{"id":"https://openalex.org/W7130574528","doi":"https://doi.org/10.1109/fllm67465.2025.11391161","title":"Using RNN to detect DDoS attack based on P4 switches","display_name":"Using RNN to detect DDoS attack based on P4 switches","publication_year":2025,"publication_date":"2025-11-25","ids":{"openalex":"https://openalex.org/W7130574528","doi":"https://doi.org/10.1109/fllm67465.2025.11391161"},"language":null,"primary_location":{"id":"doi:10.1109/fllm67465.2025.11391161","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fllm67465.2025.11391161","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 3rd International Conference on Foundation and Large Language Models (FLLM)","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/A5125116488","display_name":"Pei-Ying Huang","orcid":null},"institutions":[{"id":"https://openalex.org/I154864474","display_name":"National Taiwan University of Science and Technology","ror":"https://ror.org/00q09pe49","country_code":"TW","type":"education","lineage":["https://openalex.org/I154864474"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Pei-Ying Huang","raw_affiliation_strings":["National Taiwan University of Science and Technology,Dept. of Computer Science and Information Engineering,Taipei,Taiwan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Taiwan University of Science and Technology,Dept. of Computer Science and Information Engineering,Taipei,Taiwan","institution_ids":["https://openalex.org/I154864474"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5054582705","display_name":"Shan-Hsiang Shen","orcid":"https://orcid.org/0000-0002-2865-6760"},"institutions":[{"id":"https://openalex.org/I154864474","display_name":"National Taiwan University of Science and Technology","ror":"https://ror.org/00q09pe49","country_code":"TW","type":"education","lineage":["https://openalex.org/I154864474"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Shan-Hsiang Shen","raw_affiliation_strings":["National Taiwan University of Science and Technology,Dept. of Computer Science and Information Engineering,Taipei,Taiwan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Taiwan University of Science and Technology,Dept. of Computer Science and Information Engineering,Taipei,Taiwan","institution_ids":["https://openalex.org/I154864474"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I154864474"],"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":"886","last_page":"887"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10400","display_name":"Network Security and Intrusion Detection","score":0.6915000081062317,"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":0.6915000081062317,"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/T10714","display_name":"Software-Defined Networks and 5G","score":0.10490000247955322,"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/T11598","display_name":"Internet Traffic Analysis and Secure E-voting","score":0.06270000338554382,"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/denial-of-service-attack","display_name":"Denial-of-service attack","score":0.8582000136375427},{"id":"https://openalex.org/keywords/intrusion-detection-system","display_name":"Intrusion detection system","score":0.6574000120162964},{"id":"https://openalex.org/keywords/recurrent-neural-network","display_name":"Recurrent neural network","score":0.6154999732971191},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.400299996137619},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.39590001106262207},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.3702000081539154},{"id":"https://openalex.org/keywords/server","display_name":"Server","score":0.3467000126838684}],"concepts":[{"id":"https://openalex.org/C38822068","wikidata":"https://www.wikidata.org/wiki/Q131406","display_name":"Denial-of-service attack","level":3,"score":0.8582000136375427},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7821999788284302},{"id":"https://openalex.org/C35525427","wikidata":"https://www.wikidata.org/wiki/Q745881","display_name":"Intrusion detection system","level":2,"score":0.6574000120162964},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.6154999732971191},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.413100004196167},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.400299996137619},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.39590001106262207},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.3702000081539154},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3625999987125397},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.34929999709129333},{"id":"https://openalex.org/C93996380","wikidata":"https://www.wikidata.org/wiki/Q44127","display_name":"Server","level":2,"score":0.3467000126838684},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.3456000089645386},{"id":"https://openalex.org/C182590292","wikidata":"https://www.wikidata.org/wiki/Q989632","display_name":"Network security","level":2,"score":0.3260999917984009},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.3176000118255615},{"id":"https://openalex.org/C137524506","wikidata":"https://www.wikidata.org/wiki/Q2247688","display_name":"Anomaly-based intrusion detection system","level":3,"score":0.311599999666214},{"id":"https://openalex.org/C95713431","wikidata":"https://www.wikidata.org/wiki/Q631425","display_name":"Vulnerability (computing)","level":2,"score":0.3052999973297119},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2964000105857849},{"id":"https://openalex.org/C158251709","wikidata":"https://www.wikidata.org/wiki/Q354025","display_name":"Intrusion","level":2,"score":0.27720001339912415},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.2750000059604645},{"id":"https://openalex.org/C2780378061","wikidata":"https://www.wikidata.org/wiki/Q25351891","display_name":"Service (business)","level":2,"score":0.27410000562667847},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.2702000141143799}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/fllm67465.2025.11391161","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fllm67465.2025.11391161","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 3rd International Conference on Foundation and Large Language Models (FLLM)","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":6,"referenced_works":["https://openalex.org/W2982682021","https://openalex.org/W3126855403","https://openalex.org/W4393354607","https://openalex.org/W4400260108","https://openalex.org/W4401475186","https://openalex.org/W4401808863"],"related_works":[],"abstract_inverted_index":{"With":[0],"the":[1,4,40,67,76,119,125],"proliferation":[2],"of":[3,8,44,70,78,91,94,99,121],"internet,":[5],"Distributed":[6],"Denial":[7],"Service":[9],"(DDoS)":[10],"attacks":[11],"have":[12],"become":[13],"a":[14],"major":[15],"threat":[16],"in":[17,58,124],"modern":[18],"networks.":[19],"Traditional":[20],"defense":[21],"mechanisms":[22],"such":[23],"as":[24],"firewalls":[25],"and":[26,42,97,111],"intrusion":[27],"detection":[28,60],"systems":[29],"can":[30],"filter":[31],"some":[32],"malicious":[33],"traffic":[34],"but":[35],"struggle":[36],"to":[37,62,65,101],"cope":[38],"with":[39],"complexity":[41],"scale":[43],"increasingly":[45],"sophisticated":[46],"attacks.":[47],"Machine":[48],"learning,":[49],"particularly":[50],"Recurrent":[51],"Neural":[52],"Networks":[53],"(RNNs),":[54],"has":[55],"proven":[56],"effective":[57],"DDoS":[59,85],"due":[61],"its":[63],"capability":[64],"capture":[66],"temporal":[68],"patterns":[69],"attack":[71],"traffic.":[72],"This":[73],"study":[74],"investigates":[75],"application":[77],"RNN":[79],"models":[80],"on":[81,88],"P4":[82,126],"switches":[83],"for":[84],"detection,":[86],"focusing":[87],"efficient":[89],"utilization":[90],"resources,":[92],"optimization":[93],"model":[95],"weights,":[96],"adjustment":[98],"precision":[100,110],"improve":[102],"performance.":[103],"Experimental":[104],"results":[105],"show":[106],"that":[107],"fine-tuning":[108],"decimal":[109],"timing":[112],"parameters":[113],"significantly":[114],"improves":[115],"classification":[116],"accuracy,":[117],"demonstrating":[118],"feasibility":[120],"deploying":[122],"RNNs":[123],"environment.":[127]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2026-02-20T00:00:00"}
