Earticle

초록

영어

The ciphertexts obtained by traditional encryption techniques is not totally random sequence forms. Many cryptanalytic studies based on mathematical analysis such as linear cryptanalysis and differential cryptanalysis have been conducted. Recently, deep learning-based cryptanalysis have been proposed to show more powerful attacks than the other mathematical-based approaches. In this paper, we propose a new automated deep learning-based approach to break encryption algorithms with Feistel structure.

목차

Abstract
I. INTRODUCTION
II. BACKGROUNDS AND RELATED WORKS
A. Backgrounds
B. Related works
III. OUR MODEL
IV. EXPERIMENTS
V. CONCLUSION
ACKNOWLEDGMENT
REFERENCES

저자

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

참고문헌