{"id":"https://openalex.org/W4379932688","doi":"https://doi.org/10.1145/3590837.3590901","title":"An Effect of Stacked CNN for Network Intrusion Detection System","display_name":"An Effect of Stacked CNN for Network Intrusion Detection System","publication_year":2022,"publication_date":"2022-12-23","ids":{"openalex":"https://openalex.org/W4379932688","doi":"https://doi.org/10.1145/3590837.3590901"},"language":"en","primary_location":{"id":"doi:10.1145/3590837.3590901","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3590837.3590901","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 4th International Conference on Information Management & Machine Intelligence","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/A5045797071","display_name":"Pankaj Rahi","orcid":"https://orcid.org/0000-0003-1315-2727"},"institutions":[{"id":"https://openalex.org/I4210126659","display_name":"Poornima University","ror":"https://ror.org/03gnqp653","country_code":"IN","type":"education","lineage":["https://openalex.org/I4210126659"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Pankaj Rahi","raw_affiliation_strings":["Deptt. of Artificial Intelligence and Data Science, Poornima Institute of Engineering and Technology, Jaipur, India"],"raw_orcid":"https://orcid.org/0000-0003-1315-2727","affiliations":[{"raw_affiliation_string":"Deptt. of Artificial Intelligence and Data Science, Poornima Institute of Engineering and Technology, Jaipur, India","institution_ids":["https://openalex.org/I4210126659"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014681245","display_name":"Monika Dandotiya","orcid":"https://orcid.org/0000-0002-5501-4210"},"institutions":[{"id":"https://openalex.org/I4210126659","display_name":"Poornima University","ror":"https://ror.org/03gnqp653","country_code":"IN","type":"education","lineage":["https://openalex.org/I4210126659"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Monika Dandotiya","raw_affiliation_strings":["Computer Science & Engineering, Poornima University, India"],"raw_orcid":"https://orcid.org/0000-0002-5501-4210","affiliations":[{"raw_affiliation_string":"Computer Science & Engineering, Poornima University, India","institution_ids":["https://openalex.org/I4210126659"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113392386","display_name":"A. Anushya","orcid":null},"institutions":[{"id":"https://openalex.org/I4210126659","display_name":"Poornima University","ror":"https://ror.org/03gnqp653","country_code":"IN","type":"education","lineage":["https://openalex.org/I4210126659"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"A. Anushya","raw_affiliation_strings":["Computer Science & Engineering, POORNIMA UNIVERSITY, India"],"raw_orcid":"https://orcid.org/0000-0002-5712-4931","affiliations":[{"raw_affiliation_string":"Computer Science & Engineering, POORNIMA UNIVERSITY, India","institution_ids":["https://openalex.org/I4210126659"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046277894","display_name":"Ajay Khunteta","orcid":"https://orcid.org/0000-0002-5335-9434"},"institutions":[{"id":"https://openalex.org/I4210126659","display_name":"Poornima University","ror":"https://ror.org/03gnqp653","country_code":"IN","type":"education","lineage":["https://openalex.org/I4210126659"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Ajay Khunteta","raw_affiliation_strings":["Computer Science & Engineering, POORNIMA UNIVERSITY JAIPUR, India"],"raw_orcid":"https://orcid.org/0000-0002-5335-9434","affiliations":[{"raw_affiliation_string":"Computer Science & Engineering, POORNIMA UNIVERSITY JAIPUR, India","institution_ids":["https://openalex.org/I4210126659"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5043368187","display_name":"Pankaj Agarwal","orcid":"https://orcid.org/0000-0002-1027-2419"},"institutions":[{"id":"https://openalex.org/I4210114149","display_name":"KR Mangalam University","ror":"https://ror.org/026b9sf88","country_code":"IN","type":"education","lineage":["https://openalex.org/I4210114149"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Pankaj Agarwal","raw_affiliation_strings":["Computer Science & Engineering, K.R. Manglam University, Gurugram, Haryana, India, India"],"raw_orcid":"https://orcid.org/0000-0002-1027-2419","affiliations":[{"raw_affiliation_string":"Computer Science & Engineering, K.R. Manglam University, Gurugram, Haryana, India, India","institution_ids":["https://openalex.org/I4210114149"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5045797071"],"corresponding_institution_ids":["https://openalex.org/I4210126659"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.23292946,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"9"},"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":0.9983000159263611,"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":0.9973000288009644,"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":0.8128362894058228},{"id":"https://openalex.org/keywords/intrusion-detection-system","display_name":"Intrusion detection system","score":0.7812181711196899},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6394623517990112},{"id":"https://openalex.org/keywords/false-positive-paradox","display_name":"False positive paradox","score":0.6305254101753235},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5835834741592407},{"id":"https://openalex.org/keywords/network-security","display_name":"Network security","score":0.5801987648010254},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5464379787445068},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4897639751434326},{"id":"https://openalex.org/keywords/big-data","display_name":"Big