TY - JOUR
T1 - Application of multi-party computation and error correction with image enhancement and convolution neural networks based on cloud computing
AU - Liao, Teh Lu
AU - Peng, Chiau Yuan
AU - Hou, Yi You
N1 - Funding Information:
This work was financially supported by the National Science and Technology Council, Taiwan, under grant 111‐2218‐E‐006‐009‐MBK and 111‐2218‐E‐006‐018.
Publisher Copyright:
© 2023 The Authors. IET Image Processing published by John Wiley & Sons Ltd on behalf of The Institution of Engineering and Technology.
PY - 2023/5/11
Y1 - 2023/5/11
N2 - With the development of technology, people work hard on image processing and artificial intelligence which require a lot of computer resources. Instead of simply speeding up calculations with processors, people develop the technology of the Cloud with the Internet which performs high-quality calculations and has quite a huge amount of storage. Thus, in this paper, the authors use a kind of encryption methods, Secure Multi-Party Computation (SMPC), to protect the important information which is based on the absence of a trusted party and does not use specific keys or methods to maintain the confidentiality of data. Furthermore, the authors also use the error correction, Berlekamp–Welch (BW) algorithm, to double-check the correction of the information. To apply the two algorithms to image enhancement and convolution neural networks (CNN), the authors will also discuss the homomorphism in all operations, including addition, multiplication, division etc., and find the best way to encrypt and decrypt the information. Finally, the authors will implement the system with cloud computing to decrease the consumption of computer resources and build a system that can do image enhancement and CNN.
AB - With the development of technology, people work hard on image processing and artificial intelligence which require a lot of computer resources. Instead of simply speeding up calculations with processors, people develop the technology of the Cloud with the Internet which performs high-quality calculations and has quite a huge amount of storage. Thus, in this paper, the authors use a kind of encryption methods, Secure Multi-Party Computation (SMPC), to protect the important information which is based on the absence of a trusted party and does not use specific keys or methods to maintain the confidentiality of data. Furthermore, the authors also use the error correction, Berlekamp–Welch (BW) algorithm, to double-check the correction of the information. To apply the two algorithms to image enhancement and convolution neural networks (CNN), the authors will also discuss the homomorphism in all operations, including addition, multiplication, division etc., and find the best way to encrypt and decrypt the information. Finally, the authors will implement the system with cloud computing to decrease the consumption of computer resources and build a system that can do image enhancement and CNN.
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U2 - 10.1049/ipr2.12767
DO - 10.1049/ipr2.12767
M3 - Article
AN - SCOPUS:85148880062
SN - 1751-9659
VL - 17
SP - 1931
EP - 1950
JO - IET Image Processing
JF - IET Image Processing
IS - 6
ER -