{"id":"https://openalex.org/W2294588635","doi":"https://doi.org/10.4304/jnw.10.9.512-520","title":"Performance of Flow-based Anomaly Detection in Sampled Traffic","display_name":"Performance of Flow-based Anomaly Detection in Sampled Traffic","publication_year":2016,"publication_date":"2016-01-06","ids":{"openalex":"https://openalex.org/W2294588635","doi":"https://doi.org/10.4304/jnw.10.9.512-520","mag":"2294588635"},"language":"en","primary_location":{"id":"doi:10.4304/jnw.10.9.512-520","doi":"https://doi.org/10.4304/jnw.10.9.512-520","is_oa":false,"landing_page_url":"https://doi.org/10.4304/jnw.10.9.512-520","pdf_url":null,"source":{"id":"https://openalex.org/S189188848","display_name":"Journal of Networks","issn_l":"1796-2056","issn":["1796-2056"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["anvur-scientific","cwts-core"],"host_organization":"https://openalex.org/P4310318660","host_organization_name":"Academy Publisher","host_organization_lineage":["https://openalex.org/P4310318660"],"host_organization_lineage_names":["Academy Publisher"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Networks","raw_type":"journal-article"},"volume":null,"type":"article","is_traditional":true,"indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"http://hdl.handle.net/10072/99644","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5080148923","display_name":"Zahra Jadidi","orcid":"https://orcid.org/0000-0002-6694-7753","observed_orcids":["https://orcid.org/0000-0002-6694-7753"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zahra Jadidi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016915945","display_name":"Vallipuram Muthukkumarasamy","orcid":"https://orcid.org/0000-0002-6787-6379","observed_orcids":["https://orcid.org/0000-0002-6787-6379"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Vallipuram Muthukkumarasamy","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052346190","display_name":"Elankayer Sithirasenan","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Elankayer Sithirasenan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5111959172","display_name":"Kalvinder Singh","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kalvinder Singh","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.5993,"has_fulltext":true,"cited_by_count":10,"citation_normalized_percentile":{"value":0.90394003,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":88,"max":98},"biblio":{"volume":"10","issue":"9","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10400","display_name":"Network Security and Intrusion Detection","score":0.9779999852180481,"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"}},"topics":[{"id":"https://openalex.org/T10400","display_name":"Network Security and Intrusion Detection","score":0.9779999852180481,"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":0.011500000022351742,"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/T12326","display_name":"Network Packet Processing and Optimization","score":0.004600000102072954,"subfield":{"id":"https://openalex.org/subfields/1708","display_name":"Hardware and Architecture"},"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/neural-network-classifier","display_name":"neural network classifier","score":0.8899999856948853},{"id":"https://openalex.org/keywords/high-speed-networks","display_name":"high-speed networks","score":0.6729999780654907},{"id":"https://openalex.org/keywords/detection-rate-improvement","display_name":"detection rate improvement","score":0.5820000171661377}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.887072741985321},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.7032615542411804},{"id":"https://openalex.org/C38349280","wikidata":"https://www.wikidata.org/wiki/Q1434290","display_name":"Flow (mathematics)","level":2,"score":0.43510767817497253},{"id":"https://openalex.org/C12997251","wikidata":"https://www.wikidata.org/wiki/Q567560","display_name":"Anomaly (physics)","level":2,"score":0.4104241728782654},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3601263761520386},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.34760570526123047},{"id":"https://openalex.org/C57879066","wikidata":"https://www.wikidata.org/wiki/Q41217","display_name":"Mechanics","level":1,"score":0.08402875065803528},{"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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.4304/jnw.10.9.512-520","doi":"https://doi.org/10.4304/jnw.10.9.512-520","is_oa":false,"landing_page_url":"https://doi.org/10.4304/jnw.10.9.512-520","pdf_url":null,"source":{"id":"https://openalex.org/S189188848","display_name":"Journal of