Cloud-assisted privacy-conscious large-scale Markowitz portfolio

Zhang, Yushu; Jiang, Jin; Xiang, Yong; Zhu, Ye; Wan, Liangtian; Xie, Xiyuan

doi:10.1016/j.ins.2018.12.055

Cited by 13 publications

(5 citation statements)

References 33 publications

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“…When searching for reliable dealers, the interview method, content analysis of official sites and other Internet resources were used. When developing recommendations for compiling an investment portfolio of precious metals, the portfolio approach of Markowitz (Zhang et al, 2020) assumes the optimal choice of the asset ratio based on the riskreturn ratio. In assessing the prospects for silver in relation to other precious metals, the authors turned to the comparative method.…”

Section: Methodsmentioning

confidence: 99%

Silver Investment Coins As A Guarantee Of Financial Security

Orishev¹

2021

European Proceedings of Social and Behavioural Sciences

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Section: Methodsmentioning

confidence: 99%

Silver Investment Coins As A Guarantee Of Financial Security

Orishev¹

2021

European Proceedings of Social and Behavioural Sciences

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“…In addition, some outsourcing protocols are directly oriented to practical engineering application scenarios. An outsourcing protocol for Markowitz portfolio was proposed by Zhang et al in [27], an outsourcing protocol for data classification was proposed by Li et al in [28], an outsourcing protocol for the storage and statistics of smart meter data was proposed by Zhang et al in [29], and an outsourcing protocol for biometric identification was proposed by Zhu et al in [30]. Moreover, Li et al proposed an optimal GPUaccelerated multimedia processing service pricing strategy in [31].…”

Section: Related Workmentioning

confidence: 99%

Efficient and Privacy-Preserving Outsourcing of 2D-DCT and 2D-IDCT

Zhang

et al. 2020

Wireless Communications and Mobile Computing

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As a subset of discrete Fourier transform (DFT), discrete cosine transform (DCT), especially two-dimensional discrete cosine transform (2D-DCT), is an important mathematical tool for digital signal processing. However, the computational complexity of 2D-DCT is quite high, which makes it impossible to meet the requirements in some signal processing fields with large signal sizes. In addition, to optimize the 2D-DCT algorithm itself, seeking help from a cloud platform is considered to be an excellent alternative to dramatically speeding up 2D-DCT operations. Still, there are three key challenges in cloud computing outsourcing that need to be addressed, including protecting the privacy of input and output data, ensuring the correctness of the returned results, and ensuring adequate local cost savings. In this paper, we explore the design of a practical outsourcing protocol for 2D-DCT and 2D-IDCT, which well solves the above three challenges. Both theoretical analysis and simulation experiment results not only confirm the feasibility of the proposed protocol but also show its outstanding performance in efficiency.

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“…Among them, there are the outsourcing of matrix inversion [24], the outsourcing of linear programming [25], and the outsourcing of support vector machine (SVM) [26]. Recently, efforts have been made to apply cloud computing to specific real-world scenarios, and the corresponding research results appeared in [27]- [29].…”

Section: Related Workmentioning

confidence: 99%

Efficient and Secure Outsourcing of DFT, IDFT, and Circular Convolution

et al. 2019

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Discrete Fourier transform (DFT), inverse DFT (IDFT), and circular convolution are important tools for analyzing and designing discrete signals and systems, and are widely used in various industries. In order to pursue faster operational efficiencies or more accurate operational results, engineering calculations are often required to be quick and easy. Therefore, it is necessary to reduce the local computational overhead required to perform DFT, IDFT, and circular convolution. In addition to improving the algorithms themselves, cloud computing outsourcing is also an optional method. In this paper, in response to the new challenges brought by cloud computing outsourcing, we design and propose an efficient and secure cloud computing outsourcing protocol for DFT, IDFT, and circular convolution. Through a theoretical explanation and simulation experiment, we show the efficiency, security, and verifiability of the proposed protocol. INDEX TERMS Computing outsourcing, discrete Fourier transform, circular convolution, cloud computing.

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Cloud-assisted privacy-conscious large-scale Markowitz portfolio

Cited by 13 publications

References 33 publications

Silver Investment Coins As A Guarantee Of Financial Security

Silver Investment Coins As A Guarantee Of Financial Security

Efficient and Privacy-Preserving Outsourcing of 2D-DCT and 2D-IDCT

Efficient and Secure Outsourcing of DFT, IDFT, and Circular Convolution

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