{"id":"https://openalex.org/W3138864144","doi":"https://doi.org/10.1109/bmsb49480.2020.9379595","title":"A Nonnegativity-Constraint Sparse Stacked Denoising Autoencoder for Anomaly Detection in Electric Power Communication Network","display_name":"A Nonnegativity-Constraint Sparse Stacked Denoising Autoencoder for Anomaly Detection in Electric Power Communication Network","publication_year":2020,"publication_date":"2020-10-27","ids":{"openalex":"https://openalex.org/W3138864144","doi":"https://doi.org/10.1109/bmsb49480.2020.9379595","mag":"3138864144"},"language":"en","primary_location":{"id":"doi:10.1109/bmsb49480.2020.9379595","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bmsb49480.2020.9379595","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Symposium on Broadband Multimedia Systems and Broadcasting (BMSB)","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":null,"display_name":"Zhuo Tao","orcid":null},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhuo Tao","raw_affiliation_strings":["State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078729695","display_name":"Yong Yan","orcid":"https://orcid.org/0000-0001-7135-5456"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yong Yan","raw_affiliation_strings":["State Grid Zhejiang Electric Power Company, LTD, Zhejiang, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Grid Zhejiang Electric Power Company, LTD, Zhejiang, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100397623","display_name":"Yang Yang","orcid":"https://orcid.org/0000-0002-5245-3584"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yang Yang","raw_affiliation_strings":["State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100423138","display_name":"Yuanyuan Wang","orcid":"https://orcid.org/0000-0002-0586-9413"},"institutions":[{"id":"https://openalex.org/I202334528","display_name":"Beijing Electronic Science and Technology Institute","ror":"https://ror.org/01xdzh226","country_code":"CN","type":"education","lineage":["https://openalex.org/I202334528"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuanyuan Wang","raw_affiliation_strings":["Science and Technology on Information System Engineering Laboratory, Beijing Institute of Control and Electronic Technology, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Science and Technology on Information System Engineering Laboratory, Beijing Institute of Control and Electronic Technology, Beijing, China","institution_ids":["https://openalex.org/I202334528"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100779423","display_name":"Luo J","orcid":"https://orcid.org/0009-0006-0570-7509"},"institutions":[{"id":"https://openalex.org/I202334528","display_name":"Beijing Electronic Science and Technology Institute","ror":"https://ror.org/01xdzh226","country_code":"CN","type":"education","lineage":["https://openalex.org/I202334528"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiang Luo","raw_affiliation_strings":["Science and Technology on Information System Engineering Laboratory, Beijing Institute of Control and Electronic Technology, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Science and Technology on Information System Engineering Laboratory, Beijing Institute of Control and Electronic Technology, Beijing, China","institution_ids":["https://openalex.org/I202334528"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.20983896,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9984999895095825,"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"}},"topics":[{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9984999895095825,"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/T10400","display_name":"Network Security and Intrusion Detection","score":0.994700014591217,"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/T12451","display_name":"Smart Grid and Power Systems","score":0.958299994468689,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/constraint","display_name":"Constraint (computer-aided design)","score":0.7073221802711487},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.6399624347686768},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.630558967590332},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6281717419624329},{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.620976984500885},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5167098045349121},{"id":"https://openalex.org/keywords/adaptation","display_name":"Adaptation (eye)","score":0.4486086368560791},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.42347851395606995},{"id":"https://openalex.org/keywords/network-security","display_name":"Network security","score":0.4215271770954132},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4077640175819397},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.35367321968078613},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.34046053886413574},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.2262689471244812},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.15661272406578064}],"concepts":[{"id":"https://openalex.org/C2776036281","wikidata":"https://www.wikidata.org/wiki/Q48769818","display_name":"Constraint (computer-aided design)","level":2,"score":0.7073221802711487},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.6399624347686768},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.630558967590332},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6281717419624329},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.620976984500885},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5167098045349121},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.4486086368560791},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.42347851395606995},{"id":"https://openalex.org/C182590292","wikidata":"https://www.wikidata.org/wiki/Q989632","display_name":"Network security","level":2,"score":0.4215271770954132},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4077640175819397},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.35367321968078613},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.34046053886413574},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.2262689471244812},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.15661272406578064},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bmsb49480.2020.9379595","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bmsb49480.2020.9379595","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Symposium on Broadband Multimedia Systems and Broadcasting (BMSB)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.6700000166893005,"display_name":"Reduced inequalities"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null},{"id":"https://openalex.org/F4320337504","display_name":"Research and Development","ror":"https://ror.org/027s68j25"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":10,"referenced_works":["https://openalex.org/W2311217941","https://openalex.org/W2463319845","https://openalex.org/W2763583057","https://openalex.org/W2765317657","https://openalex.org/W2789811186","https://openalex.org/W2804964124","https://openalex.org/W2886755908","https://openalex.org/W2901639182","https://openalex.org/W2963693396","https://openalex.org/W2964285681"],"related_works":["https://openalex.org/W3013693939","https://openalex.org/W2159052453","https://openalex.org/W2566616303","https://openalex.org/W3131327266","https://openalex.org/W2734887215","https://openalex.org/W4297051394","https://openalex.org/W3186512740","https://openalex.org/W3194885736","https://openalex.org/W4363671829","https://openalex.org/W3037110488"],"abstract_inverted_index":{"As":[0],"the":[1,4,86,93,102,123],"scale":[2],"of":[3,45],"electric":[5],"power":[6],"communication":[7],"network":[8,14,28,38],"is":[9,68,112,127],"getting":[10],"larger":[11],"and":[12,20,95],"larger,":[13],"security":[15],"issues":[16],"are":[17,48],"becoming":[18],"more":[19,21],"complex.":[22],"as":[23],"an":[24],"effective":[25],"protection":[26],"method,":[27],"traffic":[29],"anomaly":[30],"detection":[31,55],"can":[32],"provide":[33],"important":[34],"technical":[35],"support":[36],"for":[37,79,114,119],"situation":[39],"awareness.":[40],"In":[41],"some":[42],"cases,":[43],"plenty":[44],"labeled":[46],"data":[47],"unavailable,":[49],"which":[50,82],"may":[51,90],"lead":[52],"to":[53,84],"low":[54],"accuracy.":[56],"To":[57],"deal":[58],"with":[59],"this":[60],"problem,":[61],"a":[62,73,98],"nonnegativity-constraint":[63],"sparse":[64],"stacked":[65],"denoising":[66],"autoencoder(NSSDAE)":[67],"proposed.":[69],"Meanwhile,":[70],"we":[71],"propose":[72],"method":[74],"called":[75],"dynamic":[76],"parameter":[77,80],"freezing(DPF)":[78],"transfer,":[81],"allows":[83],"find":[85],"best":[87],"performance":[88],"that":[89,122],"exist":[91],"between":[92],"freezing":[94],"fine-tuning":[96],"within":[97],"layer":[99],"by":[100],"adjusting":[101],"variable":[103],"alpha.":[104],"And":[105],"discriminative":[106],"joint":[107],"probability":[108],"maximum":[109],"mean":[110],"discrepancy":[111],"introduced":[113],"distribution":[115],"adaptation.":[116],"The":[117],"results":[118],"NSL-KDD":[120],"show":[121],"proposed":[124],"NSSDAE-TL":[125],"algorithm":[126],"effective.":[128]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}