{"id":"https://openalex.org/W2911921818","doi":"https://doi.org/10.1109/jiot.2019.2897063","title":"System Statistics Learning-Based IoT Security: Feasibility and Suitability","display_name":"System Statistics Learning-Based IoT Security: Feasibility and Suitability","publication_year":2019,"publication_date":"2019-02-05","ids":{"openalex":"https://openalex.org/W2911921818","doi":"https://doi.org/10.1109/jiot.2019.2897063","mag":"2911921818"},"language":"en","primary_location":{"id":"doi:10.1109/jiot.2019.2897063","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jiot.2019.2897063","pdf_url":null,"source":{"id":"https://openalex.org/S2480266640","display_name":"IEEE Internet of Things Journal","issn_l":"2327-4662","issn":["2327-4662","2372-2541"],"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 Internet of Things Journal","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5024397951","display_name":"Fangyu Li","orcid":"https://orcid.org/0000-0003-2340-3622"},"institutions":[{"id":"https://openalex.org/I165733156","display_name":"University of Georgia","ror":"https://ror.org/00te3t702","country_code":"US","type":"education","lineage":["https://openalex.org/I165733156"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Fangyu Li","raw_affiliation_strings":["Center for Cyber-Physical Systems, University of Georgia, Athens, GA, USA"],"raw_orcid":"https://orcid.org/0000-0003-2340-3622","affiliations":[{"raw_affiliation_string":"Center for Cyber-Physical Systems, University of Georgia, Athens, GA, USA","institution_ids":["https://openalex.org/I165733156"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5063539255","display_name":"Aditya Shinde","orcid":"https://orcid.org/0000-0002-7926-9365"},"institutions":[{"id":"https://openalex.org/I165733156","display_name":"University of Georgia","ror":"https://ror.org/00te3t702","country_code":"US","type":"education","lineage":["https://openalex.org/I165733156"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Aditya Shinde","raw_affiliation_strings":["Center for Cyber-Physical Systems, University of Georgia, Athens, GA, USA"],"raw_orcid":"https://orcid.org/0000-0002-7926-9365","affiliations":[{"raw_affiliation_string":"Center for Cyber-Physical Systems, University of Georgia, Athens, GA, USA","institution_ids":["https://openalex.org/I165733156"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069526885","display_name":"Yang Shi","orcid":"https://orcid.org/0000-0001-6486-4340"},"institutions":[{"id":"https://openalex.org/I165733156","display_name":"University of Georgia","ror":"https://ror.org/00te3t702","country_code":"US","type":"education","lineage":["https://openalex.org/I165733156"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yang Shi","raw_affiliation_strings":["Center for Cyber-Physical Systems, University of Georgia, Athens, GA, USA"],"raw_orcid":"https://orcid.org/0000-0001-6486-4340","affiliations":[{"raw_affiliation_string":"Center for Cyber-Physical Systems, University of Georgia, Athens, GA, USA","institution_ids":["https://openalex.org/I165733156"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100447775","display_name":"Jin Ye","orcid":"https://orcid.org/0000-0001-7756-5104"},"institutions":[{"id":"https://openalex.org/I165733156","display_name":"University of Georgia","ror":"https://ror.org/00te3t702","country_code":"US","type":"education","lineage":["https://openalex.org/I165733156"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jin Ye","raw_affiliation_strings":["Center for Cyber-Physical Systems, University of Georgia, Athens, GA, USA"],"raw_orcid":"https://orcid.org/0000-0001-7756-5104","affiliations":[{"raw_affiliation_string":"Center for Cyber-Physical Systems, University of Georgia, Athens, GA, USA","institution_ids":["https://openalex.org/I165733156"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100341802","display_name":"Xiang\u2010Yang Li","orcid":"https://orcid.org/0000-0002-6070-6625"},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiang-Yang Li","raw_affiliation_strings":["School of Computer Science, University of Science and Technology of China, Hefei, China"],"raw_orcid":"https://orcid.org/0000-0002-6070-6625","affiliations":[{"raw_affiliation_string":"School of Computer Science, University of Science and