{"id":"https://openalex.org/W2955457458","doi":"https://doi.org/10.12720/jcm.14.6.455-462","title":"An Outlier Detection Method to Improve Gathered Datasets for Network Behavior Analysis in IoT","display_name":"An Outlier Detection Method to Improve Gathered Datasets for Network Behavior Analysis in IoT","publication_year":2019,"publication_date":"2019-01-01","ids":{"openalex":"https://openalex.org/W2955457458","doi":"https://doi.org/10.12720/jcm.14.6.455-462","mag":"2955457458"},"language":"en","primary_location":{"id":"doi:10.12720/jcm.14.6.455-462","is_oa":false,"landing_page_url":"https://doi.org/10.12720/jcm.14.6.455-462","pdf_url":null,"source":{"id":"https://openalex.org/S184821498","display_name":"Journal of Communications","issn_l":"1796-2021","issn":["1796-2021","2374-4367"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4323867253","host_organization_name":"International Communication Association","host_organization_lineage":["https://openalex.org/P4323867253"],"host_organization_lineage_names":["International Communication Association"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Communications","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"http://hdl.handle.net/11250/2631794","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5074194994","display_name":"Amin Shahraki","orcid":"https://orcid.org/0000-0002-5065-9968"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Amin Shahraki","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5052823918","display_name":"\u00d8ystein Haugen","orcid":"https://orcid.org/0000-0002-0567-769X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"\u00d8ystein Haugen","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5074194994"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.6802,"has_fulltext":false,"cited_by_count":20,"citation_normalized_percentile":{"value":0.88259916,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"455","last_page":"462"},"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":0.9998999834060669,"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/T10064","display_name":"Complex Network Analysis Techniques","score":0.9958000183105469,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7940566539764404},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.7577530145645142},{"id":"https://openalex.org/keywords/outlier","display_name":"Outlier","score":0.5949820280075073},{"id":"https://openalex.org/keywords/internet-of-things","display_name":"Internet of Things","score":0.49355757236480713},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.48272988200187683},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4490608870983124},{"id":"https://openalex.org/keywords/network-analysis","display_name":"Network analysis","score":0.4256565272808075},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.40895384550094604},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.17476198077201843}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7940566539764404},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.7577530145645142},{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.5949820280075073},{"id":"https://openalex.org/C81860439","wikidata":"https://www.wikidata.org/wiki/Q251212","display_name":"Internet of Things","level":2,"score":0.49355757236480713},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.48272988200187683},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4490608870983124},{"id":"https://openalex.org/C32946077","wikidata":"https://www.wikidata.org/wiki/Q618079","display_name":"Network analysis","level":2,"score":0.4256565272808075},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.40895384550094604},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.17476198077201843},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.12720/jcm.14.6.455-462","is_oa":false,"landing_page_url":"https://doi.org/10.12720/jcm.14.6.455-462","pdf_url":null,"source":{"id":"https://openalex.org/S184821498","display_name":"Journal of Communications","issn_l":"1796-2021","issn":["1796-2021","2374-4367"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4323867253","host_organization_name":"International Communication Association","host_organization_lineage":["https://openalex.org/P4323867253"],"host_organization_lineage_names":["International Communication Association"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Communications","raw_type":"journal-article"},{"id":"pmh:oai:hiof.brage.unit.no:11250/2631794","is_oa":true,"landing_page_url":"http://hdl.handle.net/11250/2631794","pdf_url":null,"source":{"id":"https://openalex.org/S4306401716","display_name":"Duo