CASIA OpenIR
Privacy protection based on many-objective optimization algorithm
Zhang, Jiangjiang1; Xue, Fei2; Cai, Xingjuan1; Cui, Zhihua1; Chang, Yu1; Zhang, Wensheng3; Li, Wuzhao4
Source PublicationCONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE
ISSN1532-0626
2019-10-25
Volume31Issue:20Pages:14
Corresponding AuthorCui, Zhihua(cuizhihua@gmail.com)
AbstractIt is difficult to protect users' privacy and to process private information due to the complexity and uncertainty of such information. To protect private information quickly and accurately, a many-objective optimization algorithm framework based on the hybrid elite selection strategy is proposed in this paper. First, a mating selection mechanism combined with the achievement scale function and angle information index is used to generate elite offspring of the internal population. Then, the balanceable fitness estimation method is employed to select and update the external archive. To test performance, the proposed algorithm is tested on many-objective optimization problems (MaOPs) and compared with five state-of-the-art algorithms. Experimental simulation results show that the proposed algorithm is more effective in solving MaOPs and can inspire development of a better privacy protection strategy.
Keywordachievement scalarizing function angle information index balanceable fitness estimation method many-objective optimization algorithm privacy protection
DOI10.1002/cpe.5342
WOS KeywordPARTICLE SWARM OPTIMIZATION ; CUCKOO SEARCH ALGORITHM ; NSGA-III ALGORITHM ; BAT ALGORITHM ; EVOLUTIONARY ALGORITHM ; GENETIC ALGORITHM ; FIREFLY ALGORITHM ; PERFORMANCE ; POPULATIONS ; OPERATOR
Indexed BySCI
Language英语
Funding ProjectNational Natural Science Foundation of China[61806138] ; National Natural Science Foundation of China[U1636220] ; National Natural Science Foundation of China[61663028] ; Natural Science Foundation of Shanxi Province[201801D121127] ; PhD Research Startup Foundation of Taiyuan University of Science and Technology[20182002] ; Zhejiang Provincial Natural Science Foundation of China[Y18F030036]
Funding OrganizationNational Natural Science Foundation of China ; Natural Science Foundation of Shanxi Province ; PhD Research Startup Foundation of Taiyuan University of Science and Technology ; Zhejiang Provincial Natural Science Foundation of China
WOS Research AreaComputer Science
WOS SubjectComputer Science, Software Engineering ; Computer Science, Theory & Methods
WOS IDWOS:000489324000007
PublisherWILEY
Citation statistics
Cited Times:8[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/26649
Collection中国科学院自动化研究所
Corresponding AuthorCui, Zhihua
Affiliation1.Taiyuan Univ Sci & Technol, Complex Syst & Computat Intelligence Lab, Taiyuan 030024, Shanxi, Peoples R China
2.Beijing Wuzi Univ, Sch Informat, Beijing, Peoples R China
3.Chinese Acad Sci, State Key Lab Intelligent Control & Management Co, Inst Automat, Beijing, Peoples R China
4.Jiaxing Vocat Tech Coll, Jiaxing, Peoples R China
Recommended Citation
GB/T 7714
Zhang, Jiangjiang,Xue, Fei,Cai, Xingjuan,et al. Privacy protection based on many-objective optimization algorithm[J]. CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE,2019,31(20):14.
APA Zhang, Jiangjiang.,Xue, Fei.,Cai, Xingjuan.,Cui, Zhihua.,Chang, Yu.,...&Li, Wuzhao.(2019).Privacy protection based on many-objective optimization algorithm.CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE,31(20),14.
MLA Zhang, Jiangjiang,et al."Privacy protection based on many-objective optimization algorithm".CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE 31.20(2019):14.
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