Technology of China, Hefei, China","institution_ids":["https://openalex.org/I126520041"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5007530002","display_name":"Wen\u2010Zhan Song","orcid":"https://orcid.org/0000-0001-8174-1772"},"institutions":[{"id":"https://openalex.org/I165733156","display_name":"University of Georgia","ror":"https://ror.org/00te3t702","country_code":"US","type":"education","lineage":["https://openalex.org/I165733156"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Wenzhan Song","raw_affiliation_strings":["Center for Cyber-Physical Systems, University of Georgia, Athens, GA, USA"],"raw_orcid":"https://orcid.org/0000-0001-8174-1772","affiliations":[{"raw_affiliation_string":"Center for Cyber-Physical Systems, University of Georgia, Athens, GA, USA","institution_ids":["https://openalex.org/I165733156"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":9.3185,"has_fulltext":false,"cited_by_count":105,"citation_normalized_percentile":{"value":0.98257215,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":"6","issue":"4","first_page":"6396","last_page":"6403"},"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/T11241","display_name":"Advanced Malware Detection Techniques","score":0.9976000189781189,"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/computer-science","display_name":"Computer science","score":0.8749476671218872},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.6855655312538147},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.5856758952140808},{"id":"https://openalex.org/keywords/thresholding","display_name":"Thresholding","score":0.5129937529563904},{"id":"https://openalex.org/keywords/local-outlier-factor","display_name":"Local outlier factor","score":0.49910449981689453},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.4902058243751526},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.46838003396987915},{"id":"https://openalex.org/keywords/outlier","display_name":"Outlier","score":0.4327229857444763},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.41919443011283875},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.39038392901420593},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.36841967701911926},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.10537528991699219},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.10180819034576416}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8749476671218872},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.6855655312538147},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.5856758952140808},{"id":"https://openalex.org/C191178318","wikidata":"https://www.wikidata.org/wiki/Q2256906","display_name":"Thresholding","level":3,"score":0.5129937529563904},{"id":"https://openalex.org/C169029474","wikidata":"https://www.wikidata.org/wiki/Q387942","display_name":"Local outlier factor","level":3,"score":0.49910449981689453},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.4902058243751526},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.46838003396987915},{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.4327229857444763},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.41919443011283875},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.39038392901420593},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.36841967701911926},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.10537528991699219},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.10180819034576416}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/jiot.2019.2897063","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jiot.2019.2897063","pdf_url":null,"source":{"id":"https://openalex.org/S2480266640","display_name":"IEEE Internet of Things Journal","issn_l":"2327-4662","issn":["2327-4662","2372-2541"],"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 Internet of Things Journal","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Responsible consumption and