{"id":"https://openalex.org/W7130438702","doi":"https://doi.org/10.1109/iconstem65670.2025.11374686","title":"Hybrid IDS System with Neural Algorithmic Reasoning and Evolutionary Feature Selection for Internet-Based Optimized Communication","display_name":"Hybrid IDS System with Neural Algorithmic Reasoning and Evolutionary Feature Selection for Internet-Based Optimized Communication","publication_year":2025,"publication_date":"2025-11-06","ids":{"openalex":"https://openalex.org/W7130438702","doi":"https://doi.org/10.1109/iconstem65670.2025.11374686"},"language":"en","primary_location":{"id":"doi:10.1109/iconstem65670.2025.11374686","doi":"https://doi.org/10.1109/iconstem65670.2025.11374686","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iconstem65670.2025.11374686","pdf_url":null,"source":{"id":"https://openalex.org/S7407086778","display_name":"International Conference on Science Technology Engineering and Mathematics (ICONSTEM)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 Tenth International Conference on Science Technology Engineering and Mathematics (ICONSTEM)","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","is_traditional":true,"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/A5050372698","display_name":"Sugunakar Mamidala","orcid":"https://orcid.org/0000-0002-1890-8573","observed_orcids":["https://orcid.org/0000-0002-1890-8573"]},"institutions":[{"id":"https://openalex.org/I138876546","display_name":"Vels University","ror":"https://ror.org/00tscx035","country_code":"IN","type":"education","lineage":["https://openalex.org/I138876546"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Sugunakar Mamidala","raw_affiliation_strings":["Vels Institute of Science, Technology & Advanced Studies(VISTAS),Department of Electronics and Communication Engineering,Chennai,India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Vels Institute of Science, Technology & Advanced Studies(VISTAS),Department of Electronics and Communication Engineering,Chennai,India","institution_ids":["https://openalex.org/I138876546"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5118824402","display_name":"Ibrahim Mohammad Khrais","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ibrahim Mohammad Khrais","raw_affiliation_strings":["QIS College of Engineering and Technology,Department of MCA,Ongole,AndhraPradesh,India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"QIS College of Engineering and Technology,Department of MCA,Ongole,AndhraPradesh,India","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126284634","display_name":"Sayana Kondalarao","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I153687341","display_name":"Zarqa University","ror":"https://ror.org/01wf1es90","country_code":"JO","type":"education","lineage":["https://openalex.org/I153687341"]}],"countries":["JO"],"is_corresponding":false,"raw_author_name":"Sayana Kondalarao","raw_affiliation_strings":["Faculty of Economics and Administrative Sciences, Islamic Banks, Zarqa University,Zarqa,Jordan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Economics and Administrative Sciences, Islamic Banks, Zarqa University,Zarqa,Jordan","institution_ids":["https://openalex.org/I153687341"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126329289","display_name":"N Sirisha","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"N Sirisha","raw_affiliation_strings":["QIS College of Engineering and Technology,Department of CSE,Vengamukkapalem,AndhraPradesh,India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"QIS College of Engineering and Technology,Department of CSE,Vengamukkapalem,AndhraPradesh,India","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5089835074","display_name":"Vijilius Helena Raj","orcid":"https://orcid.org/0000-0002-5505-0617","observed_orcids":["https://orcid.org/0000-0002-5505-0617"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Vijilius Helena Raj","raw_affiliation_strings":["MLR Institute of Technology,Department of CSE,Hyderabad,Telangana,India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"MLR Institute of Technology,Department of CSE,Hyderabad,Telangana,India","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5121528308","display_name":"Ramya M","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ramya M","raw_affiliation_strings":["Panimalar Engineering College,Department of ECE,Chennai,India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Panimalar Engineering College,Department of ECE,Chennai,India","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.0,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"7"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10400","display_name":"Network Security and Intrusion Detection","score":0.9990000128746033,"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":0.9990000128746033,"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/T12326","display_name":"Network Packet Processing and Optimization","score":0.00019999999494757503,"subfield":{"id":"https://openalex.org/subfields/1708","display_name":"Hardware and Architecture"},"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/T12391","display_name":"Artificial Immune Systems Applications","score":0.00019999999494757503,"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/intrusion-detection-systems","display_name":"intrusion detection systems","score":0.9340000152587891},{"id":"https://openalex.org/keywords/industrial-internet-of-things-security","display_name":"Industrial Internet of Things security","score":0.8989999890327454},{"id":"https://openalex.org/keywords/evolutionary-feature-selection","display_name":"evolutionary feature selection","score":0.9639999866485596},{"id":"https://openalex.org/keywords/grey-wolf-optimizer","display_name":"grey wolf optimizer","score":0.7799999713897705},{"id":"https://openalex.org/keywords/genetic-algorithm-feature-selection","display_name":"genetic algorithm feature selection","score":0.6880000233650208},{"id":"https://openalex.org/keywords/transfer-learning","display_name":"transfer learning","score":0.7940000295639038},{"id":"https://openalex.org/keywords/convolutional-neural-networks","display_name":"convolutional neural networks","score":0.6880000233650208},{"id":"https://openalex.org/keywords/lstm","display_name":"LSTM","score":0.6710000038146973},{"id":"https://openalex.org/keywords/unknown-attack-detection","display_name":"unknown