Consortium blockchain-based SIFT: Outsourcing encrypted feature extraction in the D2D network
Privacy-preserving outsourcing algorithms for feature extraction not only reduce users' storage and computation overhead but also preserve the image privacy. However, the existing schemes still suffer from deficiencies induced by security, applications, efficiency and storage. To solve the prob...
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2018
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sg-smu-ink.sis_research-61442020-06-26T07:30:12Z Consortium blockchain-based SIFT: Outsourcing encrypted feature extraction in the D2D network FENG, Xiaoqin MA, Jianfeng FENG, Tao MIAO, Yinbin LIU, Ximeng Privacy-preserving outsourcing algorithms for feature extraction not only reduce users' storage and computation overhead but also preserve the image privacy. However, the existing schemes still suffer from deficiencies induced by security, applications, efficiency and storage. To solve the problems, we implement a consortium chain-based outsourcing feature extraction scheme over encrypted images by using the smart contract, distributed autonomous corporation (DAC), sharding technique, and device to device (D2D) communication, which is secure, widely applied, highly efficient, and has less storage overhead. First, the effectiveness, security, and performance of our scheme are analyzed. Then, the efficiency and storage overhead of our scheme are presented by conducting experimental results. 2018-01-01T08:00:00Z text application/pdf https://ink.library.smu.edu.sg/sis_research/5141 info:doi/10.1109/ACCESS.2018.2869856 https://ink.library.smu.edu.sg/context/sis_research/article/6144/viewcontent/08463445_pvoa.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University Outsourcing feature extraction consortium chain smart contract DAC sharding technique D2D communication Information Security |
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Outsourcing feature extraction consortium chain smart contract DAC sharding technique D2D communication Information Security |
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Outsourcing feature extraction consortium chain smart contract DAC sharding technique D2D communication Information Security FENG, Xiaoqin MA, Jianfeng FENG, Tao MIAO, Yinbin LIU, Ximeng Consortium blockchain-based SIFT: Outsourcing encrypted feature extraction in the D2D network |
description |
Privacy-preserving outsourcing algorithms for feature extraction not only reduce users' storage and computation overhead but also preserve the image privacy. However, the existing schemes still suffer from deficiencies induced by security, applications, efficiency and storage. To solve the problems, we implement a consortium chain-based outsourcing feature extraction scheme over encrypted images by using the smart contract, distributed autonomous corporation (DAC), sharding technique, and device to device (D2D) communication, which is secure, widely applied, highly efficient, and has less storage overhead. First, the effectiveness, security, and performance of our scheme are analyzed. Then, the efficiency and storage overhead of our scheme are presented by conducting experimental results. |
format |
text |
author |
FENG, Xiaoqin MA, Jianfeng FENG, Tao MIAO, Yinbin LIU, Ximeng |
author_facet |
FENG, Xiaoqin MA, Jianfeng FENG, Tao MIAO, Yinbin LIU, Ximeng |
author_sort |
FENG, Xiaoqin |
title |
Consortium blockchain-based SIFT: Outsourcing encrypted feature extraction in the D2D network |
title_short |
Consortium blockchain-based SIFT: Outsourcing encrypted feature extraction in the D2D network |
title_full |
Consortium blockchain-based SIFT: Outsourcing encrypted feature extraction in the D2D network |
title_fullStr |
Consortium blockchain-based SIFT: Outsourcing encrypted feature extraction in the D2D network |
title_full_unstemmed |
Consortium blockchain-based SIFT: Outsourcing encrypted feature extraction in the D2D network |
title_sort |
consortium blockchain-based sift: outsourcing encrypted feature extraction in the d2d network |
publisher |
Institutional Knowledge at Singapore Management University |
publishDate |
2018 |
url |
https://ink.library.smu.edu.sg/sis_research/5141 https://ink.library.smu.edu.sg/context/sis_research/article/6144/viewcontent/08463445_pvoa.pdf |
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1770575292596748288 |