{"id":"https://openalex.org/W4285327007","doi":"https://doi.org/10.1109/icpads53394.2021.00043","title":"Effective Anomaly Detection Based on Reinforcement Learning in Network Traffic Data","display_name":"Effective Anomaly Detection Based on Reinforcement Learning in Network Traffic Data","publication_year":2021,"publication_date":"2021-12-01","ids":{"openalex":"https://openalex.org/W4285327007","doi":"https://doi.org/10.1109/icpads53394.2021.00043"},"language":"en","primary_location":{"is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpads53394.2021.00043","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false},"type":"article","type_crossref":"proceedings-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/A5100748098","display_name":"Zhongyang Wang","orcid":"https://orcid.org/0000-0003-2717-4345"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhongyang Wang","raw_affiliation_strings":["Science and Technology on Parallel and Distributed Processing Laboratory College of Computer, National University of Defense Technology"],"affiliations":[{"raw_affiliation_string":"Science and Technology on Parallel and Distributed Processing Laboratory College of Computer, National University of Defense Technology","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100429826","display_name":"Yijie Wang","orcid":"https://orcid.org/0000-0002-2913-4016"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yijie Wang","raw_affiliation_strings":["Science and Technology on Parallel and Distributed Processing Laboratory College of Computer, National University of Defense Technology"],"affiliations":[{"raw_affiliation_string":"Science and Technology on Parallel and Distributed Processing Laboratory College of Computer, National University of Defense Technology","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5091676049","display_name":"Hongzuo Xu","orcid":"https://orcid.org/0000-0001-8074-1244"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongzuo Xu","raw_affiliation_strings":["Science and Technology on Parallel and Distributed Processing Laboratory College of Computer, National University of Defense Technology"],"affiliations":[{"raw_affiliation_string":"Science and Technology on Parallel and Distributed Processing Laboratory College of Computer, National University of Defense Technology","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100424209","display_name":"Yongjun Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yongjun Wang","raw_affiliation_strings":[],"affiliations":[]}],"institution_assertions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.0,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":0,"max":57},"biblio":{"volume":null,"issue":null,"first_page":"299","last_page":"306"},"is_retracted":false,"is_paratext":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":0.9999,"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":0.9952,"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","display_name":"Anomaly (physics)","score":0.5919948},{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.4996779},{"id":"https://openalex.org/keywords/categorical-variable","display_name":"Categorical variable","score":0.49912047},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.46182352}],"concepts":[{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.7563999},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6884271},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.67321765},{"id":"https://openalex.org/C12997251","wikidata":"https://www.wikidata.org/wiki/Q567560","display_name":"Anomaly (physics)","level":2,"score":0.5919948},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.580448},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5074641},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.4996779},{"id":"https://openalex.org/C5274069","wikidata":"https://www.wikidata.org/wiki/Q2285707","display_name":"Categorical variable","level":2,"score":0.49912047},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.47613028},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.46182352},{"id":"https://openalex.org/C106301342","wikidata":"https://www.wikidata.org/wiki/Q4117933","display_name":"Entropy (arrow of