{"id":"https://openalex.org/W2724553162","doi":"https://doi.org/10.1109/siu.2017.7960616","title":"Network intrusion detection using machine learning anomaly detection algorithms","display_name":"Network intrusion detection using machine learning anomaly detection algorithms","publication_year":2017,"publication_date":"2017-05-01","ids":{"openalex":"https://openalex.org/W2724553162","doi":"https://doi.org/10.1109/siu.2017.7960616","mag":"2724553162"},"language":"en","primary_location":{"id":"doi:10.1109/siu.2017.7960616","is_oa":false,"landing_page_url":"https://doi.org/10.1109/siu.2017.7960616","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 25th Signal Processing and Communications Applications Conference (SIU)","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/A5056353753","display_name":"M. Elif Karsl\u0131gil","orcid":"https://orcid.org/0000-0002-3477-582X"},"institutions":[{"id":"https://openalex.org/I4101805","display_name":"Y\u0131ld\u0131z Technical University","ror":"https://ror.org/0547yzj13","country_code":"TR","type":"education","lineage":["https://openalex.org/I4101805"]}],"countries":["TR"],"is_corresponding":false,"raw_author_name":"M. Elif Karsligil","raw_affiliation_strings":["Bilgisayar M\u00fchendisli\u011fi B\u00f6l\u00fcm\u00fc, Y\u0131ld\u0131z Teknik \u00dcniversitesi, \u0130stanbul, T\u00fcrkiye"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Bilgisayar M\u00fchendisli\u011fi B\u00f6l\u00fcm\u00fc, Y\u0131ld\u0131z Teknik \u00dcniversitesi, \u0130stanbul, T\u00fcrkiye","institution_ids":["https://openalex.org/I4101805"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085505828","display_name":"A. G\u00f6khan Yavuz","orcid":"https://orcid.org/0000-0002-6490-0396"},"institutions":[{"id":"https://openalex.org/I4101805","display_name":"Y\u0131ld\u0131z Technical University","ror":"https://ror.org/0547yzj13","country_code":"TR","type":"education","lineage":["https://openalex.org/I4101805"]}],"countries":["TR"],"is_corresponding":false,"raw_author_name":"A. Gokhan Yavuz","raw_affiliation_strings":["Bilgisayar M\u00fchendisli\u011fi B\u00f6l\u00fcm\u00fc, Y\u0131ld\u0131z Teknik \u00dcniversitesi, \u0130stanbul, T\u00fcrkiye"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Bilgisayar M\u00fchendisli\u011fi B\u00f6l\u00fcm\u00fc, Y\u0131ld\u0131z Teknik \u00dcniversitesi, \u0130stanbul, T\u00fcrkiye","institution_ids":["https://openalex.org/I4101805"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058725543","display_name":"M. Ama\u00e7 G\u00fcvensan","orcid":"https://orcid.org/0000-0002-2728-8900"},"institutions":[{"id":"https://openalex.org/I4101805","display_name":"Y\u0131ld\u0131z Technical University","ror":"https://ror.org/0547yzj13","country_code":"TR","type":"education","lineage":["https://openalex.org/I4101805"]}],"countries":["TR"],"is_corresponding":false,"raw_author_name":"M. Amac Guvensan","raw_affiliation_strings":["Yildiz Teknik Universitesi, Istanbul, TR"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Yildiz Teknik Universitesi, Istanbul, TR","institution_ids":["https://openalex.org/I4101805"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5063689765","display_name":"Khadija Hanifi","orcid":"https://orcid.org/0000-0001-7044-3315"},"institutions":[{"id":"https://openalex.org/I4101805","display_name":"Y\u0131ld\u0131z Technical University","ror":"https://ror.org/0547yzj13","country_code":"TR","type":"education","lineage":["https://openalex.org/I4101805"]}],"countries":["TR"],"is_corresponding":false,"raw_author_name":"Khadija Hanifi","raw_affiliation_strings":["Bilgisayar M\u00fchendisli\u011fi B\u00f6l\u00fcm\u00fc, Y\u0131ld\u0131z Teknik \u00dcniversitesi, \u0130stanbul, T\u00fcrkiye","Yildiz Teknik Universitesi, Istanbul, TR"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Bilgisayar M\u00fchendisli\u011fi B\u00f6l\u00fcm\u00fc, Y\u0131ld\u0131z Teknik \u00dcniversitesi, \u0130stanbul, T\u00fcrkiye","institution_ids":["https://openalex.org/I4101805"]},{"raw_affiliation_string":"Yildiz Teknik Universitesi, Istanbul, TR","institution_ids":["https://openalex.org/I4101805"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5085711161","display_name":"Hasan Bank","orcid":null},"institutions":[{"id":"https://openalex.org/I4101805","display_name":"Y\u0131ld\u0131z Technical University","ror":"https://ror.org/0547yzj13","country_code":"TR","type":"education","lineage":["https://openalex.org/I4101805"]}],"countries":["TR"],"is_corresponding":false,"raw_author_name":"Hasan Bank","raw_affiliation_strings":["Bilgisayar M\u00fchendisli\u011fi B\u00f6l\u00fcm\u00fc, Y\u0131ld\u0131z Teknik Universitesi, \u0130stanbul, T\u00fcrkiye","Yildiz Teknik Universitesi, Istanbul, TR"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Bilgisayar M\u00fchendisli\u011fi B\u00f6l\u00fcm\u00fc, Y\u0131ld\u0131z Teknik Universitesi, \u0130stanbul, T\u00fcrkiye","institution_ids":["https://openalex.org/I4101805"]},{"raw_affiliation_string":"Yildiz Teknik Universitesi, Istanbul, TR","institution_ids":["https://openalex.org/I4101805"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.1969,"has_fulltext":false,"cited_by_count":28,"citation_normalized_percentile":{"value":0.89355009,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"4"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10400","display_name":"Network Security and Intrusion Detection","score":1.0,"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":1.0,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9998999834060669,"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/T11598","display_name":"Internet Traffic Analysis and Secure