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Privacy Preservation in Distributed Subgradient Optimization Algorithms
Lou, Youcheng1,2; Yu, Lean3; Wang, Shouyang2; Yi, Peng4
2018-07-01
Source PublicationIEEE TRANSACTIONS ON CYBERNETICS
ISSN2168-2267
Volume48Issue:7Pages:2154-2165
AbstractIn this paper, some privacy-preserving features for distributed subgradient optimization algorithms are considered. Most of the existing distributed algorithms focus mainly on the algorithm design and convergence analysis, but not the protection of agents' privacy. Privacy is becoming an increasingly important issue in applications involving sensitive information. In this paper, we first show that the distributed subgradient synchronous homogeneous-stepsize algorithm is not privacy preserving in the sense that the malicious agent can asymptotically discover other agents' subgradients by transmitting untrue estimates to its neighbors. Then a distributed subgradient asynchronous heterogeneous-stepsize projection algorithm is proposed and accordingly its convergence and optimality is established. In contrast to the synchronous homogeneous-stepsize algorithm, in the new algorithm agents make their optimization updates asynchronously with heterogeneous stepsizes. The introduced two mechanisms of projection operation and asynchronous heterogeneous-stepsize optimization can guarantee that agents' privacy can be effectively protected.
KeywordAsynchronous optimization distributed optimization heterogeneous-stepsize privacy preservation
DOI10.1109/TCYB.2017.2728644
Language英语
Funding ProjectKey Program of National Natural Science Foundation of China[71433001] ; Key Program of National Natural Science Foundation of China[71631005] ; National Natural Science Foundation of China[71401163] ; Hong Kong Scholars Program[XJ2015049] ; National Program for Support of Top-Notch Young Professionals
WOS Research AreaAutomation & Control Systems ; Computer Science
WOS SubjectAutomation & Control Systems ; Computer Science, Artificial Intelligence ; Computer Science, Cybernetics
WOS IDWOS:000435342100017
PublisherIEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Citation statistics
Cited Times:1[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.amss.ac.cn/handle/2S8OKBNM/30483
Collection系统科学研究所
Affiliation1.Chinese Univ Hong Kong, Dept Syst Engn & Engn Management, Hong Kong, Hong Kong, Peoples R China
2.Chinese Acad Sci, Acad Math & Syst Sci, Beijing 100190, Peoples R China
3.Beijing Univ Chem Technol, Sch Econ & Management, Beijing 100029, Peoples R China
4.Univ Toronto, Dept Elect & Comp Engn, Toronto, ON M5S 3G4, Canada
Recommended Citation
GB/T 7714
Lou, Youcheng,Yu, Lean,Wang, Shouyang,et al. Privacy Preservation in Distributed Subgradient Optimization Algorithms[J]. IEEE TRANSACTIONS ON CYBERNETICS,2018,48(7):2154-2165.
APA Lou, Youcheng,Yu, Lean,Wang, Shouyang,&Yi, Peng.(2018).Privacy Preservation in Distributed Subgradient Optimization Algorithms.IEEE TRANSACTIONS ON CYBERNETICS,48(7),2154-2165.
MLA Lou, Youcheng,et al."Privacy Preservation in Distributed Subgradient Optimization Algorithms".IEEE TRANSACTIONS ON CYBERNETICS 48.7(2018):2154-2165.
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