{"id":"https://openalex.org/W3011524935","doi":"https://doi.org/10.1109/comsnets48256.2020.9027452","title":"Deep Reinforcement Learning based Intrusion Detection System for Cloud Infrastructure","display_name":"Deep Reinforcement Learning based Intrusion Detection System for Cloud Infrastructure","publication_year":2020,"publication_date":"2020-01-01","ids":{"openalex":"https://openalex.org/W3011524935","doi":"https://doi.org/10.1109/comsnets48256.2020.9027452","mag":"3011524935"},"language":"en","primary_location":{"id":"doi:10.1109/comsnets48256.2020.9027452","doi":"https://doi.org/10.1109/comsnets48256.2020.9027452","is_oa":false,"landing_page_url":"https://doi.org/10.1109/comsnets48256.2020.9027452","pdf_url":null,"source":{"id":"https://openalex.org/S7407088473","display_name":"International Conference on Communication Systems & Networks (COMSNETS)","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":"2020 International Conference on COMmunication Systems &amp; NETworkS (COMSNETS)","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/A5026959916","display_name":"Kamalakanta Sethi","orcid":"https://orcid.org/0000-0003-4986-243X","observed_orcids":["https://orcid.org/0000-0003-4986-243X"]},"institutions":[{"id":"https://openalex.org/I99729588","display_name":"Indian Institute of Technology Bhubaneswar","ror":"https://ror.org/04gx72j20","country_code":"IN","type":"education","lineage":["https://openalex.org/I99729588"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Kamalakanta Sethi","raw_affiliation_strings":["Indian Institute of Technology, Bhubaneswar, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Indian Institute of Technology, Bhubaneswar, India","institution_ids":["https://openalex.org/I99729588"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5077585432","display_name":"Rahul Kumar","orcid":"https://orcid.org/0000-0001-6183-5982","observed_orcids":["https://orcid.org/0000-0001-6183-5982"]},"institutions":[{"id":"https://openalex.org/I99729588","display_name":"Indian Institute of Technology Bhubaneswar","ror":"https://ror.org/04gx72j20","country_code":"IN","type":"education","lineage":["https://openalex.org/I99729588"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Rahul Kumar","raw_affiliation_strings":["Indian Institute of Technology, Bhubaneswar, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Indian Institute of Technology, Bhubaneswar, India","institution_ids":["https://openalex.org/I99729588"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034593444","display_name":"Nishant Prajapati","orcid":"https://orcid.org/0000-0001-7963-8848","observed_orcids":["https://orcid.org/0000-0001-7963-8848"]},"institutions":[{"id":"https://openalex.org/I16292982","display_name":"National Institute of Technology Rourkela","ror":"https://ror.org/011gmn932","country_code":"IN","type":"education","lineage":["https://openalex.org/I16292982"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Nishant Prajapati","raw_affiliation_strings":["National Institute of Technology, Rourkela, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Institute of Technology, Rourkela, India","institution_ids":["https://openalex.org/I16292982"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5071220202","display_name":"Padmalochan Bera","orcid":"https://orcid.org/0000-0002-0044-7051","observed_orcids":["https://orcid.org/0000-0002-0044-7051"]},"institutions":[{"id":"https://openalex.org/I99729588","display_name":"Indian Institute of Technology Bhubaneswar","ror":"https://ror.org/04gx72j20","country_code":"IN","type":"education","lineage":["https://openalex.org/I99729588"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Padmalochan Bera","raw_affiliation_strings":["Indian Institute of Technology, Bhubaneswar, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Indian Institute of Technology, Bhubaneswar, India","institution_ids":["https://openalex.org/I99729588"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":8.6611,"has_fulltext":false,"cited_by_count":91,"citation_normalized_percentile":{"value":0.98890116,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":93,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"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":0.00039999998989515007,"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":9.999999747378752e-05,"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":0.8579999804496765},{"id":"https://openalex.org/keywords/cloud-infrastructure-security","display_name":"cloud infrastructure security","score":0.8309999704360962},{"id":"https://openalex.org/keywords/deep-reinforcement-learning","display_name":"deep reinforcement learning","score":0.9959999918937683},{"id":"https://openalex.org/keywords/false-positive-reduction","display_name":"false positive reduction","score":0.7429999709129333},{"id":"https://openalex.org/keywords/attack-classification","display_name":"attack