{"id":"https://openalex.org/W4312480288","doi":"https://doi.org/10.1109/tase.2022.3214193","title":"Adaptive Sampling and Quick Anomaly Detection in Large Networks","display_name":"Adaptive Sampling and Quick Anomaly Detection in Large Networks","publication_year":2022,"publication_date":"2022-11-03","ids":{"openalex":"https://openalex.org/W4312480288","doi":"https://doi.org/10.1109/tase.2022.3214193"},"language":"en","primary_location":{"id":"doi:10.1109/tase.2022.3214193","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tase.2022.3214193","pdf_url":null,"source":{"id":"https://openalex.org/S34881539","display_name":"IEEE Transactions on Automation Science and Engineering","issn_l":"1545-5955","issn":["1545-5955","1558-3783"],"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 Automation Science and Engineering","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/A5030183256","display_name":"Xiaochen Xian","orcid":"https://orcid.org/0000-0001-7099-2488"},"institutions":[{"id":"https://openalex.org/I33213144","display_name":"University of Florida","ror":"https://ror.org/02y3ad647","country_code":"US","type":"education","lineage":["https://openalex.org/I33213144"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Xiaochen Xian","raw_affiliation_strings":["Department of Industrial and Systems Engineering, University of Florida, Gainesville, FL, USA"],"affiliations":[{"raw_affiliation_string":"Department of Industrial and Systems Engineering, University of Florida, Gainesville, FL, USA","institution_ids":["https://openalex.org/I33213144"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5036491276","display_name":"Alexander Semenov","orcid":"https://orcid.org/0000-0003-2691-4575"},"institutions":[{"id":"https://openalex.org/I33213144","display_name":"University of Florida","ror":"https://ror.org/02y3ad647","country_code":"US","type":"education","lineage":["https://openalex.org/I33213144"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Alexander Semenov","raw_affiliation_strings":["Department of Industrial and Systems Engineering, University of Florida, Gainesville, FL, USA"],"affiliations":[{"raw_affiliation_string":"Department of Industrial and Systems Engineering, University of Florida, Gainesville, FL, USA","institution_ids":["https://openalex.org/I33213144"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101443062","display_name":"Yaodan Hu","orcid":"https://orcid.org/0000-0003-3075-982X"},"institutions":[{"id":"https://openalex.org/I106969075","display_name":"Idaho State University","ror":"https://ror.org/0162z8b04","country_code":"US","type":"education","lineage":["https://openalex.org/I106969075"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yaodan Hu","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Idaho State University, Pocatello, ID, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Idaho State University, Pocatello, ID, USA","institution_ids":["https://openalex.org/I106969075"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100665239","display_name":"Andi Wang","orcid":"https://orcid.org/0000-0003-4925-1962"},"institutions":[{"id":"https://openalex.org/I55732556","display_name":"Arizona State University","ror":"https://ror.org/03efmqc40","country_code":"US","type":"education","lineage":["https://openalex.org/I55732556"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Andi Wang","raw_affiliation_strings":["School of Manufacturing Systems and Networks, Arizona State University, Mesa, AZ, USA"],"affiliations":[{"raw_affiliation_string":"School of Manufacturing Systems and Networks, Arizona State University, Mesa, AZ, USA","institution_ids":["https://openalex.org/I55732556"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5017464942","display_name":"Yier Jin","orcid":"https://orcid.org/0000-0002-8791-0597"},"institutions":[{"id":"https://openalex.org/I33213144","display_name":"University of Florida","ror":"https://ror.org/02y3ad647","country_code":"US","type":"education","lineage":["https://openalex.org/I33213144"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yier Jin","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Florida, Gainesville, FL, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Florida, Gainesville, FL, USA","institution_ids":["https://openalex.org/I33213144"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5030183256"],"corresponding_institution_ids":["https://openalex.org/I33213144"],"apc_list":null,"apc_paid":null,"fwci":0.928,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.79302534,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":98},"biblio":{"volume":"20","issue":"4","first_page":"2253","last_page":"2267"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9998000264167786,"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":0.9998000264167786,"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/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9962000250816345,"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"}},{"id":"https://openalex.org/T12761","display_name":"Data Stream Mining Techniques","score":0.9957000017166138,"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":0.7950718402862549},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7399675846099854},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.571459949016571},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.560642421245575},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.5465649366378784},{"id":"https://openalex.org/keywords/adaptive-sampling","display_name":"Adaptive