:research-information.bris.ac.uk:openaire_cris_publications/b7127db3-ae18-4786-b076-3005c8eb5323","is_oa":true,"landing_page_url":"https://research-information.bris.ac.uk/en/publications/b7127db3-ae18-4786-b076-3005c8eb5323","pdf_url":null,"source":{"id":"https://openalex.org/S7407055359","display_name":"Explore Bristol Research","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"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":"Andrews, A, Oikonomou, G, Armour, S M D, Thomas, P & Cattermole, T 2023, Granular IoT Device Identification Using TF-IDF and Cosine Similarity. in CPSIoTSec '23 : Proceedings of the 5th Workshop on CPS &IoT Security and Privacy. Association for Computing Machinery, pp. 91-99. https://doi.org/10.1145/3605758.3623492","raw_type":"contributionToPeriodical"}],"best_oa_location":{"id":"doi:10.1145/3605758.3623492","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3605758.3623492","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3605758.3623492","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 5th Workshop on CPS&IoT Security and Privacy","raw_type":"proceedings-article"},"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","score":0.44999998807907104,"id":"https://metadata.un.org/sdg/9"}],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4388925691.pdf","grobid_xml":"https://content.openalex.org/works/W4388925691.grobid-xml"},"referenced_works_count":19,"referenced_works":["https://openalex.org/W2147268071","https://openalex.org/W2511541902","https://openalex.org/W2574448563","https://openalex.org/W2735618023","https://openalex.org/W2793255524","https://openalex.org/W2805626176","https://openalex.org/W2888505697","https://openalex.org/W2892074796","https://openalex.org/W2967495102","https://openalex.org/W2967569942","https://openalex.org/W2970180303","https://openalex.org/W3005645561","https://openalex.org/W3015181824","https://openalex.org/W3041550943","https://openalex.org/W3043781642","https://openalex.org/W3096391524","https://openalex.org/W3198964211","https://openalex.org/W4234256248","https://openalex.org/W4324267469"],"related_works":["https://openalex.org/W2389818373","https://openalex.org/W2220831889","https://openalex.org/W4312683641","https://openalex.org/W3027421045","https://openalex.org/W2576320324","https://openalex.org/W2980386803","https://openalex.org/W3215994059","https://openalex.org/W2319823519","https://openalex.org/W4206798987","https://openalex.org/W2801158176"],"abstract_inverted_index":{"Internet":[0],"of":[1,51,131,189,207,243,250,259],"things":[2],"(IoT)":[3],"devices":[4,30,46,63,133,184,224],"are":[5,13,142,198],"becoming":[6],"more":[7],"prevalent":[8],"in":[9,75,145],"home":[10],"environments":[11],"and":[12,106,110,121,173,212,214],"shown":[14],"to":[15,26,43,48,60,87,95,117,181,186,201,222,226,232,236,247],"be":[16,72,81,151,164],"generally":[17],"insecure.":[18],"There":[19],"have":[20,58],"been":[21],"many":[22],"previous":[23,56],"studies":[24,57],"looking":[25],"identify":[27,44,182,223],"unknown":[28,45],"IoT":[29,183],"on":[31],"networks.":[32],"To":[33],"truly":[34],"secure":[35],"a":[36,41,54,84,168,205,227],"network":[37,108],"however,":[38],"there":[39,70,141],"is":[40,67],"need":[42],"down":[47,185,225,235],"the":[49,76,119,146,178,187,216,248],"granularity":[50,234],"firmware":[52,190,228],"version;":[53],"problem":[55],"failed":[59],"solve.":[61],"As":[62],"change":[64],"versions,":[65,213],"it":[66],"expected":[68],"that":[69,79,123,140,149,160,176,194],"would":[71,80],"subtle":[73],"differences":[74],"on-wire":[77],"signatures":[78],"hard":[82],"for":[83,91],"human":[85],"analyst":[86],"notice,":[88],"but":[89],"easy":[90],"an":[92,241,257],"NLP":[93],"technique":[94,170],"identify.":[96],"In":[97],"this":[98],"paper":[99],"we":[100,255],"extract":[101],"keywords":[102,148],"from":[103],"both":[104],"encrypted":[105],"unencrypted":[107],"traffic":[109],"first":[111],"use":[112],"UMAP":[113],"with":[114],"K-Means":[115],"clustering":[116,179],"visualise":[118],"data":[120],"show":[122,159,193],"natural":[124],"clusters":[125],"form":[126],"across":[127,204],"our":[128,195],"test":[129],"dataset":[130],"18":[132],"covering":[134],"61":[135],"versions.":[136],"This":[137,230],"analysis":[138],"suggests":[139],"underlying":[143],"patterns":[144,162],"extracted":[147],"could":[150],"detected":[152,165],"by":[153,166],"machine":[154],"learning":[155],"techniques.":[156],"We":[157,192],"then":[158],"these":[161],"can":[163],"proposing":[167],"novel":[169],"using":[171],"TF-IDF":[172],"cosine":[174],"similarity":[175],"follows":[177],"results":[180],"level":[188,239],"version.":[191,229],"chosen":[196],"features":[197],"strong":[199],"enough":[200],"work":[202],"accurately":[203],"range":[206],"device":[208,237,252],"types,":[209],"manufacturers,":[210],"models":[211],"note":[215],"main":[217],"observations":[218],"found":[219],"when":[220],"trying":[221],"approach":[231],"get":[233],"version":[238],"achieves":[240],"accuracy":[242,258],"67%":[244],"without":[245],"being":[246],"detriment":[249],"identifying":[251],"models,":[253],"where":[254],"achieve":[256],"90%.":[260]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":4}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}