{"id":"https://openalex.org/W3197150995","doi":"https://doi.org/10.1109/tnse.2021.3109644","title":"HNN: A Novel Model to Study the Intrusion Detection Based on Multi-Feature Correlation and Temporal-Spatial Analysis","display_name":"HNN: A Novel Model to Study the Intrusion Detection Based on Multi-Feature Correlation and Temporal-Spatial Analysis","publication_year":2021,"publication_date":"2021-09-02","ids":{"openalex":"https://openalex.org/W3197150995","doi":"https://doi.org/10.1109/tnse.2021.3109644","mag":"3197150995"},"language":"en","primary_location":{"id":"doi:10.1109/tnse.2021.3109644","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnse.2021.3109644","pdf_url":null,"source":{"id":"https://openalex.org/S2484352698","display_name":"IEEE Transactions on Network Science and Engineering","issn_l":"2327-4697","issn":["2327-4697","2334-329X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Network Science and Engineering","raw_type":"journal-article"},"type":"article","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/A5080830682","display_name":"Shengwei Lei","orcid":"https://orcid.org/0000-0002-9252-4551"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shengwei Lei","raw_affiliation_strings":["Key Laboratory of Beijing Network Technology, Beihang University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-9252-4551","affiliations":[{"raw_affiliation_string":"Key Laboratory of Beijing Network Technology, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035296513","display_name":"Chunhe Xia","orcid":"https://orcid.org/0000-0003-4424-8449"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chunhe Xia","raw_affiliation_strings":["Key Laboratory of Beijing Network Technology, Beihang University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0003-4424-8449","affiliations":[{"raw_affiliation_string":"Key Laboratory of Beijing Network Technology, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020561528","display_name":"Zhong Li","orcid":"https://orcid.org/0000-0003-2304-923X"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhong Li","raw_affiliation_strings":["Key Laboratory of Beijing Network Technology, Beihang University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Key Laboratory of Beijing Network Technology, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100679808","display_name":"Xiaojian Li","orcid":"https://orcid.org/0000-0002-5353-5207"},"institutions":[{"id":"https://openalex.org/I29739308","display_name":"Guangxi Normal University","ror":"https://ror.org/02frt9q65","country_code":"CN","type":"education","lineage":["https://openalex.org/I29739308"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaojian Li","raw_affiliation_strings":["College of Computer Science and Information Technology, Guangxi Normal University Guilin, Guangxi, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Computer Science and Information Technology, Guangxi Normal University Guilin, Guangxi, China","institution_ids":["https://openalex.org/I29739308"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5018085680","display_name":"Tianbo Wang","orcid":"https://orcid.org/0000-0002-0227-9557"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tianbo Wang","raw_affiliation_strings":["School of Cyber Science and Technology, Beihang University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-0227-9557","affiliations":[{"raw_affiliation_string":"School of Cyber Science and Technology, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":4.4057,"has_fulltext":false,"cited_by_count":51,"citation_normalized_percentile":{"value":0.94614631,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":100},"biblio":{"volume":"8","issue":"4","first_page":"3257","last_page":"3274"},"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/T11598","display_name":"Internet Traffic Analysis and Secure E-voting","score":0.9973000288009644,"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"}},{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9958999752998352,"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":0.7988208532333374},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6817406415939331},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6528705954551697},{"id":"https://openalex.org/keywords/intrusion-detection-system","display_name":"Intrusion detection system","score":0.6401928663253784},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5926260948181152},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5681008696556091},{"id":"https://openalex.org/keywords/correlation","display_name":"Correlation","score":0.5364051461219788},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.5141830444335938},{"id":"https://openalex.org/keywords/spatial-correlation","display_name":"Spatial correlation","score":0.5012457370758057},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.500154972076416},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.4985513687133789},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4685550332069397},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.46410974860191345},{"id":"https://openalex.org/keywords/spatial-analysis","display_name":"Spatial analysis","score":0.4478064477443695},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4322045147418976},{"id":"https://openalex.org/keywords/recurrent-neural-network","display_name":"Recurrent neural network","score":0.4238550662994385},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3391743004322052},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.06628444790840149},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.06483498215675354},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.05969598889350891}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7988208532333374},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6817406415939331},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6528705954551697},{"id":"https://openalex.org/C35525427","wikidata":"https://www.wikidata.org/wiki/Q745881","display_name":"Intrusion detection system","level":2,"score":0.6401928663253784},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5926260948181152},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5681008696556091},{"id":"https://openalex.org/C117220453","wikidata":"https://www.wikidata.org/wiki/Q5172842","display_name":"Correlation","level":2,"score":0.5364051461219788},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.5141830444335938},{"id":"https://openalex.org/C150060386","wikidata":"https://www.wikidata.org/wiki/Q7574054","display_name":"Spatial