{"id":"https://openalex.org/W4408954712","doi":"https://doi.org/10.23919/icact63878.2025.10936304","title":"An Enhanced Intrusion Detection Model with FeedForward Neural Network Classifier","display_name":"An Enhanced Intrusion Detection Model with FeedForward Neural Network Classifier","publication_year":2025,"publication_date":"2025-02-16","ids":{"openalex":"https://openalex.org/W4408954712","doi":"https://doi.org/10.23919/icact63878.2025.10936304"},"language":"en","primary_location":{"id":"doi:10.23919/icact63878.2025.10936304","is_oa":false,"landing_page_url":"https://doi.org/10.23919/icact63878.2025.10936304","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 27th International Conference on Advanced Communications Technology (ICACT)","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/A5115829229","display_name":"Asadov Amirjon","orcid":null},"institutions":[{"id":"https://openalex.org/I35928602","display_name":"Kyung Hee University","ror":"https://ror.org/01zqcg218","country_code":"KR","type":"education","lineage":["https://openalex.org/I35928602"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Asadov Amirjon","raw_affiliation_strings":["Kyung Hee University,Department of Computer Science and Engineering,Yongin,South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Kyung Hee University,Department of Computer Science and Engineering,Yongin,South Korea","institution_ids":["https://openalex.org/I35928602"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088612895","display_name":"Mrityunjoy Gain","orcid":"https://orcid.org/0000-0002-1771-0100"},"institutions":[{"id":"https://openalex.org/I35928602","display_name":"Kyung Hee University","ror":"https://ror.org/01zqcg218","country_code":"KR","type":"education","lineage":["https://openalex.org/I35928602"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Mrityunjoy Gain","raw_affiliation_strings":["Kyung Hee University,Department of Artificial Intelligence,Yongin,South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Kyung Hee University,Department of Artificial Intelligence,Yongin,South Korea","institution_ids":["https://openalex.org/I35928602"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072190484","display_name":"K. Kim","orcid":null},"institutions":[{"id":"https://openalex.org/I35928602","display_name":"Kyung Hee University","ror":"https://ror.org/01zqcg218","country_code":"KR","type":"education","lineage":["https://openalex.org/I35928602"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Keon Oh Kim","raw_affiliation_strings":["Kyung Hee University,Department of Computer Science and Engineering,Yongin,South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Kyung Hee University,Department of Computer Science and Engineering,Yongin,South Korea","institution_ids":["https://openalex.org/I35928602"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5034052371","display_name":"Choong Seon Hong","orcid":"https://orcid.org/0000-0003-3484-7333"},"institutions":[{"id":"https://openalex.org/I35928602","display_name":"Kyung Hee University","ror":"https://ror.org/01zqcg218","country_code":"KR","type":"education","lineage":["https://openalex.org/I35928602"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Choong Seon Hong","raw_affiliation_strings":["Kyung Hee University,Department of Computer Science and Engineering,Yongin,South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Kyung Hee University,Department of Computer Science and Engineering,Yongin,South Korea","institution_ids":["https://openalex.org/I35928602"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I35928602"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"88","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/T11241","display_name":"Advanced Malware Detection Techniques","score":0.9951000213623047,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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":0.9894000291824341,"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":0.7505671977996826},{"id":"https://openalex.org/keywords/feedforward-neural-network","display_name":"Feedforward neural network","score":0.6476373672485352},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.6264663338661194},{"id":"https://openalex.org/keywords/intrusion-detection-system","display_name":"Intrusion detection system","score":0.5853129625320435},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5314199924468994},{"id":"https://openalex.org/keywords/feed-forward","display_name":"Feed forward","score":0.5196039080619812},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5083176493644714},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3673873245716095},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3638027310371399},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.11517053842544556},{"id":"https://openalex.org/keywords/control-engineering","display_name":"Control engineering","score":0.06796342134475708}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7505671977996826},{"id":"https://openalex.org/C47702885","wikidata":"https://www.wikidata.org/wiki/Q5441227","display_name":"Feedforward