Research Archive (University of Oslo)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I184942183","host_organization_name":"University of Oslo","host_organization_lineage":["https://openalex.org/I184942183"],"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":"455-462","raw_type":"info:eu-repo/semantics/article"}],"best_oa_location":{"id":"pmh:oai:hiof.brage.unit.no:11250/2631794","is_oa":true,"landing_page_url":"http://hdl.handle.net/11250/2631794","pdf_url":null,"source":{"id":"https://openalex.org/S4306401716","display_name":"Duo Research Archive (University of Oslo)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I184942183","host_organization_name":"University of Oslo","host_organization_lineage":["https://openalex.org/I184942183"],"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":"455-462","raw_type":"info:eu-repo/semantics/article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":33,"referenced_works":["https://openalex.org/W159748277","https://openalex.org/W1552339598","https://openalex.org/W1553063632","https://openalex.org/W1965606617","https://openalex.org/W1965972569","https://openalex.org/W1974690209","https://openalex.org/W1989068596","https://openalex.org/W1989898472","https://openalex.org/W1995003166","https://openalex.org/W1995484833","https://openalex.org/W1996077475","https://openalex.org/W2011430131","https://openalex.org/W2018588330","https://openalex.org/W2026493302","https://openalex.org/W2051367110","https://openalex.org/W2060536267","https://openalex.org/W2075721911","https://openalex.org/W2087260876","https://openalex.org/W2101254347","https://openalex.org/W2122951085","https://openalex.org/W2126895435","https://openalex.org/W2148140427","https://openalex.org/W2154579873","https://openalex.org/W2155788085","https://openalex.org/W2157949690","https://openalex.org/W2158238403","https://openalex.org/W2165824180","https://openalex.org/W2337854997","https://openalex.org/W2588336250","https://openalex.org/W2737485257","https://openalex.org/W2766776039","https://openalex.org/W2963786595","https://openalex.org/W3125923948"],"related_works":["https://openalex.org/W4311097251","https://openalex.org/W2625093826","https://openalex.org/W2921026492","https://openalex.org/W3006513224","https://openalex.org/W2499612753","https://openalex.org/W3111802945","https://openalex.org/W2946096271","https://openalex.org/W2295423552","https://openalex.org/W3107369729","https://openalex.org/W2998615029"],"abstract_inverted_index":{"Outlier":[0],"detection":[1,122],"is":[2,68,87],"a":[3,46,69,79,88,118,142],"subfield":[4],"of":[5,18,106,163],"data":[6,10,26,82,125],"mining":[7],"to":[8,71,91,140],"determine":[9],"points":[11,27],"that":[12,24,102,115,145],"notably":[13],"deviate":[14,97],"from":[15],"the":[16,61,104,107,124,148,156,161,171],"rest":[17],"a\\ndataset.":[19],"Their":[20],"deviation":[21],"can":[22,96,136],"indicate":[23],"these":[25],"are":[28,40,132,160],"generated":[29],"by":[30],"errors":[31],"and":[32,74,98,158],"should":[33],"therefore":[34],"be":[35,138],"removed":[36,139],"or":[37,52,56],"repaired.":[38],"There":[39],"many":[41],"reasons":[42],"for":[43,120],"outliers":[44,131,135],"in":[45,78,84],"network":[47,93,149,177],"dataset":[48,144],"such":[49],"as":[50],"human":[51],"instrument":[53],"errors,":[54],"noise":[55],"system":[57],"behavior":[58,150],"changes.":[59],"On":[60],"other":[62],"side,":[63],"Network":[64],"Behavior":[65],"Analysis":[66],"(NBA)":[67],"way":[70,90],"monitor":[72],"traffic":[73],"recognize":[75],"unusual":[76],"actions":[77],"network.":[80],"Analyzing":[81],"trends":[83,101],"NBA":[85,108,153],"methods":[86],"common":[89],"interpret":[92],"situation.":[94],"Outliers":[95],"produce":[99],"erroneous":[100],"influence":[103],"results":[105],"methods.":[109,154],"This":[110],"paper":[111],"presents":[112],"an":[113],"approach":[114],"based":[116],"on":[117,174],"method":[119,169,173],"trend":[121],"divides":[123],"set":[126],"into":[127],"subsets":[128],"where":[129],"contextual":[130],"discovered.":[133],"The":[134],"then":[137],"have":[141],"clear":[143],"better":[146],"shows":[147],"when":[151],"using":[152],"Increasing":[155],"accuracy":[157],"reliability":[159],"goals":[162],"our":[164],"method.":[165],"We":[166],"compare":[167],"the\\nproposed":[168],"with":[170],"Hampel":[172],"simulated":[175],"IoT":[176],"data.":[178]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":6},{"year":2020,"cited_by_count":1}],"updated_date":"2026-01-13T01:12:25.745995","created_date":"2019-07-12T00:00:00"}
