{"id":"https://openalex.org/W4404030072","doi":"https://doi.org/10.1109/icccnt61001.2024.10725313","title":"An Efficient Approach Using Graphical Neural Network for Network Intrusion Detection System","display_name":"An Efficient Approach Using Graphical Neural Network for Network Intrusion Detection System","publication_year":2024,"publication_date":"2024-06-24","ids":{"openalex":"https://openalex.org/W4404030072","doi":"https://doi.org/10.1109/icccnt61001.2024.10725313"},"language":"en","primary_location":{"id":"doi:10.1109/icccnt61001.2024.10725313","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icccnt61001.2024.10725313","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 15th International Conference on Computing Communication and Networking Technologies (ICCCNT)","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/A5104089364","display_name":"Shailendra Pratap Singh","orcid":"https://orcid.org/0000-0002-2153-9641"},"institutions":[{"id":"https://openalex.org/I3129773123","display_name":"Bennett University","ror":"https://ror.org/00an5hx75","country_code":"IN","type":"education","lineage":["https://openalex.org/I3129773123"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Shailendra Pratap Singh","raw_affiliation_strings":["Bennett University,SCSET,Greater Noida,India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Bennett University,SCSET,Greater Noida,India","institution_ids":["https://openalex.org/I3129773123"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5114511389","display_name":"Bansal Abhay","orcid":null},"institutions":[{"id":"https://openalex.org/I3129773123","display_name":"Bennett University","ror":"https://ror.org/00an5hx75","country_code":"IN","type":"education","lineage":["https://openalex.org/I3129773123"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Bansal Abhay","raw_affiliation_strings":["Bennett University,Dean of Engineering - SCSET & SEAS,Greater Noida,India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Bennett University,Dean of Engineering - SCSET & SEAS,Greater Noida,India","institution_ids":["https://openalex.org/I3129773123"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101059249","display_name":"Akshat Kumar","orcid":"https://orcid.org/0009-0003-9157-2505"},"institutions":[{"id":"https://openalex.org/I3129773123","display_name":"Bennett University","ror":"https://ror.org/00an5hx75","country_code":"IN","type":"education","lineage":["https://openalex.org/I3129773123"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Akshat Kumar","raw_affiliation_strings":["Bennett University,SCSET,Greater Noida,India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Bennett University,SCSET,Greater Noida,India","institution_ids":["https://openalex.org/I3129773123"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5044291511","display_name":"Prakhar Agrawal","orcid":null},"institutions":[{"id":"https://openalex.org/I3129773123","display_name":"Bennett University","ror":"https://ror.org/00an5hx75","country_code":"IN","type":"education","lineage":["https://openalex.org/I3129773123"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Prakhar Agrawal","raw_affiliation_strings":["Bennett University,SCSET,Greater Noida,India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Bennett University,SCSET,Greater Noida,India","institution_ids":["https://openalex.org/I3129773123"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5109695510","display_name":"Druhan Singh","orcid":null},"institutions":[{"id":"https://openalex.org/I3129773123","display_name":"Bennett University","ror":"https://ror.org/00an5hx75","country_code":"IN","type":"education","lineage":["https://openalex.org/I3129773123"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Druhan Singh","raw_affiliation_strings":["Bennett University,SCSET,Greater Noida,India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Bennett University,SCSET,Greater Noida,India","institution_ids":["https://openalex.org/I3129773123"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5108911794","display_name":"Vivashwan Ghosh","orcid":null},"institutions":[{"id":"https://openalex.org/I3129773123","display_name":"Bennett University","ror":"https://ror.org/00an5hx75","country_code":"IN","type":"education","lineage":["https://openalex.org/I3129773123"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Vivashwan Ghosh","raw_affiliation_strings":["Bennett University,SCSET,Greater Noida,India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Bennett University,SCSET,Greater