Privacy protection based on many-objective optimization algorithm
Zhang, Jiangjiang1; Xue, Fei2; Cai, Xingjuan1; Cui, Zhihua1; Chang, Yu1; Zhang, Wensheng3; Li, Wuzhao4
发表期刊CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE
ISSN1532-0626
2019-10-25
卷号31期号:20页码:14
通讯作者Cui, Zhihua(cuizhihua@gmail.com)
摘要It 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.
关键词achievement scalarizing function angle information index balanceable fitness estimation method many-objective optimization algorithm privacy protection
DOI10.1002/cpe.5342
关键词[WOS]PARTICLE SWARM OPTIMIZATION ; CUCKOO SEARCH ALGORITHM ; NSGA-III ALGORITHM ; BAT ALGORITHM ; EVOLUTIONARY ALGORITHM ; GENETIC ALGORITHM ; FIREFLY ALGORITHM ; PERFORMANCE ; POPULATIONS ; OPERATOR
收录类别SCI
语种英语
资助项目National 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] ; National 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]
项目资助者National 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研究方向Computer Science
WOS类目Computer Science, Software Engineering ; Computer Science, Theory & Methods
WOS记录号WOS:000489324000007
出版者WILEY
引用统计
被引频次:26[WOS]   [WOS记录]     [WOS相关记录]
文献类型期刊论文
条目标识符http://ir.ia.ac.cn/handle/173211/26649
专题精密感知与控制研究中心_人工智能与机器学习
通讯作者Cui, Zhihua
作者单位1.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
推荐引用方式
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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