Networks","issn_l":"1796-2056","issn":["1796-2056"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["anvur-scientific","cwts-core"],"host_organization":"https://openalex.org/P4310318660","host_organization_name":"Academy Publisher","host_organization_lineage":["https://openalex.org/P4310318660"],"host_organization_lineage_names":["Academy Publisher"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Networks","raw_type":"journal-article"},{"id":"pmh:oai:research-repository.griffith.edu.au:10072/99644","doi":null,"is_oa":true,"landing_page_url":"http://hdl.handle.net/10072/99644","pdf_url":"http://hdl.handle.net/10072/99644","source":{"id":"https://openalex.org/S7407064376","display_name":"Griffith Research Online","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Journal article"}],"best_oa_location":{"id":"pmh:oai:research-repository.griffith.edu.au:10072/99644","doi":null,"is_oa":true,"landing_page_url":"http://hdl.handle.net/10072/99644","pdf_url":"http://hdl.handle.net/10072/99644","source":{"id":"https://openalex.org/S7407064376","display_name":"Griffith Research Online","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Journal article"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2294588635.pdf","grobid_xml":"https://content.openalex.org/works/W2294588635.grobid-xml"},"referenced_works_count":27,"referenced_works":["https://openalex.org/W1493447042","https://openalex.org/W1738203895","https://openalex.org/W1977141583","https://openalex.org/W1980062751","https://openalex.org/W1983488804","https://openalex.org/W1993467749","https://openalex.org/W1994864447","https://openalex.org/W1996639403","https://openalex.org/W2001396694","https://openalex.org/W2012027153","https://openalex.org/W2020699332","https://openalex.org/W2050546928","https://openalex.org/W2061338198","https://openalex.org/W2069685920","https://openalex.org/W2072955302","https://openalex.org/W2074838602","https://openalex.org/W2104936918","https://openalex.org/W2117747231","https://openalex.org/W2134539183","https://openalex.org/W2136842915","https://openalex.org/W2163375756","https://openalex.org/W2164532265","https://openalex.org/W2165032725","https://openalex.org/W2171331105","https://openalex.org/W2277036336","https://openalex.org/W2339635974","https://openalex.org/W2569506738"],"related_works":["https://openalex.org/W2295597102","https://openalex.org/W2563352585","https://openalex.org/W2011787683","https://openalex.org/W2157955210","https://openalex.org/W7137786708","https://openalex.org/W1496859626","https://openalex.org/W2165032725","https://openalex.org/W2368453656","https://openalex.org/W2357594444","https://openalex.org/W2127307360"],"abstract_inverted_index":{"In":[0,90],"recent":[1],"years,":[2],"flow-based":[3,103,137,155],"anomaly":[4,30,104,114,138],"detection":[5,31,105,115,133],"has":[6,74],"attracted":[7],"considerable":[8],"attention":[9],"from":[10],"many":[11],"researchers":[12],"and":[13,127],"some":[14],"methods":[15,112],"have":[16,28],"been":[17],"proposed":[18,122,151],"to":[19,62,98],"improve":[20,99],"its":[21],"accuracy.":[22],"However,":[23],"only":[24,117],"a":[25,75,95],"few":[26],"studies":[27],"considered":[29],"with":[32],"sampled":[33,107],"flow":[34,66],"traffic,":[35],"which":[36],"is":[37,48,140],"widely":[38],"used":[39],"for":[40,113],"the":[41,80,86,100,121,132,136,150],"management":[42],"of":[43,78,88,102,135],"high-speed":[44],"networks.":[45],"This":[46],"gap":[47],"addressed":[49],"in":[50,65,85,106,159],"this":[51,91,160],"study.":[52,161],"First,":[53],"we":[54,93],"optimize":[55],"an":[56],"artificial":[57],"neural":[58],"network":[59],"(ANN)-based":[60],"classifier":[61,81],"detect":[63],"anomalies":[64],"traffic.":[67,108],"The":[68],"results":[69],"show":[70],"that":[71],"although":[72],"it":[73],"high":[76],"degree":[77],"accuracy,":[79],"loses":[82],"significant":[83],"information":[84],"process":[87],"sampling.":[89],"regard,":[92],"propose":[94],"sampling":[96,111,152],"method":[97],"performance":[101],"While":[109],"existing":[110],"preserve":[116],"small":[118,126],"malicious":[119,129],"flows,":[120],"algorithm":[123],"samples":[124],"both":[125],"large":[128],"flows.":[130],"Therefore,":[131],"rate":[134],"detector":[139],"improved":[141],"by":[142],"about":[143],"5%":[144],"using":[145],"our":[146],"algorithm.":[147],"To":[148],"evaluate":[149],"method,":[153],"three":[154],"datasets":[156],"are":[157],"generated":[158]},"counts_by_year":[{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":2},{"year":2016,"cited_by_count":5},{"year":2015,"cited_by_count":1}],"updated_date":"2026-09-02T18:50:13.731487","created_date":"2016-06-24T00:00:00"}