Noida,India","institution_ids":["https://openalex.org/I3129773123"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I3129773123"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"11"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10400","display_name":"Network Security and Intrusion Detection","score":0.9671000242233276,"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":0.9671000242233276,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7940188050270081},{"id":"https://openalex.org/keywords/intrusion-detection-system","display_name":"Intrusion detection system","score":0.7161643505096436},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5528280735015869},{"id":"https://openalex.org/keywords/graphical-model","display_name":"Graphical model","score":0.4487789571285248},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3679320812225342}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7940188050270081},{"id":"https://openalex.org/C35525427","wikidata":"https://www.wikidata.org/wiki/Q745881","display_name":"Intrusion detection system","level":2,"score":0.7161643505096436},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5528280735015869},{"id":"https://openalex.org/C155846161","wikidata":"https://www.wikidata.org/wiki/Q1143367","display_name":"Graphical model","level":2,"score":0.4487789571285248},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3679320812225342}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icccnt61001.2024.10725313","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icccnt61001.2024.10725313","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 15th International Conference on Computing Communication and Networking Technologies (ICCCNT)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":7,"referenced_works":["https://openalex.org/W65242977","https://openalex.org/W1570448133","https://openalex.org/W2042495914","https://openalex.org/W2065028222","https://openalex.org/W2085305295","https://openalex.org/W2150847526","https://openalex.org/W3214373139"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2109986081","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890"],"abstract_inverted_index":{"This":[0],"investigation":[1],"is":[2,70,112],"centered":[3],"on":[4,11,121,135,175],"addressing":[5],"the":[6,25,36,92,103,110,190],"imperative":[7],"for":[8,38,58,80,89,127],"a":[9,22,39,53,95,123,136],"System":[10,101],"Intrusion":[12,99],"Detection":[13,100],"capable":[14],"of":[15,29,71,94,199],"accurately":[16],"discerning":[17],"anomalies":[18],"and":[19,27,84,97,107,147,165,181,186],"attacks":[20,76,108],"within":[21,109],"system.":[23,130],"As":[24],"frequency":[26],"severity":[28],"network":[30,59,68,128],"intrusion":[31,60,75,129],"incidents":[32],"continue":[33],"to":[34,47,105],"rise,":[35],"necessity":[37],"robust":[40,96],"IDS":[41],"becomes":[42],"increasingly":[43],"pronounced.":[44],"To":[45,152],"contribute":[46],"this":[48,116],"endeavor,":[49],"we":[50,118,155],"have":[51],"devised":[52],"classification":[54,125],"model":[55,126,134],"specifically":[56],"designed":[57],"detection,":[61],"leveraging":[62],"advanced":[63],"techniques.In":[64],"today\u2019s":[65],"interconnected":[66],"landscape,":[67],"security":[69],"utmost":[72],"importance.":[73],"Network":[74],"pose":[77],"formidable":[78],"challenges":[79],"all":[81],"computer":[82],"networks":[83],"can":[85],"incur":[86],"substantial":[87],"costs":[88],"manufacturers.":[90],"Consequently,":[91],"significance":[93],"dependable":[98],"with":[102],"ability":[104],"identifying":[106],"system":[111],"steadily":[113],"increasing.":[114],"In":[115],"research,":[117],"primarily":[119],"focused":[120],"developing":[122],"multinomial":[124],"We":[131,169],"trained":[132],"our":[133,184],"dataset":[137],"including":[138],"various":[139],"attack":[140],"types,":[141],"such":[142,159],"as":[143,160],"R2L,":[144],"PROBE,":[145],"DOS,":[146],"U2R,":[148],"alongside":[149],"typical":[150],"attacks.":[151],"achieve":[153],"it,":[154],"explored":[156],"ML":[157],"methods":[158],"decision":[161],"trees,":[162],"k-nearest":[163],"neighbors,":[164],"random":[166],"forest":[167],"classifiers.":[168],"measured":[170],"each":[171],"algorithm\u2019s":[172],"performance":[173],"based":[174],"metrics":[176],"like":[177],"accuracy,":[178],"precision,":[179],"recall,":[180],"F1-score.":[182],"Notably,":[183],"research":[185],"numbers":[187],"indicate":[188],"that":[189],"GNN":[191],"algorithm":[192],"outperformed":[193],"others,":[194],"achieving":[195],"an":[196],"accuracy":[197],"rate":[198],"$91":[200],"\\%$.":[201]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}