sampling","score":0.526221752166748},{"id":"https://openalex.org/keywords/distributed-computing","display_name":"Distributed computing","score":0.4829930067062378},{"id":"https://openalex.org/keywords/node","display_name":"Node (physics)","score":0.48267295956611633},{"id":"https://openalex.org/keywords/centrality","display_name":"Centrality","score":0.48115313053131104},{"id":"https://openalex.org/keywords/network-topology","display_name":"Network topology","score":0.4752768576145172},{"id":"https://openalex.org/keywords/curse-of-dimensionality","display_name":"Curse of dimensionality","score":0.46594157814979553},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.4629894495010376},{"id":"https://openalex.org/keywords/network-monitoring","display_name":"Network monitoring","score":0.44107553362846375},{"id":"https://openalex.org/keywords/wireless-sensor-network","display_name":"Wireless sensor network","score":0.44083383679389954},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.4172188639640808},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.3443021774291992},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.21391308307647705},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.20048031210899353},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.1426784098148346}],"concepts":[{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.7950718402862549},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7399675846099854},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.571459949016571},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.560642421245575},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.5465649366378784},{"id":"https://openalex.org/C2781395549","wikidata":"https://www.wikidata.org/wiki/Q4680762","display_name":"Adaptive sampling","level":3,"score":0.526221752166748},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.4829930067062378},{"id":"https://openalex.org/C62611344","wikidata":"https://www.wikidata.org/wiki/Q1062658","display_name":"Node (physics)","level":2,"score":0.48267295956611633},{"id":"https://openalex.org/C53811970","wikidata":"https://www.wikidata.org/wiki/Q5062194","display_name":"Centrality","level":2,"score":0.48115313053131104},{"id":"https://openalex.org/C199845137","wikidata":"https://www.wikidata.org/wiki/Q145490","display_name":"Network topology","level":2,"score":0.4752768576145172},{"id":"https://openalex.org/C111030470","wikidata":"https://www.wikidata.org/wiki/Q1430460","display_name":"Curse of dimensionality","level":2,"score":0.46594157814979553},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.4629894495010376},{"id":"https://openalex.org/C81877898","wikidata":"https://www.wikidata.org/wiki/Q1965787","display_name":"Network monitoring","level":2,"score":0.44107553362846375},{"id":"https://openalex.org/C24590314","wikidata":"https://www.wikidata.org/wiki/Q336038","display_name":"Wireless sensor network","level":2,"score":0.44083383679389954},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.4172188639640808},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.3443021774291992},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.21391308307647705},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.20048031210899353},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.1426784098148346},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"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/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.0},{"id":"https://openalex.org/C66938386","wikidata":"https://www.wikidata.org/wiki/Q633538","display_name":"Structural engineering","level":1,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C19499675","wikidata":"https://www.wikidata.org/wiki/Q232207","display_name":"Monte Carlo method","level":2,"score":0.0},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tase.2022.3214193","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tase.2022.3214193","pdf_url":null,"source":{"id":"https://openalex.org/S34881539","display_name":"IEEE Transactions on Automation Science and Engineering","issn_l":"1545-5955","issn":["1545-5955","1558-3783"],"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 Automation Science and Engineering","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G293755711","display_name":null,"funder_award_id":"2032734","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G5143559255","display_name":null,"funder_award_id":"1818500","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":45,"referenced_works":["https://openalex.org/W1588558377","https://openalex.org/W1992250165","https://openalex.org/W2006349683","https://openalex.org/W2023977759","https://openalex.org/W2025183033","https://openalex.org/W2045067839","https://openalex.org/W2046660258","https://openalex.org/W2054395931","https://openalex.org/W2058049280","https://openalex.org/W2097363716","https://openalex.org/W2108858998","https://openalex.org/W2124604342","https://openalex.org/W2127548576","https://openalex.org/W2129242823","https://openalex.org/W2130017063","https://openalex.org/W2162438975","https://openalex.org/W2166531037","https://openalex.org/W2234416893","https://openalex.org/W2272986348","https://openalex.org/W2328672706","https://openalex.org/W2346720329