classification","score":0.7990000247955322},{"id":"https://openalex.org/keywords/novel-attack-detection","display_name":"novel attack detection","score":0.7649999856948853},{"id":"https://openalex.org/keywords/unsw-nb15","display_name":"UNSW-NB15","score":0.8970000147819519}],"concepts":[{"id":"https://openalex.org/C35525427","wikidata":"https://www.wikidata.org/wiki/Q745881","display_name":"Intrusion detection system","level":2,"score":0.8745092153549194},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8253378868103027},{"id":"https://openalex.org/C79974875","wikidata":"https://www.wikidata.org/wiki/Q483639","display_name":"Cloud computing","level":2,"score":0.8133367300033569},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.7617886066436768},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.637975811958313},{"id":"https://openalex.org/C95922358","wikidata":"https://www.wikidata.org/wiki/Q5432725","display_name":"False positive rate","level":2,"score":0.5603263974189758},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5236924886703491},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5196239352226257},{"id":"https://openalex.org/C158251709","wikidata":"https://www.wikidata.org/wiki/Q354025","display_name":"Intrusion","level":2,"score":0.4651637375354767},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.41104185581207275},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.335321307182312},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3277181088924408},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.13220009207725525},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C17409809","wikidata":"https://www.wikidata.org/wiki/Q161764","display_name":"Geochemistry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/comsnets48256.2020.9027452","doi":"https://doi.org/10.1109/comsnets48256.2020.9027452","is_oa":false,"landing_page_url":"https://doi.org/10.1109/comsnets48256.2020.9027452","pdf_url":null,"source":{"id":"https://openalex.org/S7407088473","display_name":"International Conference on Communication Systems & Networks (COMSNETS)","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":"2020 International Conference on COMmunication Systems &amp; NETworkS (COMSNETS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W41554520","https://openalex.org/W1489073918","https://openalex.org/W1591530988","https://openalex.org/W2101234009","https://openalex.org/W2168032523","https://openalex.org/W2296509296","https://openalex.org/W2334853001","https://openalex.org/W2626468835","https://openalex.org/W2899761491","https://openalex.org/W2905199997","https://openalex.org/W2982375055","https://openalex.org/W3123212791"],"related_works":["https://openalex.org/W3118181167","https://openalex.org/W4416249949","https://openalex.org/W7219217256","https://openalex.org/W7155052697","https://openalex.org/W4414198818","https://openalex.org/W7136158741","https://openalex.org/W7201836599","https://openalex.org/W4401976140","https://openalex.org/W6939382552","https://openalex.org/W4414292414"],"abstract_inverted_index":{"Intrusion":[0,26],"Detection":[1],"in":[2,38],"cloud":[3,50,84],"platform":[4],"is":[5,30],"a":[6,43,63,79],"challenging":[7],"problem":[8],"due":[9],"to":[10,54,122],"its":[11],"extensive":[12,107],"usage":[13],"and":[14,23,34,68,92,96,101,118],"distributed":[15],"nature":[16],"that":[17,87,114],"are":[18,52,59],"constant":[19],"targets":[20],"of":[21,47,61,99],"new":[22,100],"unknown":[24],"attacks.":[25,56,103],"detection":[27,95],"system":[28,41],"(IDS)":[29],"responsible":[31],"for":[32],"monitoring":[33],"detecting":[35],"malicious":[36],"activities":[37],"any":[39],"computing":[40],"or":[42],"network.":[44],"However,":[45],"most":[46],"the":[48,89,110,123],"traditional":[49],"IDSs":[51],"vulnerable":[53],"novel":[55],"Also,":[57],"they":[58],"incapable":[60],"maintaining":[62],"balance":[64],"between":[65],"high":[66],"accuracy":[67,117],"less":[69,119],"false":[70],"positive":[71],"rate":[72],"(FPR).":[73],"In":[74],"this":[75],"paper,":[76],"we":[77],"propose":[78],"deep":[80],"reinforcement":[81],"learning-based":[82],"adaptive":[83],"IDS":[85],"architecture":[86],"addresses":[88],"above":[90],"limitations":[91],"performs":[93],"accurate":[94],"fine-grained":[97],"classification":[98],"complex":[102],"We":[104],"have":[105],"done":[106],"experimentation":[108],"using":[109],"benchmark":[111],"UNSW-NB15":[112],"dataset":[113],"shows":[115],"better":[116],"FPR":[120],"compared":[121],"state-of-the-art":[124],"IDSs.":[125]},"counts_by_year":[{"year":2026,"cited_by_count":12},{"year":2025,"cited_by_count":15},{"year":2024,"cited_by_count":16},{"year":2023,"cited_by_count":14},{"year":2022,"cited_by_count":17},{"year":2021,"cited_by_count":15},{"year":2020,"cited_by_count":2}],"updated_date":"2026-11-10T11:39:43.021295","created_date":"2020-03-23T00:00:00"}
