{"id":"https://openalex.org/W2944643572","doi":"https://doi.org/10.1145/3299815.3314439","title":"Intrusion Detection Using Big Data and Deep Learning Techniques","display_name":"Intrusion Detection Using Big Data and Deep Learning Techniques","publication_year":2019,"publication_date":"2019-04-18","ids":{"openalex":"https://openalex.org/W2944643572","doi":"https://doi.org/10.1145/3299815.3314439","mag":"2944643572"},"language":"en","primary_location":{"id":"doi:10.1145/3299815.3314439","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3299815.3314439","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2019 ACM Southeast Conference","raw_type":"proceedings-article"},"type":"conference-paper","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/A5029039267","display_name":"Osama Faker","orcid":"https://orcid.org/0000-0002-9281-7944"},"institutions":[{"id":"https://openalex.org/I106245021","display_name":"\u00c7ankaya University","ror":"https://ror.org/056wqre19","country_code":"TR","type":"education","lineage":["https://openalex.org/I106245021"]}],"countries":["TR"],"is_corresponding":false,"raw_author_name":"Osama Faker","raw_affiliation_strings":["Cankaya University, Ankara, Turkey"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Cankaya University, Ankara, Turkey","institution_ids":["https://openalex.org/I106245021"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5076293142","display_name":"Erdo\u011fan Do\u011fdu","orcid":"https://orcid.org/0000-0001-5987-0164"},"institutions":[{"id":"https://openalex.org/I106245021","display_name":"\u00c7ankaya University","ror":"https://ror.org/056wqre19","country_code":"TR","type":"education","lineage":["https://openalex.org/I106245021"]},{"id":"https://openalex.org/I181565077","display_name":"Georgia State University","ror":"https://ror.org/03qt6ba18","country_code":"US","type":"education","lineage":["https://openalex.org/I181565077"]}],"countries":["TR","US"],"is_corresponding":false,"raw_author_name":"Erdogan Dogdu","raw_affiliation_strings":["Cankaya University, Georgia State University (adjunct), Ankara, Turkey"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Cankaya University, Georgia State University (adjunct), Ankara, Turkey","institution_ids":["https://openalex.org/I106245021","https://openalex.org/I181565077"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":28.843,"has_fulltext":false,"cited_by_count":222,"citation_normalized_percentile":{"value":0.99919389,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"86","last_page":"93"},"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":0.9997000098228455,"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":0.9994999766349792,"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/computer-science","display_name":"Computer science","score":0.816631555557251},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7730981111526489},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.7293648719787598},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6872398257255554},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.681785523891449},{"id":"https://openalex.org/keywords/gradient-boosting","display_name":"Gradient boosting","score":0.6644344329833984},{"id":"https://openalex.org/keywords/multiclass-classification","display_name":"Multiclass classification","score":0.6642158031463623},{"id":"https://openalex.org/keywords/binary-classification","display_name":"Binary classification","score":0.6201468110084534},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5759800672531128},{"id":"https://openalex.org/keywords/ensemble-learning","display_name":"Ensemble learning","score":0.5268253684043884},{"id":"https://openalex.org/keywords/boosting","display_name":"Boosting (machine learning)","score":0.510644257068634},{"id":"https://openalex.org/keywords/deep-neural-networks","display_name":"Deep neural networks","score":0.500159740447998},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.494973361492157},{"id":"https://openalex.org/keywords/intrusion-detection-system","display_name":"Intrusion detection system","score":0.4748385548591614},{"id":"https://openalex.org/keywords/big-data","display_name":"Big data","score":0.41550207138061523},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3980727791786194},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.3060121536254883}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.816631555557251},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7730981111526489},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.7293648719787598},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6872398257255554},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.681785523891449},{"id":"https://openalex.org/C70153297","wikidata":"https://www.wikidata.org/wiki/Q5591907","display_name":"Gradient boosting","level":3,"score":0.6644344329833984},{"id":"https://openalex.org/C123860398","wikidata":"https://www.wikidata.org/wiki/Q6934605","display_name":"Multiclass classification","level":3,"score":0.6642158031463623},{"id":"https://openalex.org/C66905080","wikidata":"https://www.wikidata.org/wiki/Q17005494","display_name":"Binary