time)","level":2,"score":0.41743612},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4103778},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.28788787},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"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/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","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":1,"locations":[{"is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpads53394.2021.00043","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false}],"best_oa_location":null,"sustainable_development_goals":[],"grants":[{"funder":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China","award_id":"61379052,61472439"},{"funder":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China","award_id":"2016YFB1000101"}],"datasets":[],"versions":[],"referenced_works_count":23,"referenced_works":["https://openalex.org/W1031497972","https://openalex.org/W1581299182","https://openalex.org/W1594509342","https://openalex.org/W1966147156","https://openalex.org/W2059013010","https://openalex.org/W2074937039","https://openalex.org/W2104052971","https://openalex.org/W2107373450","https://openalex.org/W2134510195","https://openalex.org/W2134532107","https://openalex.org/W2170902455","https://openalex.org/W2282861635","https://openalex.org/W2336788611","https://openalex.org/W2474015102","https://openalex.org/W2584316068","https://openalex.org/W2767534812","https://openalex.org/W2788154850","https://openalex.org/W2788767962","https://openalex.org/W2799033092","https://openalex.org/W2905191756","https://openalex.org/W2963341628","https://openalex.org/W3004149215","https://openalex.org/W4253461361"],"related_works":["https://openalex.org/W4363671829","https://openalex.org/W4300558037","https://openalex.org/W4290647774","https://openalex.org/W3210364259","https://openalex.org/W3207797160","https://openalex.org/W3194885736","https://openalex.org/W3189286258","https://openalex.org/W3186512740","https://openalex.org/W2912112202","https://openalex.org/W2806741695"],"abstract_inverted_index":{"Mixed-type":[0],"data":[1,28],"with":[2,21,156],"both":[3],"categorical":[4,145],"and":[5,40,53,110,119,123,137,140,146,203,231,248,264,311,319],"numerical":[6,147],"features":[7],"are":[8,17,60,161,246,269,273],"ubiquitous":[9],"in":[10,56,74,80,143],"network":[11,302],"security,":[12],"but":[13],"the":[14,44,66,70,144,165,187,193,198,206,211,217,223,228,233,239,249,254,257,265,282,289,293],"existing":[15,47],"methods":[16,24,48],"minimal":[18],"to":[19,69,105,133,151,163,184,196,210,215,226,238,275,280],"deal":[20],"them.":[22],"Existing":[23],"usually":[25,49],"process":[26,291],"mixed-type":[27],"through":[29],"feature":[30,148],"conversion,":[31],"whereas":[32],"their":[33],"performance":[34],"is":[35,261,295],"downgraded":[36],"by":[37,43,317],"information":[38],"loss":[39],"noise":[41],"caused":[42],"transformation.":[45],"Meanwhile,":[46],"superimpose":[50],"domain":[51,117,131],"knowledge":[52,118,132,225],"machine":[54,120,278],"learning":[55,104,121,183,279],"which":[57,78,101,160],"fixed":[58],"thresholds":[59,109],"used.":[61],"It":[62],"cannot":[63],"dynamically":[64,106],"adjust":[65,227],"anomaly":[67,113,153,158,167,177,194,200,212,229,267],"threshold":[68,195,243,255],"actual":[71],"scenario,":[72],"resulting":[73],"inaccurate":[75],"anomalies":[76,136],"obtained,":[77,263],"results":[79],"poor":[81],"performance.":[82],"To":[83,174],"address":[84],"these":[85],"issues,":[86],"this":[87],"paper":[88],"proposes":[89],"a":[90,170],"novel":[91],"Anomaly":[92],"Detection":[93],"method":[94,294],"based":[95],"on":[96,205,299],"Reinforcement":[97],"Learning,":[98],"termed":[99],"ADRL,":[100],"uses":[102,129,138,181,222],"reinforcement":[103,182],"search":[107,185],"for":[108,186,285],"accurately":[111],"obtain":[112,152,175],"candidate":[114,178,201,213],"sets,":[115,179],"fusing":[116],"fully":[122],"promoting":[124],"each":[125],"other.":[126],"Specifically,":[127],"ADRL":[128,180,221,307],"prior":[130],"label":[134],"known":[135,157],"entropy":[139],"deep":[141],"autoencoder":[142],"spaces,":[149],"respectively,":[150],"scores":[154,168,268,272],"combining":[155],"information,":[159],"integrated":[162],"get":[164,197,232],"overall":[166],"via":[169],"dynamic":[171],"integration":[172],"strategy.":[173],"accurate":[176],"best":[188,250],"threshold.":[189],"Detailedly,":[190],"it":[191],"initializes":[192],"initial":[199],"set":[202,214],"carries":[204],"frequent":[207],"rule":[208],"mining":[209],"form":[216],"new":[218],"knowledge.":[219],"Then,":[220],"obtained":[224],"score":[230,234],"modification":[235,240,244,259],"rate.":[236],"According":[237],"rate,":[241,260],"different":[242],"strategies":[245],"executed,":[247],"threshold,":[251],"that":[252],"is,":[253],"under":[256],"maximum":[258],"finally":[262],"modified":[266],"obtained.":[270],"The":[271],"used":[274],"re-carry":[276],"out":[277],"improve":[281],"algorithm's":[283],"accuracy":[284],"anomalous":[286],"data.":[287],"Repeat":[288],"above":[290],"until":[292],"stable.":[296],"We":[297],"experiment":[298],"ten":[300],"real":[301],"traffic":[303],"datasets.":[304],"Experiments":[305],"show":[306],"averagely":[308],"improves":[309],"ROC-AUC":[310],"PR-AUC":[312],"than":[313],"eight":[314],"state-of-the-art":[315],"competitors":[316],"89.6%":[318],"286.0%,":[320],"respectively.":[321]},"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W4285327007","counts_by_year":[],"updated_date":"2024-12-24T04:29:37.267753","created_date":"2022-07-14"}