{"id":"https://openalex.org/W4401168252","doi":"https://doi.org/10.1145/3674225.3674369","title":"PDAP-GAN: Generative Adversarial Network for Power Data Anonymization Protection","display_name":"PDAP-GAN: Generative Adversarial Network for Power Data Anonymization Protection","publication_year":2024,"publication_date":"2024-01-19","ids":{"openalex":"https://openalex.org/W4401168252","doi":"https://doi.org/10.1145/3674225.3674369"},"language":"en","primary_location":{"id":"doi:10.1145/3674225.3674369","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3674225.3674369","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 International Conference on Power Electronics and Artificial Intelligence","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/A5102156509","display_name":"Qian Guo","orcid":"https://orcid.org/0000-0003-1728-7581"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Qian Guo","raw_affiliation_strings":["State Grid Smart Grid Research Institute, China"],"raw_orcid":"https://orcid.org/0000-0003-1728-7581","affiliations":[{"raw_affiliation_string":"State Grid Smart Grid Research Institute, China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5005843205","display_name":"Wen Shen","orcid":"https://orcid.org/0000-0003-4754-1405"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wen Shen","raw_affiliation_strings":["State Grid Smart Grid Research Institute, China"],"raw_orcid":"https://orcid.org/0000-0003-4754-1405","affiliations":[{"raw_affiliation_string":"State Grid Smart Grid Research Institute, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"797","last_page":"801"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9927999973297119,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9927999973297119,"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/T12357","display_name":"Digital Media Forensic Detection","score":0.9706000089645386,"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"}},{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9663000106811523,"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/generative-adversarial-network","display_name":"Generative adversarial network","score":0.77065110206604},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6502139568328857},{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.5776019096374512},{"id":"https://openalex.org/keywords/power","display_name":"Power (physics)","score":0.4362739324569702},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.4200816750526428},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.355714350938797},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.24170714616775513},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.12977653741836548}],"concepts":[{"id":"https://openalex.org/C2988773926","wikidata":"https://www.wikidata.org/wiki/Q25104379","display_name":"Generative adversarial network","level":3,"score":0.77065110206604},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6502139568328857},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.5776019096374512},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.4362739324569702},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.4200816750526428},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.355714350938797},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.24170714616775513},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.12977653741836548},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3674225.3674369","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3674225.3674369","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 International Conference on Power Electronics and Artificial Intelligence","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":7,"referenced_works":["https://openalex.org/W1981276685","https://openalex.org/W2981447707","https://openalex.org/W3088321389","https://openalex.org/W6600186770","https://openalex.org/W6605588651","https://openalex.org/W6608993855","https://openalex.org/W6630827713"],"related_works":["https://openalex.org/W2502115930","https://openalex.org/W2482350142","https://openalex.org/W4246396837","https://openalex.org/W3126451824","https://openalex.org/W1561927205","https://openalex.org/W3191453585","https://openalex.org/W4297672492","https://openalex.org/W4310988119","https://openalex.org/W4285226279","https://openalex.org/W4385421777"],"abstract_inverted_index":{"Aiming":[0],"at":[1],"the":[2,6,13,26,33,54,73,99,102,117,121,132,138,142,161,171,183,187],"problem":[3],"that":[4,137],"in":[5,145,152],"current":[7],"environment":[8],"of":[9,22,28,70,124,186],"power":[10,46],"data":[11,23,29,34,47,82,91,109,119,123,126,139,173,178],"usage,":[12],"increased":[14],"openness,":[15],"frequent":[16],"flow":[17],"and":[18,58,86,113,128,156,177,180],"complex":[19],"interaction":[20],"objects":[21],"lead":[24],"to":[25,65,79,106,116,160,169],"prevalence":[27],"leakage":[30],"risk":[31],"throughout":[32],"life":[35],"cycle,":[36],"this":[37,146],"study":[38],"proposes":[39],"a":[40],"generative":[41,74],"adversarial":[42,75],"network":[43,76],"model":[44,51,103,143],"for":[45,120,174],"anonymization":[48],"protection.":[49],"The":[50],"first":[52],"parses":[53],"original":[55,118,122,133,162,172,188],"JSON":[56],"file":[57],"encodes":[59],"it":[60,165],"using":[61],"different":[62,68],"feature":[63],"encoders":[64],"effectively":[66,181],"handle":[67],"types":[69],"variables.":[71],"Second,":[72],"is":[77,88,104],"improved":[78],"generate":[80,107],"anonymized":[81,108],"through":[83],"loss":[84],"feedback,":[85],"privacy":[87,184],"protected":[89],"during":[90],"generation":[92],"by":[93,141],"adding":[94],"random":[95],"noise.":[96],"Compared":[97],"with":[98,110,131],"existing":[100],"methods,":[101],"able":[105],"high":[111],"utility":[112,155],"strong":[114],"similarity":[115,158],"mixed":[125],"types,":[127],"realize":[129,182],"decoupling":[130],"data.":[134,189],"Experiments":[135],"demonstrate":[136],"synthesized":[140],"proposed":[144],"paper":[147],"has":[148],"significantly":[149],"reduced":[150],"differences":[151],"machine":[153],"learning":[154],"statistical":[157],"compared":[159],"data,":[163],"thus":[164],"can":[166],"be":[167],"used":[168],"replace":[170],"mining":[175],"analysis":[176],"sharing,":[179],"protection":[185]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