neural network","level":3,"score":0.6476373672485352},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6264663338661194},{"id":"https://openalex.org/C35525427","wikidata":"https://www.wikidata.org/wiki/Q745881","display_name":"Intrusion detection system","level":2,"score":0.5853129625320435},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5314199924468994},{"id":"https://openalex.org/C38858127","wikidata":"https://www.wikidata.org/wiki/Q5441228","display_name":"Feed forward","level":2,"score":0.5196039080619812},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5083176493644714},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3673873245716095},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3638027310371399},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.11517053842544556},{"id":"https://openalex.org/C133731056","wikidata":"https://www.wikidata.org/wiki/Q4917288","display_name":"Control engineering","level":1,"score":0.06796342134475708}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.23919/icact63878.2025.10936304","is_oa":false,"landing_page_url":"https://doi.org/10.23919/icact63878.2025.10936304","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 27th International Conference on Advanced Communications Technology (ICACT)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Climate action","id":"https://metadata.un.org/sdg/13","score":0.4300000071525574}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W3000307855","https://openalex.org/W3010704846","https://openalex.org/W4211016117","https://openalex.org/W4211201838","https://openalex.org/W4285268941","https://openalex.org/W4288038854","https://openalex.org/W4297094626","https://openalex.org/W4313378981","https://openalex.org/W4387682066","https://openalex.org/W4388938439","https://openalex.org/W4389428576","https://openalex.org/W4394862991","https://openalex.org/W4400322826","https://openalex.org/W4400411463","https://openalex.org/W4400737507","https://openalex.org/W4404740100"],"related_works":["https://openalex.org/W2115072676","https://openalex.org/W2357447513","https://openalex.org/W4311212821","https://openalex.org/W1529660427","https://openalex.org/W2378845890","https://openalex.org/W2102065768","https://openalex.org/W4390752998","https://openalex.org/W2158578859","https://openalex.org/W2358123629","https://openalex.org/W4391020207"],"abstract_inverted_index":{"A":[0],"major":[1],"obstacle":[2],"in":[3,142,147,159,174],"the":[4,62,118,154],"face":[5],"of":[6,76,96,98,134,156],"increasingly":[7],"complex":[8],"cyberattacks":[9],"is":[10,86,109],"network":[11,28,34,160,203],"security.":[12],"Proactive":[13],"security":[14,161,204],"measures":[15,151],"require":[16],"effective":[17],"intrusion":[18,193],"detection":[19,36,177,194],"systems":[20,195],"(IDS)":[21],"that":[22,65,152,182],"can":[23,187],"precisely":[24],"classify":[25],"and":[26,37,80,90,103,114,128,166,196],"categorize":[27],"threats.":[29],"In":[30],"order":[31],"to":[32,124,190,200],"improve":[33,129],"attack":[35],"classification,":[38],"this":[39],"paper":[40],"proposes":[41],"a":[42,46,59,74,171,198],"reliable":[43],"method":[44],"utilizing":[45],"Feedforward":[47],"Neural":[48],"Network":[49],"(FFNN)":[50],"supplemented":[51],"with":[52,101],"Adaptive":[53],"Synthetic":[54],"(ADASYN)":[55],"sampling.":[56],"We":[57],"created":[58],"model":[60,85,119,144],"using":[61,73],"UNSW-NB15":[63],"dataset":[64],"efficiently":[66],"handles":[67],"high-dimensional":[68],"datasets":[69],"by":[70,111,138],"preprocessing":[71],"data":[72,137],"combination":[75],"polynomial":[77],"feature":[78],"transformation":[79],"one-hot":[81],"encoding.":[82],"The":[83,132,179],"FFNN":[84],"optimized":[87],"for":[88],"binary":[89],"multi-class":[91],"classification":[92,130,167],"tasks.":[93],"It":[94],"consists":[95],"layers":[97],"dense":[99],"units":[100],"dropout":[102],"batch":[104],"normalization.":[105],"Our":[106],"method\u2019s":[107],"efficacy":[108],"proven":[110],"rigorous":[112],"training":[113,136],"validation":[115],"procedures,":[116],"where":[117],"significantly":[120],"increased":[121],"its":[122],"ability":[123],"handle":[125],"class":[126],"imbalances":[127],"accuracy.":[131],"synthesis":[133],"new":[135],"ADASYN":[139],"was":[140],"crucial":[141],"improving":[143],"performance,":[145],"especially":[146],"underrepresented":[148],"classes.":[149],"Evaluation":[150],"highlight":[153],"potential":[155],"deep":[157],"learning":[158,185],"applications":[162],"are":[163],"ROC-AUC":[164],"scores":[165],"reports,":[168],"which":[169],"show":[170,181],"notable":[172],"improvement":[173],"our":[175],"IDS\u2019s":[176],"capabilities.":[178],"results":[180],"advanced":[183],"machine":[184],"techniques":[186],"be":[188],"used":[189],"enhance":[191],"conventional":[192],"provide":[197],"means":[199],"build":[201],"stronger":[202],"designs.":[205]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
