Earticle

초록

영어

To manage the big data in constraint resources has difficulties and challenges. The power and the cost can be saved when the cloud services are used to process and store the data. However, the data includes the personal information that can be sensitive and should be hidden from the others. So we propose the privacy-preserving classification scheme for image data. The pixel-based learning is the scheme that is adapted to the cryptosystem, and is used to classify the encrypted images. Our proposed deep learning model has the convolutional layers that has the same size of the kernel with the block size in the cryptographic algorithm. The experiment results show that it can improve the accuracy on classification of encrypted images, and make it possible to use the private data securely.

목차

Abstract
I. INTRODUCTION
II. THEORY
A. Double Random Phase Encoding (DRPE)
B. Data Encryption Standard (DES)
III. PROPOSED SCHEME
IV. EXPERIMENT RESULTS
V. CONCLUSION
ACKNOWLEDGMENT
REFERENCES

저자

• Ongee Jeong [ Department of Robotics Engineering DGIST ]
• Youhyun Kim [ Department of Robotics Engineering DGIST ]
• Inkyu Moon [ Department of Robotics Engineering DGIST ]

참고문헌