{"id":"https://openalex.org/W3097487972","doi":"https://doi.org/10.1145/3421766.3421891","title":"Deep Learning for IoT Intrusion Detection based on LSTMs-AE","display_name":"Deep Learning for IoT Intrusion Detection based on LSTMs-AE","publication_year":2020,"publication_date":"2020-10-15","ids":{"openalex":"https://openalex.org/W3097487972","doi":"https://doi.org/10.1145/3421766.3421891","mag":"3097487972"},"language":"en","primary_location":{"id":"doi:10.1145/3421766.3421891","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3421766.3421891","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2nd International Conference on Artificial Intelligence and Advanced Manufacture","raw_type":"proceedings-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/A5022882653","display_name":"Yingfei Xu","orcid":null},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yingfei Xu","raw_affiliation_strings":["College of Computer, National University of Defense Technology, Changsha, China"],"affiliations":[{"raw_affiliation_string":"College of Computer, National University of Defense Technology, Changsha, China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110374351","display_name":"Yong Tang","orcid":null},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yong Tang","raw_affiliation_strings":["College of Computer, National University of Defense Technology, Changsha, China"],"affiliations":[{"raw_affiliation_string":"College of Computer, National University of Defense Technology, Changsha, China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100636286","display_name":"Qiang Yang","orcid":"https://orcid.org/0000-0001-5059-8360"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qiang Yang","raw_affiliation_strings":["College of Computer, National University of Defense Technology, Changsha, China"],"affiliations":[{"raw_affiliation_string":"College of Computer, National University of Defense Technology, Changsha, China","institution_ids":["https://openalex.org/I170215575"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5022882653"],"corresponding_institution_ids":["https://openalex.org/I170215575"],"apc_list":null,"apc_paid":null,"fwci":1.2334,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":{"value":0.81594938,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"64","last_page":"68"},"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9995999932289124,"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/T11241","display_name":"Advanced Malware Detection Techniques","score":0.9986000061035156,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.9472218155860901},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8313957452774048},{"id":"https://openalex.org/keywords/intrusion-detection-system","display_name":"Intrusion detection system","score":0.7920128107070923},{"id":"https://openalex.org/keywords/internet-of-things","display_name":"Internet of Things","score":0.6412633061408997},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.6283813714981079},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5923023223876953},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5818853378295898},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.5816001892089844},{"id":"https://openalex.org/keywords/scheme","display_name":"Scheme (mathematics)","score":0.5125162601470947},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.4624709188938141},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4425901472568512},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.42080622911453247},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4202580153942108},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.14324259757995605}],"concepts":[{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.9472218155860901},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8313957452774048},{"id":"https://openalex.org/C35525427","wikidata":"https://www.wikidata.org/wiki/Q745881","display_name":"Intrusion detection system","level":2,"score":0.7920128107070923},{"id":"https://openalex.org/C81860439","wikidata":"https://www.wikidata.org/wiki/Q251212","display_name":"Internet of Things","level":2,"score":0.6412633061408997},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6283813714981079},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5923023223876953},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5818853378295898},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.5816001892089844},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.5125162601470947},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.4624709188938141},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4425901472568512},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.42080622911453247},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4202580153942108},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.14324259757995605},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","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},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3421766.3421891","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3421766.3421891","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2nd International Conference on Artificial Intelligence and Advanced Manufacture","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W2064675550","https://openalex.org/W2120685459","https://openalex.org/W2278186031","https://openalex.org/W2340896621","https://openalex.org/W2799758613","https://openalex.org/W2963166639","https://openalex.org/W2981386789","https://openalex.org/W3025093231","https://openalex.org/W3122864121","https://openalex.org/W4255666005","https://openalex.org/W6607987730"],"related_works":["https://openalex.org/W3186512740","https://openalex.org/W3194885736","https://openalex.org/W4363671829","https://openalex.org/W2983142544","https://openalex.org/W2891059443","https://openalex.org/W4281663961","https://openalex.org/W3208888551","https://openalex.org/W4313561566","https://openalex.org/W3208386644","https://openalex.org/W4389832810"],"abstract_inverted_index":{"With":[0],"the":[1,24,44,49,78,84,108,110],"advent":[2],"of":[3,8,18,27,48,88,107,113],"5G":[4],"era,":[5],"The":[6],"Internet":[7],"Things":[9],"(IoT)":[10],"is":[11,71,81],"obtaining":[12],"considerable":[13],"attention":[14],"in":[15,35,68,105],"all":[16],"walks":[17],"life":[19],"nowadays.":[20],"However,":[21],"due":[22],"to":[23,73],"hardware":[25],"problems":[26,34],"devices,":[28],"there":[29],"may":[30],"exists":[31],"some":[32],"security":[33],"IOT.":[36],"While":[37],"existing":[38],"intrusion":[39,79,98],"detection":[40,80,99],"methods":[41],"rarely":[42],"consider":[43],"time":[45],"series":[46],"feature":[47,85],"data.":[50],"In":[51],"this":[52],"paper,":[53],"we":[54],"propose":[55],"an":[56],"anomaly":[57],"monitoring":[58],"model":[59,95],"for":[60],"Autoencoder":[61],"based":[62],"on":[63],"Long-Short":[64],"Term":[65],"Memory":[66],"(LSTMs-AE),":[67],"which":[69],"LTSM":[70],"exploited":[72],"capture":[74],"time-series":[75],"features":[76],"and":[77],"performed":[82],"by":[83],"learning":[86],"ability":[87],"Autoencoder.":[89],"Thorough":[90],"experiments":[91],"demonstrate":[92],"that":[93],"our":[94],"has":[96],"better":[97],"performance":[100],"than":[101],"ordinary":[102],"Autoencoder,":[103],"as":[104],"most":[106],"dataset":[109],"accuracy":[111],"rate":[112],"proposed":[114],"scheme":[115],"exceeds":[116],"0.95.":[117]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}