{"id":"https://openalex.org/W3035869188","doi":"https://doi.org/10.1109/ants47819.2019.9117966","title":"A Neural Network based NIDS framework for intrusion detection in contemporary network traffic","display_name":"A Neural Network based NIDS framework for intrusion detection in contemporary network traffic","publication_year":2019,"publication_date":"2019-12-01","ids":{"openalex":"https://openalex.org/W3035869188","doi":"https://doi.org/10.1109/ants47819.2019.9117966","mag":"3035869188"},"language":"en","primary_location":{"id":"doi:10.1109/ants47819.2019.9117966","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ants47819.2019.9117966","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE International Conference on Advanced Networks and Telecommunications Systems (ANTS)","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/A5017476118","display_name":"Basant Subba","orcid":"https://orcid.org/0000-0001-9482-8324"},"institutions":[{"id":"https://openalex.org/I36909309","display_name":"National Institute of Technology Hamirpur","ror":"https://ror.org/01nc8zs04","country_code":"IN","type":"education","lineage":["https://openalex.org/I36909309","https://openalex.org/I4210152752"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Basant Subba","raw_affiliation_strings":["Department of Computer Science & Engineering, National Institute of Technology Hamirpur, Himachal Pradesh, India"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science & Engineering, National Institute of Technology Hamirpur, Himachal Pradesh, India","institution_ids":["https://openalex.org/I36909309"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5017476118"],"corresponding_institution_ids":["https://openalex.org/I36909309"],"apc_list":null,"apc_paid":null,"fwci":0.5305,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.71385017,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"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":0.9994000196456909,"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":0.9991000294685364,"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":0.8015679717063904},{"id":"https://openalex.org/keywords/intrusion-detection-system","display_name":"Intrusion detection system","score":0.60236656665802},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5876399278640747},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5377270579338074},{"id":"https://openalex.org/keywords/hyperparameter","display_name":"Hyperparameter","score":0.533515453338623},{"id":"https://openalex.org/keywords/traffic-classification","display_name":"Traffic classification","score":0.5161594152450562},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5138104557991028},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.5088079571723938},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.47172895073890686},{"id":"https://openalex.org/keywords/constant-false-alarm-rate","display_name":"Constant false alarm rate","score":0.46389344334602356},{"id":"https://openalex.org/keywords/simulated-annealing","display_name":"Simulated annealing","score":0.42314213514328003},{"id":"https://openalex.org/keywords/network-packet","display_name":"Network packet","score":0.2430422604084015},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.20163553953170776}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8015679717063904},{"id":"https://openalex.org/C35525427","wikidata":"https://www.wikidata.org/wiki/Q745881","display_name":"Intrusion detection system","level":2,"score":0.60236656665802},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5876399278640747},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5377270579338074},{"id":"https://openalex.org/C8642999","wikidata":"https://www.wikidata.org/wiki/Q4171168","display_name":"Hyperparameter","level":2,"score":0.533515453338623},{"id":"https://openalex.org/C169988225","wikidata":"https://www.wikidata.org/wiki/Q7832484","display_name":"Traffic classification","level":3,"score":0.5161594152450562},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5138104557991028},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.5088079571723938},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.47172895073890686},{"id":"https://openalex.org/C77052588","wikidata":"https://www.wikidata.org/wiki/Q644307","display_name":"Constant false alarm rate","level":2,"score":0.46389344334602356},{"id":"https://openalex.org/C126980161","wikidata":"https://www.wikidata.org/wiki/Q863783","display_name":"Simulated annealing","level":2,"score":0.42314213514328003},{"id":"https://openalex.org/C158379750","wikidata":"https://www.wikidata.org/wiki/Q214111","display_name":"Network packet","level":2,"score":0.2430422604084015},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.20163553953170776}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ants47819.2019.9117966","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ants47819.2019.9117966","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE International Conference on Advanced Networks and Telecommunications Systems (ANTS)","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":27,"referenced_works":["https://openalex.org/W114517082","https://openalex.org/W405461467","https://openalex.org/W1511622987","https://openalex.org/W1674877186","https://openalex.org/W1973207880","https://openalex.org/W2001107211","https://openalex.org/W2002900768","https://openalex.org/W2004915807","https://openalex.org/W2078868204","https://openalex.org/W2096915403","https://openalex.org/W2099940443","https://openalex.org/W2101234009","https://openalex.org/W2122217421","https://openalex.org/W2150579376","https://openalex.org/W2159294971","https://openalex.org/W2166706236","https://openalex.org/W2169041657","https://openalex.org/W2264833084","https://openalex.org/W2288766236","https://openalex.org/W2296509296","https://openalex.org/W2508613954","https://openalex.org/W2744338514","https://openalex.org/W6637096788","https://openalex.org/W6675354045","https://openalex.org/W6683272254","https://openalex.org/W6684249991","https://openalex.org/W6696294499"],"related_works":["https://openalex.org/W2140186469","https://openalex.org/W4390421286","https://openalex.org/W4280563792","https://openalex.org/W4389724018","https://openalex.org/W4318719684","https://openalex.org/W3183136280","https://openalex.org/W4318559728","https://openalex.org/W2775233965","https://openalex.org/W4360995913","https://openalex.org/W4312193868"],"abstract_inverted_index":{"Most":[0],"of":[1,38,114,141],"the":[2,12,18,29,39,69,115,124,130],"anomaly":[3,55,84],"based":[4,78,118],"Network":[5,77,117],"Intrusion":[6],"Detection":[7],"Systems":[8],"(NIDSs)":[9],"proposed":[10,92,131],"in":[11,57,86],"literature":[13],"have":[14,67],"been":[15],"evaluated":[16],"on":[17,47,123],"legacy":[19],"NSL-KDD":[20,23,48],"dataset.":[21],"The":[22,91],"dataset":[24,49,72,127],"do":[25],"not":[26,51],"truely":[27],"represent":[28],"complex":[30],"data":[31],"patterns":[32],"and":[33,106],"low":[34,150],"footprint":[35],"stealth":[36],"attacks":[37],"contemporary":[40,70,125],"network":[41,60,89,144],"traffic.":[42,61,90],"Therefore,":[43],"NIDS":[44,79,93,119,132],"frameworks":[45],"trained":[46],"are":[50],"well":[52],"suited":[53],"for":[54,81],"detection":[56,85,136],"modern":[58,87,142],"day":[59,88,143],"To":[62],"address":[63],"this":[64],"issue,":[65],"we":[66],"used":[68],"UNSW-NB15":[71,126],"to":[73,109],"train":[74],"a":[75,148],"Neural":[76,116],"framework":[80,94,133],"real":[82],"time":[83],"uses":[95],"convex":[96],"Logistic":[97],"Regression":[98],"cost":[99],"functions":[100],"along":[101],"with":[102],"stochastic":[103],"gradient":[104],"descent":[105],"simulated":[107],"annealing":[108],"fine":[110],"tune":[111],"various":[112],"hyperparameters":[113],"classifier.":[120],"Experimental":[121],"results":[122],"show":[128],"that":[129],"achieves":[134],"high":[135],"rate":[137],"against":[138],"wide":[139],"range":[140],"attacks,":[145],"while":[146],"maintaining":[147],"relatively":[149],"false":[151],"alarm":[152],"rate.":[153]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":3},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