","https://openalex.org/W2572289316","https://openalex.org/W2607420770","https://openalex.org/W2719238910","https://openalex.org/W2734129016","https://openalex.org/W2772999189","https://openalex.org/W2790203851","https://openalex.org/W2898699838","https://openalex.org/W2937234651","https://openalex.org/W2962860893","https://openalex.org/W2963741028","https://openalex.org/W2979786201","https://openalex.org/W2980588138","https://openalex.org/W2990611428","https://openalex.org/W3008300502","https://openalex.org/W3024133375","https://openalex.org/W3031223766","https://openalex.org/W3102702458","https://openalex.org/W3137278554","https://openalex.org/W4232212779","https://openalex.org/W4239876309","https://openalex.org/W4253895441","https://openalex.org/W4297068940","https://openalex.org/W4301668410","https://openalex.org/W6783881714"],"related_works":["https://openalex.org/W4229078645","https://openalex.org/W1977345676","https://openalex.org/W4282032776","https://openalex.org/W2047552823","https://openalex.org/W4321606905","https://openalex.org/W3130445735","https://openalex.org/W2105110616","https://openalex.org/W2739658809","https://openalex.org/W2747930654","https://openalex.org/W2419362237"],"abstract_inverted_index":{"The":[0,340,364],"monitoring":[1,127,149,176,230,262,268],"of":[2,53,61,68,165,179,183,217,225,231,242,277,290,329,372],"data":[3,63,71,299],"streams":[4],"with":[5,30,97,161],"a":[6,37,101,147,207,239,275],"network":[7,33,49,122,168,212,281,287,338,378],"structure":[8,123,288],"have":[9,213],"drawn":[10],"increasing":[11],"attention":[12],"due":[13,104,335],"to":[14,41,89,105,158,228,307,314,323,336,359,369],"its":[15],"wide":[16],"applications":[17,243],"in":[18,85,93,136,221,261,265,279,361,376,389,394],"modern":[19],"process":[20,175],"control.":[21],"In":[22,35,117],"these":[23],"applications,":[24],"high-dimensional":[25],"sensor":[26],"nodes":[27,55,278,291,310,360],"are":[28,143,270,312,367],"interconnected":[29],"an":[31],"underlying":[32],"topology.":[34],"such":[36,62,75,94,272],"case,":[38],"abnormalities":[39,92],"occurring":[40],"any":[42],"node":[43],"may":[44],"propagate":[45],"dynamically":[46,380],"across":[47],"the":[48,66,106,110,126,159,184,200,215,218,259,280,318,324,327,330,337,354,362,377,382,395],"and":[50,73,114,128,150,154,170,177,195,206,301,346,379,399],"cause":[51],"changes":[52,375,381],"other":[54],"over":[56],"time.":[57],"Furthermore,":[58],"high":[59],"dimensionality":[60],"significantly":[64],"increased":[65],"cost":[67],"resources":[69,269],"for":[70,132,173,233,238,292,302,348],"transmission":[72],"computation,":[74],"that":[76,273,311,326],"only":[77,140,274],"partial":[78,141],"observations":[79,142,388],"can":[80],"be":[81,315,370],"transmitted":[82],"or":[83],"processed":[84],"practice.":[86],"Overall,":[87],"how":[88],"quickly":[90,373],"detect":[91],"large":[95,137,240,263],"networks":[96,138,232,264],"resource":[98],"constraints":[99],"remains":[100],"challenge,":[102],"especially":[103,352],"sampling":[107,130,152,189,305,383],"uncertainty":[108],"under":[109],"dynamic":[111],"anomaly":[112,134,350,356],"occurrences":[113],"network-based":[115],"patterns.":[116],"this":[118],"paper,":[119],"we":[120,285],"incorporate":[121],"information":[124,172,289],"into":[125],"adaptive":[129,151,304],"methodologies":[131],"quick":[133],"detection":[135,201,295],"where":[139,267],"available.":[144],"We":[145],"develop":[146],"general":[148],"method":[153,319,342],"further":[155,321],"extend":[156],"it":[157],"case":[160,208,325,400],"memory":[162,328],"constraints,":[163],"both":[164],"which":[166],"exploit":[167],"distance":[169],"centrality":[171],"better":[174],"identification":[178],"abnormalities.":[180],"Theoretical":[181],"investigations":[182],"proposed":[185,219,365],"methods":[186,220,296,366],"demonstrate":[187],"their":[188],"efficiency":[190],"on":[191,210,386],"balancing":[192],"between":[193],"exploration":[194],"exploitation,":[196],"as":[197,199,392],"well":[198],"performance":[202],"guarantee.":[203],"Numerical":[204],"simulations":[205,398],"study":[209],"power":[211,245],"demonstrated":[214,368],"superiority":[216],"detecting":[222,374],"various":[223,349,390],"types":[224],"shifts.":[226],"Note":[227],"Practitioners\u2014Continuous":[229],"anomalous":[234],"events":[235],"is":[236,282,320,332,343],"critical":[237],"number":[241],"involving":[244],"networks,":[246,248,252],"computer":[247],"epidemiological":[249],"surveillance,":[250],"social":[251],"etc.":[253],"This":[254],"paper":[255],"aims":[256],"at":[257],"addressing":[258],"challenges":[260],"cases":[266],"limited":[271],"subset":[276],"observable.":[283],"Specifically,":[284],"integrate":[286],"constructing":[293],"sequential":[294],"via":[297],"effective":[298,347],"augmentation,":[300],"designing":[303],"algorithms":[306],"observe":[308],"suspicious":[309],"likely":[313],"abnormal.":[316],"Then,":[317],"generalized":[322],"computation":[331],"also":[333],"constrained":[334],"size.":[339],"developed":[341],"greatly":[344],"beneficial":[345],"patterns,":[351],"when":[353],"initial":[355],"randomly":[357],"occurs":[358],"network.":[363],"capable":[371],"priority":[384],"based":[385],"online":[387],"cases,":[391],"shown":[393],"theoretical":[396],"investigation,":[397],"studies.":[401]},"counts_by_year":[{"year":2025,"cited_by_count":5},{"year":2023,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