attack detection","score":0.9589999914169312},{"id":"https://openalex.org/keywords/network-traffic-classification","display_name":"network traffic classification","score":0.6449999809265137}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7770000100135803},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7087000012397766},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5551999807357788},{"id":"https://openalex.org/C35525427","wikidata":"https://www.wikidata.org/wiki/Q745881","display_name":"Intrusion detection system","level":2,"score":0.5508000254631042},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.522599995136261},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.4921000003814697},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.4799000024795532},{"id":"https://openalex.org/C152124472","wikidata":"https://www.wikidata.org/wiki/Q1204361","display_name":"Redundancy (engineering)","level":2,"score":0.47350001335144043},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.4462999999523163},{"id":"https://openalex.org/C8642999","wikidata":"https://www.wikidata.org/wiki/Q4171168","display_name":"Hyperparameter","level":2,"score":0.41429999470710754},{"id":"https://openalex.org/C159149176","wikidata":"https://www.wikidata.org/wiki/Q14489129","display_name":"Evolutionary algorithm","level":2,"score":0.37310001254081726},{"id":"https://openalex.org/C8880873","wikidata":"https://www.wikidata.org/wiki/Q187787","display_name":"Genetic algorithm","level":2,"score":0.35600000619888306},{"id":"https://openalex.org/C2779990667","wikidata":"https://www.wikidata.org/wiki/Q5953266","display_name":"Hybrid neural network","level":3,"score":0.3458000123500824},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.3427000045776367},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3334999978542328},{"id":"https://openalex.org/C105902424","wikidata":"https://www.wikidata.org/wiki/Q1197129","display_name":"Evolutionary computation","level":2,"score":0.3303999900817871},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.321399986743927},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.29330000281333923},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.2824000120162964},{"id":"https://openalex.org/C117241572","wikidata":"https://www.wikidata.org/wiki/Q5192379","display_name":"Cuckoo search","level":3,"score":0.27459999918937683},{"id":"https://openalex.org/C89288958","wikidata":"https://www.wikidata.org/wiki/Q7301504","display_name":"Reasoning system","level":2,"score":0.26750001311302185},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.26649999618530273}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iconstem65670.2025.11374686","doi":"https://doi.org/10.1109/iconstem65670.2025.11374686","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iconstem65670.2025.11374686","pdf_url":null,"source":{"id":"https://openalex.org/S7407086778","display_name":"International Conference on Science Technology Engineering and Mathematics (ICONSTEM)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 Tenth International Conference on Science Technology Engineering and Mathematics (ICONSTEM)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9","score":0.6773999929428101}],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W3162999172","https://openalex.org/W4298624898","https://openalex.org/W4324144118","https://openalex.org/W4386747333","https://openalex.org/W4387168854","https://openalex.org/W4387732479","https://openalex.org/W4388023739","https://openalex.org/W4389727067","https://openalex.org/W4401623625","https://openalex.org/W4402700982","https://openalex.org/W4403383940","https://openalex.org/W4403570857","https://openalex.org/W4405322220"],"related_works":["https://openalex.org/W7166323091","https://openalex.org/W7140659711","https://openalex.org/W4412787150","https://openalex.org/W4410762268","https://openalex.org/W7172536688","https://openalex.org/W4388626146","https://openalex.org/W4362486885","https://openalex.org/W4410191145","https://openalex.org/W7163921834","https://openalex.org/W7215931159"],"abstract_inverted_index":{"To":[0,106],"improve":[1],"security":[2],"in":[3],"Industrial":[4],"Internet":[5],"of":[6,87,113],"Things":[7],"(IIoT)":[8],"environments":[9],"within":[10],"Industry":[11],"4.0,":[12],"we":[13],"developed":[14],"a":[15,122],"HINEIO":[16,109],"is":[17],"Hybrid":[18],"IDS":[19],"with":[20],"Neural":[21,51,91],"Reasoning":[22,93],"and":[23,40,54,99,120,132,144,153],"Evolutionary":[24],"FS":[25],"for":[26,126],"IoT":[27],"Security.":[28],"A":[29,48,90],"multistage":[30],"hybrid":[31],"framework":[32],"that":[33],"combines":[34],"optimized":[35],"deep":[36],"learning,":[37],"evolutionary":[38],"computation,":[39],"hierarchical":[41,103],"reasoning":[42],"to":[43,57,73,140],"enhance":[44,107],"intrusion":[45],"detection":[46,86],"accuracy.":[47],"pretrained":[49],"Convolutional":[50],"Network":[52],"(CNN)":[53],"transfer":[55],"learning":[56],"extract":[58],"features":[59],"from":[60],"IIoT":[61],"network":[62],"traffic":[63],"while":[64],"tuning":[65],"essential":[66],"hyperparameters":[67],"using":[68,102],"Grey":[69],"Wolf":[70],"Optimization":[71],"(GWO)":[72],"mitigate":[74],"overfitting.":[75],"Long":[76],"Short-Term":[77],"Memory":[78],"(LSTM)":[79],"layers":[80],"capture":[81],"temporal":[82],"dependencies,":[83],"facilitating":[84],"the":[85],"complex":[88],"cyberattacks.":[89],"Algorithmic":[92],"(NAR)":[94],"pipeline":[95],"classifies":[96],"both":[97],"known":[98],"new":[100],"attacks":[101,115],"inference":[104],"structures.":[105],"detection,":[108],"distinguishes":[110],"between":[111],"types":[112],"zero-day":[114],"by":[116],"analyzing":[117],"reclassification":[118],"patterns":[119],"employs":[121],"Genetic":[123],"Algorithm":[124],"(GA)":[125],"effective":[127],"feature":[128],"selection,":[129],"minimizing":[130],"redundancy":[131],"maximizing":[133],"diversity.":[134],"The":[135],"simulation":[136],"parameters":[137],"were":[138],"used":[139],"calculate":[141],"HINEIO,":[142],"training":[143],"testing":[145],"average":[146],"value":[147],"analysis,":[148],"accuracy,":[149],"loss,":[150],"precision,":[151],"recall":[152],"computational":[154],"time.":[155]},"counts_by_year":[],"updated_date":"2026-11-10T11:39:43.021295","created_date":"2026-02-19T00:00:00"}
