{"id":"https://openalex.org/W4414169721","doi":"https://doi.org/10.1109/iwqos65803.2025.11143506","title":"WisePIFinder: Efficient and Accurate Detection of Persistent and Infrequent Flows","display_name":"WisePIFinder: Efficient and Accurate Detection of Persistent and Infrequent Flows","publication_year":2025,"publication_date":"2025-07-02","ids":{"openalex":"https://openalex.org/W4414169721","doi":"https://doi.org/10.1109/iwqos65803.2025.11143506"},"language":"en","primary_location":{"id":"doi:10.1109/iwqos65803.2025.11143506","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iwqos65803.2025.11143506","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE/ACM 33rd International Symposium on Quality of Service (IWQoS)","raw_type":"proceedings-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/A5071283751","display_name":"Zengxie Ma","orcid":null},"institutions":[{"id":"https://openalex.org/I78988378","display_name":"Renmin University of China","ror":"https://ror.org/041pakw92","country_code":"CN","type":"education","lineage":["https://openalex.org/I78988378"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zengxie Ma","raw_affiliation_strings":["Renmin University of China"],"affiliations":[{"raw_affiliation_string":"Renmin University of China","institution_ids":["https://openalex.org/I78988378"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040069267","display_name":"Yao Xin","orcid":"https://orcid.org/0000-0002-6495-081X"},"institutions":[{"id":"https://openalex.org/I37987034","display_name":"Guangzhou University","ror":"https://ror.org/05ar8rn06","country_code":"CN","type":"education","lineage":["https://openalex.org/I37987034"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yao Xin","raw_affiliation_strings":["Guangzhou University"],"affiliations":[{"raw_affiliation_string":"Guangzhou University","institution_ids":["https://openalex.org/I37987034"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100383072","display_name":"Ying Chen","orcid":"https://orcid.org/0000-0002-6387-8107"},"institutions":[{"id":"https://openalex.org/I78988378","display_name":"Renmin University of China","ror":"https://ror.org/041pakw92","country_code":"CN","type":"education","lineage":["https://openalex.org/I78988378"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ying Chen","raw_affiliation_strings":["Renmin University of China"],"affiliations":[{"raw_affiliation_string":"Renmin University of China","institution_ids":["https://openalex.org/I78988378"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5089567046","display_name":"Zhuochen Fan","orcid":"https://orcid.org/0000-0003-0042-1828"},"institutions":[{"id":"https://openalex.org/I4210136793","display_name":"Peng Cheng Laboratory","ror":"https://ror.org/03qdqbt06","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210136793"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhuochen Fan","raw_affiliation_strings":["Pengcheng Laboratory"],"affiliations":[{"raw_affiliation_string":"Pengcheng Laboratory","institution_ids":["https://openalex.org/I4210136793"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100359033","display_name":"Tong Li","orcid":"https://orcid.org/0000-0002-6805-9565"},"institutions":[{"id":"https://openalex.org/I78988378","display_name":"Renmin University of China","ror":"https://ror.org/041pakw92","country_code":"CN","type":"education","lineage":["https://openalex.org/I78988378"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tong Li","raw_affiliation_strings":["Renmin University of China"],"affiliations":[{"raw_affiliation_string":"Renmin University of China","institution_ids":["https://openalex.org/I78988378"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5044196870","display_name":"Ning Hu","orcid":"https://orcid.org/0000-0002-8355-0969"},"institutions":[{"id":"https://openalex.org/I4210136793","display_name":"Peng Cheng Laboratory","ror":"https://ror.org/03qdqbt06","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210136793"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ning Hu","raw_affiliation_strings":["Pengcheng Laboratory"],"affiliations":[{"raw_affiliation_string":"Pengcheng Laboratory","institution_ids":["https://openalex.org/I4210136793"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5062785023","display_name":"Qing Liao","orcid":"https://orcid.org/0000-0003-3137-2862"},"institutions":[{"id":"https://openalex.org/I4210136793","display_name":"Peng Cheng Laboratory","ror":"https://ror.org/03qdqbt06","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210136793"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qing Liao","raw_affiliation_strings":["Pengcheng Laboratory"],"affiliations":[{"raw_affiliation_string":"Pengcheng Laboratory","institution_ids":["https://openalex.org/I4210136793"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110200590","display_name":"Yi Zhao","orcid":null},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yi Zhao","raw_affiliation_strings":["Beijing Institute of Technology"],"affiliations":[{"raw_affiliation_string":"Beijing Institute of Technology","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100401308","display_name":"Feng Zhang","orcid":"https://orcid.org/0000-0003-1475-8480"},"institutions":[{"id":"https://openalex.org/I78988378","display_name":"Renmin University of China","ror":"https://ror.org/041pakw92","country_code":"CN","type":"education","lineage":["https://openalex.org/I78988378"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Feng Zhang","raw_affiliation_strings":["Renmin University of China"],"affiliations":[{"raw_affiliation_string":"Renmin University of