data","score":0.4791702330112457},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.44787225127220154},{"id":"https://openalex.org/keywords/encryption","display_name":"Encryption","score":0.4452711045742035},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4441637694835663},{"id":"https://openalex.org/keywords/feature-engineering","display_name":"Feature engineering","score":0.42010048031806946},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.25826773047447205}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8128362894058228},{"id":"https://openalex.org/C35525427","wikidata":"https://www.wikidata.org/wiki/Q745881","display_name":"Intrusion detection system","level":2,"score":0.7812181711196899},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6394623517990112},{"id":"https://openalex.org/C64869954","wikidata":"https://www.wikidata.org/wiki/Q1859747","display_name":"False positive paradox","level":2,"score":0.6305254101753235},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5835834741592407},{"id":"https://openalex.org/C182590292","wikidata":"https://www.wikidata.org/wiki/Q989632","display_name":"Network security","level":2,"score":0.5801987648010254},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5464379787445068},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4897639751434326},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.4791702330112457},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.44787225127220154},{"id":"https://openalex.org/C148730421","wikidata":"https://www.wikidata.org/wiki/Q141090","display_name":"Encryption","level":2,"score":0.4452711045742035},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4441637694835663},{"id":"https://openalex.org/C2778827112","wikidata":"https://www.wikidata.org/wiki/Q22245680","display_name":"Feature engineering","level":3,"score":0.42010048031806946},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.25826773047447205},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3590837.3590901","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3590837.3590901","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 4th International Conference on Information Management & Machine Intelligence","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":23,"referenced_works":["https://openalex.org/W2090777335","https://openalex.org/W2144317842","https://openalex.org/W2157069634","https://openalex.org/W2418891196","https://openalex.org/W2546923044","https://openalex.org/W2576070019","https://openalex.org/W2605902561","https://openalex.org/W2807319534","https://openalex.org/W2924372725","https://openalex.org/W2983194513","https://openalex.org/W3005805195","https://openalex.org/W3008004464","https://openalex.org/W3015665983","https://openalex.org/W3025552039","https://openalex.org/W3042722309","https://openalex.org/W3080177360","https://openalex.org/W3100958451","https://openalex.org/W3109901447","https://openalex.org/W3129232608","https://openalex.org/W3133493967","https://openalex.org/W3136161312","https://openalex.org/W4251961722","https://openalex.org/W4352975933"],"related_works":["https://openalex.org/W2061466315","https://openalex.org/W2376886931","https://openalex.org/W2010561419","https://openalex.org/W2374845301","https://openalex.org/W2351448539","https://openalex.org/W1977863481","https://openalex.org/W2384741105","https://openalex.org/W2185594426","https://openalex.org/W3157271777","https://openalex.org/W2377372927"],"abstract_inverted_index":{"The":[0,172],"Intrusion":[1,163],"Detection":[2],"System":[3],"(IDS)":[4],"is":[5,71],"a":[6,37,54,111],"vital":[7],"component":[8],"of":[9,20,26,40,57,80,100,104],"network":[10,28,30,84,106,121],"security":[11,85],"since":[12],"it":[13],"recognizes":[14],"&":[15,50,91,180],"inhibits":[16],"hostile":[17],"behavior.":[18],"Because":[19],"the":[21,27,78,102,143],"dynamic":[22],"and":[23,132,142,187],"time-varying":[24],"nature":[25],"environment,":[29],"intrusion":[31],"data":[32,81,92],"are":[33,96,127,189],"drowned":[34],"out":[35],"by":[36,129,183],"big":[38],"number":[39],"normal":[41],"samples,":[42],"resulting":[43],"in":[44,73],"inadequate":[45],"samples":[46],"for":[47,145,161],"model":[48],"training":[49],"detection":[51,140,170],"outcomes":[52],"with":[53,120],"high":[55],"percentage":[56],"false":[58],"positives.":[59],"An":[60],"ID":[61,125],"(Intrusion":[62],"Detection)":[63,164],"approach":[64],"based":[65],"on":[66,185],"stacked":[67,166],"Convolutional":[68],"Neural":[69],"Networks":[70],"discussed":[72],"this":[74,177],"work":[75],"to":[76,115,118,168],"solve":[77],"issue":[79],"imbalance.":[82],"Modern":[83],"requires":[86],"more":[87],"than":[88,191],"conventional":[89],"firewalls":[90],"encryption":[93],"technologies,":[94],"which":[95,149],"no":[97],"longer":[98],"capable":[99],"meeting":[101],"demands":[103],"modern":[105],"security.":[107],"It":[108],"has":[109],"as":[110],"consequence":[112],"been":[113],"advocated":[114],"use":[116],"IDSs":[117],"cope":[119],"threats.":[122],"Recent":[123],"mainstream":[124],"methods":[126],"helped":[128],"Machine":[130],"Learning":[131,159],"Deep":[133],"Learning;":[134],"however,":[135],"they":[136],"suffer":[137],"from":[138],"poor":[139],"rates":[141],"requirement":[144],"considerable":[146],"feature":[147],"engineering,":[148],"makes":[150],"them":[151],"less":[152],"effective.":[153],"This":[154],"research":[155],"presents":[156],"DLNID":[157],"(Deep":[158],"Model":[160],"Network":[162],"utilizing":[165],"CNN":[167,184],"improve":[169],"accuracy.":[171],"experimental":[173],"results":[174],"demonstrate":[175],"that":[176],"model's":[178],"accuracy":[179],"F1-":[181],"score":[182],"NSL-KDD":[186],"UNS":[188],"better":[190],"CNN.":[192]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}