E-voting","score":0.9987000226974487,"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":0.7488510608673096},{"id":"https://openalex.org/keywords/intrusion-detection-system","display_name":"Intrusion detection system","score":0.7365840077400208},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7179652452468872},{"id":"https://openalex.org/keywords/anomaly","display_name":"Anomaly (physics)","score":0.5504978895187378},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5328320264816284},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5124498009681702},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.48969176411628723},{"id":"https://openalex.org/keywords/threshold-limit-value","display_name":"Threshold limit value","score":0.469096302986145},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.44338318705558777},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4348160922527313},{"id":"https://openalex.org/keywords/intrusion","display_name":"Intrusion","score":0.42077577114105225},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4143630266189575},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.07885223627090454}],"concepts":[{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.7488510608673096},{"id":"https://openalex.org/C35525427","wikidata":"https://www.wikidata.org/wiki/Q745881","display_name":"Intrusion detection system","level":2,"score":0.7365840077400208},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7179652452468872},{"id":"https://openalex.org/C12997251","wikidata":"https://www.wikidata.org/wiki/Q567560","display_name":"Anomaly (physics)","level":2,"score":0.5504978895187378},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5328320264816284},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5124498009681702},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.48969176411628723},{"id":"https://openalex.org/C64413873","wikidata":"https://www.wikidata.org/wiki/Q21005","display_name":"Threshold limit value","level":2,"score":0.469096302986145},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.44338318705558777},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4348160922527313},{"id":"https://openalex.org/C158251709","wikidata":"https://www.wikidata.org/wiki/Q354025","display_name":"Intrusion","level":2,"score":0.42077577114105225},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4143630266189575},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.07885223627090454},{"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/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0},{"id":"https://openalex.org/C99454951","wikidata":"https://www.wikidata.org/wiki/Q932068","display_name":"Environmental health","level":1,"score":0.0},{"id":"https://openalex.org/C17409809","wikidata":"https://www.wikidata.org/wiki/Q161764","display_name":"Geochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/siu.2017.7960616","is_oa":false,"landing_page_url":"https://doi.org/10.1109/siu.2017.7960616","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 25th Signal Processing and Communications Applications Conference (SIU)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W1499653549","https://openalex.org/W1554891714","https://openalex.org/W1992419399","https://openalex.org/W2011430131","https://openalex.org/W2059515884","https://openalex.org/W2099940443","https://openalex.org/W2127218421","https://openalex.org/W2130072301","https://openalex.org/W2136504847","https://openalex.org/W2153919695","https://openalex.org/W2157665255","https://openalex.org/W2188735660","https://openalex.org/W2278186031","https://openalex.org/W2362380615","https://openalex.org/W4285719527","https://openalex.org/W6683235873","https://openalex.org/W6687177199"],"related_works":["https://openalex.org/W2806741695","https://openalex.org/W4290647774","https://openalex.org/W3189286258","https://openalex.org/W3207797160","https://openalex.org/W3210364259","https://openalex.org/W4300558037","https://openalex.org/W2912112202","https://openalex.org/W2667207928","https://openalex.org/W4377864969","https://openalex.org/W3030345572"],"abstract_inverted_index":{"Attacks":[0],"on":[1,119],"the":[2,39,71,89,94,120],"network":[3,22,109],"are":[4,8,86],"exceptional":[5],"cases":[6],"that":[7,85,125],"not":[9],"observed":[10],"in":[11,18,53],"normal":[12,42,61],"traffic":[13],"behavior.":[14],"In":[15],"this":[16],"work,":[17],"order":[19,54],"to":[20,55,58,67],"detect":[21],"attacks,":[23],"using":[24,75],"k-means":[25,50],"algorithm":[26],"a":[27,76,105],"new":[28],"semi-supervised":[29],"anomaly":[30],"detection":[31],"system":[32],"has":[33],"been":[34],"designed":[35],"and":[36,62,74],"implemented.":[37],"During":[38],"training":[40],"phase,":[41],"samples":[43,64,84],"were":[44],"separated":[45],"into":[46],"clusters":[47],"by":[48],"applying":[49],"algorithm.":[51],"Then,":[52],"be":[56],"able":[57],"distinguish":[59],"between":[60],"abnormal":[63],"\u2014":[65,104],"according":[66],"their":[68],"distances":[69],"from":[70,88],"clusters'":[72,90],"centers":[73,91],"validation":[77],"dataset-a":[78],"threshold":[79,95],"value":[80,96],"was":[81],"calculated.":[82],"New":[83],"far":[87],"more":[92],"than":[93],"is":[97],"detected":[98],"as":[99],"anomalies.":[100],"We":[101],"used":[102],"NSL-KDD":[103,121],"labelled":[106],"dataset":[107],"of":[108,130],"connection":[110],"traces-for":[111],"testing":[112],"our":[113],"method's":[114],"effectiveness.":[115],"The":[116],"experiments":[117],"result":[118],"data":[122],"set,":[123],"shows":[124],"we":[126],"achieved":[127],"an":[128],"accuracy":[129],"80.119%.":[131]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":7},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":5},{"year":2019,"cited_by_count":5}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}