China","institution_ids":["https://openalex.org/I78988378"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":9,"corresponding_author_ids":["https://openalex.org/A5071283751"],"corresponding_institution_ids":["https://openalex.org/I78988378"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.13349072,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"10"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12761","display_name":"Data Stream Mining Techniques","score":0.9990000128746033,"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/T12761","display_name":"Data Stream Mining Techniques","score":0.9990000128746033,"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":0.9965999722480774,"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/T11181","display_name":"Advanced Data Storage Technologies","score":0.982699990272522,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/sketch","display_name":"Sketch","score":0.6273000240325928},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.5376999974250793},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.5145000219345093},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.49810001254081726},{"id":"https://openalex.org/keywords/flow","display_name":"Flow (mathematics)","score":0.3402000069618225},{"id":"https://openalex.org/keywords/throughput","display_name":"Throughput","score":0.3368000090122223}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6628999710083008},{"id":"https://openalex.org/C2779231336","wikidata":"https://www.wikidata.org/wiki/Q7534724","display_name":"Sketch","level":2,"score":0.6273000240325928},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.5376999974250793},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.5145000219345093},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.49810001254081726},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.49380001425743103},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.40610000491142273},{"id":"https://openalex.org/C38349280","wikidata":"https://www.wikidata.org/wiki/Q1434290","display_name":"Flow (mathematics)","level":2,"score":0.3402000069618225},{"id":"https://openalex.org/C157764524","wikidata":"https://www.wikidata.org/wiki/Q1383412","display_name":"Throughput","level":3,"score":0.3368000090122223},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.29660001397132874},{"id":"https://openalex.org/C114809511","wikidata":"https://www.wikidata.org/wiki/Q1412924","display_name":"Flow network","level":2,"score":0.28850001096725464},{"id":"https://openalex.org/C198386975","wikidata":"https://www.wikidata.org/wiki/Q117785","display_name":"Finite impulse response","level":2,"score":0.2881999909877777},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.2515000104904175}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iwqos65803.2025.11143506","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iwqos65803.2025.11143506","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE/ACM 33rd International Symposium on Quality of Service (IWQoS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W1968625547","https://openalex.org/W1977951613","https://openalex.org/W2025970444","https://openalex.org/W2058217283","https://openalex.org/W2080234606","https://openalex.org/W2798945787","https://openalex.org/W2808923818","https://openalex.org/W2893547295","https://openalex.org/W2910711617","https://openalex.org/W2967106834","https://openalex.org/W2969998124","https://openalex.org/W3080797160","https://openalex.org/W3102387041","https://openalex.org/W3153713140","https://openalex.org/W3175777295","https://openalex.org/W3189127798","https://openalex.org/W3197629532","https://openalex.org/W3212706643","https://openalex.org/W4213058572","https://openalex.org/W4291657023","https://openalex.org/W4296441549","https://openalex.org/W4376464605","https://openalex.org/W4385329419","https://openalex.org/W4386156805","https://openalex.org/W4401176811","https://openalex.org/W4401508212","https://openalex.org/W4409310868"],"related_works":[],"abstract_inverted_index":{"In":[0],"large-scale":[1],"data":[2],"stream":[3],"analytics,":[4],"accurate":[5,114],"identification":[6],"of":[7,14,58],"Persistent":[8,27],"and":[9,19,48,69,94,133],"Infrequent":[10],"(PI)":[11],"flows":[12,38,91,107],"is":[13,101],"great":[15],"significance":[16],"for":[17,51,146],"monitoring":[18],"protecting":[20],"against":[21],"network":[22],"attacks":[23],"such":[24],"as":[25],"Advanced":[26],"Threats":[28],"(APT).":[29],"However,":[30],"existing":[31],"research":[32],"focuses":[33],"mainly":[34],"on":[35,45,55,116,156],"detecting":[36,109,147],"frequent":[37],"or":[39],"persistent":[40],"flows,":[41,61],"with":[42],"insufficient":[43],"studies":[44],"the":[46,56,125,143],"characterization":[47],"detection":[49],"methods":[50],"PI":[52,75,90,117,148],"flows.":[53,76,118,149],"Based":[54],"analysis":[57],"sufficient":[59],"APT":[60],"we":[62,78],"propose":[63,79],"a":[64,80],"method":[65],"that":[66,122],"combines":[67],"global":[68],"local":[70],"features":[71],"to":[72,88,102,112,142],"effectively":[73],"characterize":[74],"Further,":[77],"novel":[81],"sketch":[82],"algorithm":[83],"called":[84],"WisePIFinder,":[85],"which":[86],"aims":[87],"detect":[89],"more":[92],"accurately":[93],"efficiently":[95],"in":[96],"realtime.":[97],"The":[98],"key":[99],"idea":[100],"continuously":[103],"filter":[104],"out":[105],"non-PI":[106],"while":[108],"flow":[110],"persistence,":[111],"achieve":[113],"statistics":[115],"Experimental":[119],"results":[120],"show":[121],"WisePIFinder":[123],"improves":[124],"F1":[126],"Score":[127],"by":[128,136],"at":[129,137],"least":[130,138],"20":[131],"%":[132,140],"insertion":[134],"throughput":[135],"60":[139],"compared":[141],"state-of-the-art":[144],"solution":[145],"All":[150],"related":[151],"codes":[152],"have":[153],"been":[154],"open-sourced":[155],"GitHub.":[157]},"counts_by_year":[],"updated_date":"2026-03-07T16:01:11.037858","created_date":"2025-10-10T00:00:00"}