correlation","level":2,"score":0.5012457370758057},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.500154972076416},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.4985513687133789},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4685550332069397},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.46410974860191345},{"id":"https://openalex.org/C159620131","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Spatial analysis","level":2,"score":0.4478064477443695},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4322045147418976},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.4238550662994385},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3391743004322052},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.06628444790840149},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.06483498215675354},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.05969598889350891},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tnse.2021.3109644","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnse.2021.3109644","pdf_url":null,"source":{"id":"https://openalex.org/S2484352698","display_name":"IEEE Transactions on Network Science and Engineering","issn_l":"2327-4697","issn":["2327-4697","2334-329X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Network Science and Engineering","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3171365517","display_name":"\u590d\u6742\u65f6\u5e8f\u4e91\u5f02\u8d28\u670d\u52a1\u8d44\u6e90\u7684\u95ee\u8d23\u673a\u5236\u7814\u7a76","funder_award_id":"61862008","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4645851237","display_name":null,"funder_award_id":"U1636208","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6897205863","display_name":null,"funder_award_id":"61902013","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":43,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1963579636","https://openalex.org/W1978502884","https://openalex.org/W1985258458","https://openalex.org/W1998496248","https://openalex.org/W2002261403","https://openalex.org/W2003282593","https://openalex.org/W2025183498","https://openalex.org/W2107164534","https://openalex.org/W2110890874","https://openalex.org/W2139733965","https://openalex.org/W2296509296","https://openalex.org/W2318865872","https://openalex.org/W2413951536","https://openalex.org/W2435937066","https://openalex.org/W2528827134","https://openalex.org/W2554704889","https://openalex.org/W2606697812","https://openalex.org/W2732560875","https://openalex.org/W2775103799","https://openalex.org/W2789828921","https://openalex.org/W2801756871","https://openalex.org/W2894006709","https://openalex.org/W2919815709","https://openalex.org/W2921364842","https://openalex.org/W2956765062","https://openalex.org/W2973055534","https://openalex.org/W2984419450","https://openalex.org/W2986334213","https://openalex.org/W2990225485","https://openalex.org/W2991507433","https://openalex.org/W2997507814","https://openalex.org/W3000225415","https://openalex.org/W3004777721","https://openalex.org/W3007182219","https://openalex.org/W3012302768","https://openalex.org/W3013386139","https://openalex.org/W3019959491","https://openalex.org/W3021219025","https://openalex.org/W3040628207","https://openalex.org/W4230857879","https://openalex.org/W6631190155","https://openalex.org/W6776311242"],"related_works":["https://openalex.org/W4225394202","https://openalex.org/W4298287631","https://openalex.org/W2953061907","https://openalex.org/W1847088711","https://openalex.org/W3036642985","https://openalex.org/W3032952384","https://openalex.org/W3003272824","https://openalex.org/W2481566011","https://openalex.org/W2239213377","https://openalex.org/W2384922233"],"abstract_inverted_index":{"Network":[0,34,171],"intrusion":[1,23,84,175],"poses":[2],"a":[3,54,102,118],"severe":[4],"threat":[5],"to":[6,19,43,66,136,173],"the":[7,26,31,72,80,96,130,143,147,152,155,163,168,191],"Internet.":[8],"Intrusion":[9],"detection":[10],"methods":[11,76],"based":[12],"on":[13,162,190],"deep":[14],"learning":[15],"are":[16],"very":[17],"effective":[18],"process":[20],"and":[21,36,46,112,127,132,187,196],"analyze":[22],"data.":[24,85,176],"On":[25,71],"one":[27],"hand,":[28,74],"they":[29,51,88],"use":[30],"Convolutional":[32],"Neural":[33,170],"(CNN)":[35],"Long":[37],"Short":[38],"Term":[39],"Memory":[40],"(LSTM)":[41],"models":[42,60],"extract":[44,137],"spatial":[45],"temporal":[47],"features,":[48,149],"respectively.":[49],"However,":[50],"either":[52],"adopt":[53,117],"single":[55],"model":[56,107],"or":[57,150],"operate":[58],"two":[59,97],"in":[61,134],"series.":[62],"And":[63,86],"it":[64],"fails":[65],"capture":[67],"temporal-spatial":[68,113,138,144,156],"features":[69,145,157],"effectively.":[70],"other":[73],"previous":[75],"do":[77],"not":[78],"consider":[79],"multi-feature":[81,110,125],"correlation":[82,111,126,148],"of":[83,154],"then":[87,128],"cannot":[89],"get":[90],"better":[91],"classification":[92],"performance.":[93],"To":[94],"address":[95],"above":[98,164],"problems,":[99],"we":[100,116,123,141,166],"propose":[101],"hybrid":[103],"neural":[104],"network":[105],"(HNN)":[106],"by":[108,158],"integrating":[109],"analysis.":[114],"First,":[115],"contribution-based":[119],"feature":[120],"selection.":[121],"Second,":[122],"reconstruct":[124],"apply":[129],"CNN":[131],"LSTM":[133],"parallel":[135],"features.":[139],"Finally,":[140],"splice":[142],"with":[146],"study":[151],"influence":[153],"attention":[159],"mechanism.":[160],"Based":[161],"operations,":[165],"exploit":[167],"Deep":[169],"(DNN)":[172],"detect":[174],"The":[177],"experimental":[178],"results":[179],"show":[180],"that":[181],"HNN":[182],"improves":[183],"3.78%,":[184],"1.31%,":[185],"0.21%,":[186],"1.13%":[188],"accuracy":[189],"UNSW-NB15,":[192],"AWID,":[193],"CICIDS":[194,197],"2017,":[195],"2018":[198],"datasets.":[199]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":19},{"year":2024,"cited_by_count":9},{"year":2023,"cited_by_count":13},{"year":2022,"cited_by_count":6},{"year":2021,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
