{"id":"https://openalex.org/W3120418020","doi":"https://doi.org/10.1109/ipccc50635.2020.9391558","title":"Deep Learning for IoT","display_name":"Deep Learning for IoT","publication_year":2020,"publication_date":"2020-11-06","ids":{"openalex":"https://openalex.org/W3120418020","doi":"https://doi.org/10.1109/ipccc50635.2020.9391558","mag":"3120418020"},"language":"en","primary_location":{"id":"doi:10.1109/ipccc50635.2020.9391558","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ipccc50635.2020.9391558","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE 39th International Performance Computing and Communications Conference (IPCCC)","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/A5082908200","display_name":"Tao Lin","orcid":"https://orcid.org/0000-0001-9386-7858"},"institutions":[{"id":"https://openalex.org/I1311688040","display_name":"Amazon (United States)","ror":"https://ror.org/04mv4n011","country_code":"US","type":"company","lineage":["https://openalex.org/I1311688040"]},{"id":"https://openalex.org/I58610484","display_name":"Seattle University","ror":"https://ror.org/02jqc0m91","country_code":"US","type":"education","lineage":["https://openalex.org/I58610484"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Tao Lin","raw_affiliation_strings":["Amazon, Seattle, US"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Amazon, Seattle, US","institution_ids":["https://openalex.org/I1311688040","https://openalex.org/I58610484"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5082908200"],"corresponding_institution_ids":["https://openalex.org/I1311688040","https://openalex.org/I58610484"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":57,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"4"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10400","display_name":"Network Security and Intrusion Detection","score":0.9984999895095825,"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":0.9984999895095825,"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":0.9969000220298767,"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/T12034","display_name":"Digital and Cyber Forensics","score":0.9871000051498413,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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":0.8188235759735107},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6760336756706238},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6715307235717773},{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.6697114706039429},{"id":"https://openalex.org/keywords/adversary","display_name":"Adversary","score":0.667126476764679},{"id":"https://openalex.org/keywords/internet-of-things","display_name":"Internet of Things","score":0.5124621987342834},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4950994551181793},{"id":"https://openalex.org/keywords/adversarial-machine-learning","display_name":"Adversarial machine learning","score":0.4579876661300659},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4436623454093933},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.4330430030822754},{"id":"https://openalex.org/keywords/hacker","display_name":"Hacker","score":0.41393816471099854},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.32435011863708496}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8188235759735107},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6760336756706238},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6715307235717773},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.6697114706039429},{"id":"https://openalex.org/C41065033","wikidata":"https://www.wikidata.org/wiki/Q2825412","display_name":"Adversary","level":2,"score":0.667126476764679},{"id":"https://openalex.org/C81860439","wikidata":"https://www.wikidata.org/wiki/Q251212","display_name":"Internet of Things","level":2,"score":0.5124621987342834},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4950994551181793},{"id":"https://openalex.org/C2778403875","wikidata":"https://www.wikidata.org/wiki/Q20312394","display_name":"Adversarial machine learning","level":3,"score":0.4579876661300659},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4436623454093933},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.4330430030822754},{"id":"https://openalex.org/C86844869","wikidata":"https://www.wikidata.org/wiki/Q2798820","display_name":"Hacker","level":2,"score":0.41393816471099854},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.32435011863708496}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ipccc50635.2020.9391558","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ipccc50635.2020.9391558","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE 39th International Performance Computing and Communications Conference (IPCCC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","score":0.4699999988079071,"display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":7,"referenced_works":["https://openalex.org/W2284615764","https://openalex.org/W2752804236","https://openalex.org/W2793461878","https://openalex.org/W2895017383","https://openalex.org/W2903139497","https://openalex.org/W4391505049","https://openalex.org/W6755634564"],"related_works":["https://openalex.org/W4320018150","https://openalex.org/W4239582170","https://openalex.org/W3048732067","https://openalex.org/W2918664383","https://openalex.org/W106056076","https://openalex.org/W4320855730","https://openalex.org/W4383468834","https://openalex.org/W2135200719","https://openalex.org/W4283221438","https://openalex.org/W2900159906"],"abstract_inverted_index":{"Deep":[0],"learning":[1,5,113],"and":[2],"other":[3],"machine":[4,43,137],"approaches":[6,144],"are":[7],"deployed":[8],"to":[9,13,28,127,149],"many":[10],"systems":[11,31],"related":[12],"Internet":[14],"of":[15,41,135,147],"Things":[16],"or":[17],"IoT.":[18],"However,":[19],"it":[20],"faces":[21],"challenges":[22],"that":[23],"adversaries":[24,131],"can":[25],"take":[26],"loopholes":[27],"hack":[29],"these":[30],"through":[32],"tampering":[33],"history":[34],"data.This":[35],"paper":[36,63,119],"first":[37],"presents":[38,120],"overall":[39],"points":[40],"adversarial":[42,158],"learning.":[44,160],"Then,":[45],"we":[46,105],"illustrate":[47],"traditional":[48],"methods,":[49],"such":[50],"as":[51],"Petri":[52],"Net":[53],"cannot":[54],"solve":[55],"this":[56,62,118,151],"new":[57,143],"question":[58],"efficiently.":[59],"After":[60],"that,":[61],"uses":[64],"the":[65,93,133,142],"example":[66],"from":[67,70],"triage(filter)":[68],"analysis":[69,77,102],"IoT":[71,83,100,154],"cyber":[72,84,94],"security":[73],"operations":[74],"center.":[75],"Filter":[76],"plays":[78],"a":[79,107,121],"significant":[80],"role":[81],"in":[82,132,145,153],"operations.":[85],"The":[86],"overwhelming":[87],"data":[88,101,124],"flood":[89],"is":[90],"obviously":[91],"above":[92],"analyst's":[95],"analytical":[96],"reasoning.":[97],"To":[98],"help":[99],"more":[103],"efficient,":[104],"propose":[106],"retrieval":[108,125],"method":[109],"based":[110,156],"on":[111,123,157],"deep":[112,159],"(recurrent":[114],"neural":[115],"network).":[116],"Besides,":[117],"research":[122],"solution":[126],"avoid":[128],"hacking":[129],"by":[130],"fields":[134],"adversary":[136],"leaning.":[138],"It":[139],"further":[140],"directs":[141],"terms":[146],"how":[148],"implementing":[150],"framework":[152],"settings":[155]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":8},{"year":2023,"cited_by_count":9},{"year":2022,"cited_by_count":15},{"year":2021,"cited_by_count":13},{"year":2019,"cited_by_count":3}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
