The 7th International Conference on Next Generation Computing 2021 (2021.11)바로가기
페이지
pp.272-273
저자
Hyunil Kim, Ongee Jeong, Youhyun Kim, Inkyu Moon
언어
영어(ENG)
URL
https://www.earticle.net/Article/A448065
원문정보
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
키워드
CryptanalysisFeistel networkDeep learning
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 ]