classification","level":3,"score":0.6201468110084534},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5759800672531128},{"id":"https://openalex.org/C45942800","wikidata":"https://www.wikidata.org/wiki/Q245652","display_name":"Ensemble learning","level":2,"score":0.5268253684043884},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.510644257068634},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.500159740447998},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.494973361492157},{"id":"https://openalex.org/C35525427","wikidata":"https://www.wikidata.org/wiki/Q745881","display_name":"Intrusion detection system","level":2,"score":0.4748385548591614},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.41550207138061523},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3980727791786194},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.3060121536254883}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3299815.3314439","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3299815.3314439","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2019 ACM Southeast Conference","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.4699999988079071,"id":"https://metadata.un.org/sdg/15","display_name":"Life in Land"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":39,"referenced_works":["https://openalex.org/W613690151","https://openalex.org/W1505837402","https://openalex.org/W2025001960","https://openalex.org/W2025215403","https://openalex.org/W2026205964","https://openalex.org/W2070493638","https://openalex.org/W2076063813","https://openalex.org/W2099940443","https://openalex.org/W2108142795","https://openalex.org/W2110086534","https://openalex.org/W2118023920","https://openalex.org/W2119738171","https://openalex.org/W2122646361","https://openalex.org/W2138615112","https://openalex.org/W2144855985","https://openalex.org/W2296509296","https://openalex.org/W2334853001","https://openalex.org/W2498672755","https://openalex.org/W2507920413","https://openalex.org/W2542459869","https://openalex.org/W2591712613","https://openalex.org/W2599306383","https://openalex.org/W2614393686","https://openalex.org/W2618735189","https://openalex.org/W2622610444","https://openalex.org/W2729006349","https://openalex.org/W2732560875","https://openalex.org/W2762958083","https://openalex.org/W2783796368","https://openalex.org/W2786743105","https://openalex.org/W2789828921","https://openalex.org/W2793412195","https://openalex.org/W2799548584","https://openalex.org/W2805221961","https://openalex.org/W2885812677","https://openalex.org/W2911964244","https://openalex.org/W4245684777","https://openalex.org/W4285719527","https://openalex.org/W4300874179"],"related_works":["https://openalex.org/W3208169454","https://openalex.org/W4298012357","https://openalex.org/W4296079469","https://openalex.org/W4376528628","https://openalex.org/W2896054965","https://openalex.org/W2896110774","https://openalex.org/W1537592868","https://openalex.org/W2568135170","https://openalex.org/W2470590370","https://openalex.org/W3207192536"],"abstract_inverted_index":{"In":[0],"this":[1,85],"paper,":[2],"Big":[3],"Data":[4],"and":[5,28,36,42,70,138,152],"Deep":[6,31,107],"Learning":[7,108,126],"Techniques":[8],"are":[9,21,30,72,120],"integrated":[10,104],"to":[11,23,61,74,87,110],"improve":[12],"the":[13,49,54,76,89,95,98,112,117,161,168,178],"performance":[14],"of":[15],"intrusion":[16],"detection":[17],"systems.":[18],"Three":[19],"classifiers":[20],"used":[22,73,83],"classify":[24],"network":[25],"traffic":[26],"datasets,":[27,55],"these":[29],"Feed-Forward":[32],"Neural":[33],"Network":[34],"(DNN)":[35],"two":[37],"ensemble":[38,118],"techniques,":[39],"Random":[40],"Forest":[41],"Gradient":[43],"Boosting":[44],"Tree":[45],"(GBT).":[46],"To":[47],"select":[48],"most":[50],"relevant":[51],"attributes":[52],"from":[53],"we":[56],"use":[57],"a":[58,131],"homogeneity":[59],"metric":[60],"evaluate":[62,75,88],"features.":[63],"Two":[64],"recently":[65],"published":[66],"datasets":[67],"UNSW":[68,142],"NB15":[69,143],"CICIDS2017":[71,169],"proposed":[77],"method.":[78],"5-fold":[79],"cross":[80],"validation":[81],"is":[82],"in":[84],"work":[86],"machine":[90],"learning":[91,114],"models.":[92],"We":[93],"implemented":[94,121],"method":[96],"using":[97,122],"distributed":[99],"computing":[100],"environment":[101],"Apache":[102,123],"Spark,":[103],"with":[105,134,145,167,181],"Keras":[106],"Library":[109],"implement":[111],"deep":[113],"technique":[115],"while":[116],"techniques":[119],"Spark":[124],"Machine":[125],"Library.":[127],"The":[128],"results":[129],"show":[130],"high":[132],"accuracy":[133,163,180],"DNN":[135,176],"for":[136,149,154,164,173],"binary":[137,150,165],"multiclass":[139,155,174],"classification":[140,151,166,175],"on":[141],"dataset":[144,170],"accuracies":[146],"at":[147,171],"99.16%":[148],"97.01%":[153],"classification.":[156],"While":[157],"GBT":[158],"classifier":[159],"achieved":[160],"best":[162],"99.99%,":[172],"has":[177],"highest":[179],"99.56%.":[182]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":24},{"year":2024,"cited_by_count":33},{"year":2023,"cited_by_count":41},{"year":2022,"cited_by_count":45},{"year":2021,"cited_by_count":42},{"year":2020,"cited_by_count":28},{"year":2019,"cited_by_count":5}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