production","score":0.4000000059604645,"id":"https://metadata.un.org/sdg/12"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":37,"referenced_works":["https://openalex.org/W1559384589","https://openalex.org/W1576185228","https://openalex.org/W1645615506","https://openalex.org/W1815076433","https://openalex.org/W1964274671","https://openalex.org/W1971167072","https://openalex.org/W1971673042","https://openalex.org/W1976262362","https://openalex.org/W2004235835","https://openalex.org/W2007087405","https://openalex.org/W2025743285","https://openalex.org/W2096974968","https://openalex.org/W2103188731","https://openalex.org/W2124280970","https://openalex.org/W2128038346","https://openalex.org/W2135039490","https://openalex.org/W2136992183","https://openalex.org/W2142100695","https://openalex.org/W2144182447","https://openalex.org/W2264016719","https://openalex.org/W2271840356","https://openalex.org/W2289218694","https://openalex.org/W2493493073","https://openalex.org/W2581511846","https://openalex.org/W2730842245","https://openalex.org/W2764129961","https://openalex.org/W2786027963","https://openalex.org/W2794563095","https://openalex.org/W2885012953","https://openalex.org/W2896463081","https://openalex.org/W2963344707","https://openalex.org/W2963467342","https://openalex.org/W2963608065","https://openalex.org/W4289743351","https://openalex.org/W6638545294","https://openalex.org/W6675325168","https://openalex.org/W6694517276"],"related_works":["https://openalex.org/W2499612753","https://openalex.org/W2770832849","https://openalex.org/W3111802945","https://openalex.org/W114119537","https://openalex.org/W2912112202","https://openalex.org/W4240627425","https://openalex.org/W2761705761","https://openalex.org/W205872183","https://openalex.org/W2019014808","https://openalex.org/W2946096271"],"abstract_inverted_index":{"Cyber":[0],"attacks":[1],"and":[2,30,59,77,107,122,155,195],"malfunctions":[3],"challenge":[4],"the":[5,37,46,74,83,102,125,134,156,161,177],"wide":[6],"applications":[7],"of":[8,10,36],"Internet":[9],"Things":[11],"(IoT).":[12],"Since":[13],"they":[14],"are":[15,189],"generally":[16],"designed":[17,49],"as":[18,80,87,149,174,176],"embedded":[19],"systems,":[20],"typical":[21],"auto-sustainable":[22,127],"IoT":[23,98,110,128,193],"devices":[24],"usually":[25],"have":[26],"a":[27,31,196],"limited":[28,38],"capacity":[29],"low":[32],"processing":[33],"power.":[34],"Because":[35,82],"computation":[39,178],"resources,":[40],"it":[41],"is":[42,105,201],"difficult":[43],"to":[44,67,72,118],"apply":[45],"traditional":[47],"techniques":[48],"for":[50,192],"personal":[51],"computers":[52],"or":[53],"super":[54],"computers,":[55],"like":[56],"traffic":[57],"analyzers":[58],"antivirus":[60],"software.":[61],"In":[62],"this":[63],"paper,":[64],"we":[65,112,181],"propose":[66],"leverage":[68],"statistical":[69],"learning":[70,116,187],"methods":[71],"characterize":[73],"device":[75],"behavior":[76],"flag":[78],"deviations":[79],"anomalies.":[81],"system":[84,136],"statistics,":[85],"such":[86,148],"CPU":[88],"usage":[89],"cycles,":[90],"disk":[91],"usage,":[92],"etc.,":[93],"can":[94,138,164],"be":[95,139,165],"obtained":[96],"by":[97],"application":[99],"program":[100],"interfaces,":[101],"proposed":[103,157],"framework":[104],"platform":[106],"deviceindependent.":[108],"Considering":[109],"applications,":[111],"train":[113],"multiple":[114],"machine":[115,186],"models":[117,188],"evaluate":[119],"their":[120,169],"feasibility":[121],"suitability.":[123],"For":[124],"target":[126],"devices,":[129],"which":[130],"operate":[131],"well-planned":[132],"processes,":[133],"normal":[135],"performances":[137,170],"modeled":[140],"accurately.":[141],"Based":[142],"on":[143,171],"time":[144],"series":[145],"analysis":[146],"methods,":[147],"local":[150],"outlier":[151],"factor,":[152],"cumulative":[153],"sum,":[154],"adaptive":[158],"online":[159],"thresholding,":[160],"anomalous":[162],"behaviors":[163],"effectively":[166],"detected.":[167],"Comparing":[168],"detecting":[172],"anomalies":[173],"well":[175],"sources":[179],"required,":[180],"conclude":[182],"that":[183],"relatively":[184],"simple":[185],"more":[190],"suitable":[191],"security,":[194],"data-driven":[197],"anomaly":[198],"detection":[199],"method":[200],"preferred.":[202]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":10},{"year":2024,"cited_by_count":11},{"year":2023,"cited_by_count":14},{"year":2022,"cited_by_count":21},{"year":2021,"cited_by_count":19},{"year":2020,"cited_by_count":18},{"year":2019,"cited_by_count":8},{"year":2018,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
