{"id":"https://openalex.org/W4389077493","doi":"https://doi.org/10.1109/icmlc58545.2023.10327933","title":"Research on Security Data of Federated Learning Privacy LSTM Model Based on Generative Adversarial Network","display_name":"Research on Security Data of Federated Learning Privacy LSTM Model Based on Generative Adversarial Network","publication_year":2023,"publication_date":"2023-07-09","ids":{"openalex":"https://openalex.org/W4389077493","doi":"https://doi.org/10.1109/icmlc58545.2023.10327933"},"language":"en","primary_location":{"id":"doi:10.1109/icmlc58545.2023.10327933","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icmlc58545.2023.10327933","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 International Conference on Machine Learning and Cybernetics (ICMLC)","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/A5100920624","display_name":"Xu Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I4210134419","display_name":"Neusoft (China)","ror":"https://ror.org/02zc84r97","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210134419"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wang Xu","raw_affiliation_strings":["School of Computer, Neusoft Institute Guangdong,Department of Network Engineering","Department of Network Engineering, School of Computer, Neusoft Institute Guangdong"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer, Neusoft Institute Guangdong,Department of Network Engineering","institution_ids":["https://openalex.org/I4210134419"]},{"raw_affiliation_string":"Department of Network Engineering, School of Computer, Neusoft Institute Guangdong","institution_ids":["https://openalex.org/I4210134419"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5093357935","display_name":"Liang Zhuoming","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liang Zhuoming","raw_affiliation_strings":["South china Nomal University,Network Center","Network Center, South china Nomal University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"South china Nomal University,Network Center","institution_ids":[]},{"raw_affiliation_string":"Network Center, South china Nomal University","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.17843681,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"601","last_page":"607"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9994000196456909,"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/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9994000196456909,"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/T13918","display_name":"Advanced Data and IoT Technologies","score":0.986299991607666,"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"}},{"id":"https://openalex.org/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.9811000227928162,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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":0.745050311088562},{"id":"https://openalex.org/keywords/inversion","display_name":"Inversion (geology)","score":0.7212433815002441},{"id":"https://openalex.org/keywords/constraint","display_name":"Constraint (computer-aided design)","score":0.6586797833442688},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.6253379583358765},{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.526434063911438},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.5252582430839539},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.44950851798057556},{"id":"https://openalex.org/keywords/wireless","display_name":"Wireless","score":0.446321964263916},{"id":"https://openalex.org/keywords/experimental-data","display_name":"Experimental data","score":0.43527597188949585},{"id":"https://openalex.org/keywords/fading","display_name":"Fading","score":0.4314868748188019},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.4294169843196869},{"id":"https://openalex.org/keywords/inverse-transform-sampling","display_name":"Inverse transform sampling","score":0.41954994201660156},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3809685707092285},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3783096969127655},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.37285926938056946},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.160092294216156},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.13084369897842407},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.1077984869480133}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.745050311088562},{"id":"https://openalex.org/C1893757","wikidata":"https://www.wikidata.org/wiki/Q3653001","display_name":"Inversion (geology)","level":3,"score":0.7212433815002441},{"id":"https://openalex.org/C2776036281","wikidata":"https://www.wikidata.org/wiki/Q48769818","display_name":"Constraint (computer-aided design)","level":2,"score":0.6586797833442688},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.6253379583358765},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.526434063911438},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.5252582430839539},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.44950851798057556},{"id":"https://openalex.org/C555944384","wikidata":"https://www.wikidata.org/wiki/Q249","display_name":"Wireless","level":2,"score":0.446321964263916},{"id":"https://openalex.org/C55037315","wikidata":"https://www.wikidata.org/wiki/Q5421151","display_name":"Experimental data","level":2,"score":0.43527597188949585},{"id":"https://openalex.org/C81978471","wikidata":"https://www.wikidata.org/wiki/Q1196572","display_name":"Fading","level":3,"score":0.4314868748188019},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.4294169843196869},{"id":"https://openalex.org/C143606050","wikidata":"https://www.wikidata.org/wiki/Q1377019","display_name":"Inverse transform sampling","level":3,"score":0.41954994201660156},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3809685707092285},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3783096969127655},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.37285926938056946},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.160092294216156},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.13084369897842407},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.1077984869480133},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.0},{"id":"https://openalex.org/C109007969","wikidata":"https://www.wikidata.org/wiki/Q749565","display_name":"Structural basin","level":2,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C84174578","wikidata":"https://www.wikidata.org/wiki/Q889796","display_name":"Surface wave","level":2,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icmlc58545.2023.10327933","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icmlc58545.2023.10327933","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 International Conference on Machine Learning and Cybernetics (ICMLC)","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":8,"referenced_works":["https://openalex.org/W1873763122","https://openalex.org/W1915485278","https://openalex.org/W2067713319","https://openalex.org/W2112796928","https://openalex.org/W2793685318","https://openalex.org/W2954388561","https://openalex.org/W2964162474","https://openalex.org/W4205228770"],"related_works":["https://openalex.org/W2502115930","https://openalex.org/W4246396837","https://openalex.org/W3176240006","https://openalex.org/W3126451824","https://openalex.org/W2482350142","https://openalex.org/W1561927205","https://openalex.org/W3191453585","https://openalex.org/W4297672492","https://openalex.org/W4288019534","https://openalex.org/W4283217948"],"abstract_inverted_index":{"As":[0],"a":[1],"new":[2],"wireless":[3],"transmission":[4],"architecture":[5],"technology,":[6],"cSO":[7,18],"can":[8,129],"effectively":[9],"reduce":[10],"the":[11,26,35,38,44,51,57,78,89,93,112,125,135,143,146],"influence":[12],"of":[13,32,59,95,115,122,134,137,145],"fading":[14],"channels":[15],"and":[16,34,99],"provide":[17],"links":[19],"for":[20,107],"low":[21],"channel":[22],"quality.":[23],"Secondly,":[24],"in":[25,56],"ultra-large":[27],"traffic":[28],"cSO,":[29],"The":[30],"fitting":[31,70,97],"data":[33,69,96],"constraint":[36,83,105,128],"on":[37,92],"model":[39,82,104,127],"must":[40],"be":[41,86,130],"considered":[42],"at":[43],"same":[45],"time.":[46],"Generally":[47],"speaking,":[48],"regularization":[49],"is":[50,62],"most":[52],"common":[53],"method,":[54],"because":[55],"process":[58],"inversion,":[60],"it":[61],"far":[63],"from":[64,120],"enough":[65],"to":[66,76,88],"only":[67],"use":[68],"terms":[71,84],"as":[72],"constraints.":[73],"In":[74],"order":[75],"make":[77],"inversion":[79,133],"results":[80],"stable,":[81],"should":[85],"added":[87],"objective":[90],"function":[91],"basis":[94],"terms,":[98],"there":[100],"are":[101,118],"usually":[102],"different":[103,108,119],"methods":[106],"practical":[109],"problems.":[110],"When":[111,132],"physical":[113],"properties":[114],"anomalous":[116],"body":[117],"those":[121],"surrounding":[123],"rock,":[124],"minimum":[126],"used.":[131],"moderocess":[136],"EMM-connected":[138],"state":[139],"was":[140],"consistent":[141],"with":[142],"determination":[144],"coverage":[147],"enhancement":[148],"level.":[149]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
