Earticle

초록

영어

To overcome the dependence on prior knowledge of traditional filtering algorithm, this paper proposes a novel non-parameter and adaptive multivariate empirical mode decomposition interval threshold (MEMD-IT) denoising approach for signal preprocessing of electromagnetic template attack(ETA). MEMD-IT can reduce the discontinuity induced by traditional MEMD-DT and aims to remove the Gaussian noise coupled into side-channel electromagnetic radiations. The proposed method and some other filters such as butterworth low-pass filter(BLPF)，wavelet threshold denoising and MEMD direct threshold (MEMD-DT) denoising are applied to analyze the electromagnetic radiation traces intercepted while cipher device was implementing RC4 encryption algorithm. Furthermore, twin SVM multi-class classifier based ETA was performed to evaluate the attack results. In the same attack scenario, the highest predictive success rate for 9 Hamming Weights of the key reached 92%,90%,84%,83% and 73% for MEMD-IT, WFTF, MEMD-DT,WULETF and BLPF preprocessing methods, respectively. The experiment results indicate that our proposed scheme has a significant performance compared with the traditional ETA.

목차

Abstract
 1. Introduction
 2. MEMD Based Denoising
  2.1. Criterion of Selecting Relevant Modes
  2.2. MEMD Interval Threshold Denoising
 3. Electromagnetic Radiations Preprocessing Based on MEMD-IT
  3.1. Electromagnetic Radiations Interception
  3.2. Preprocessing Based on MEMD-IT
 4. Electromagnetic Side-Channel Attack Analysis Based on TWSVM
  4.1. Feature Selection of the Traces
  4.2. Side-Channel Analysis Based on TWSVM
 5. Conclusion
 References

키워드

저자

• Duan Li [ School of Electronic Engineering, Beijing University of Posts and Telecommunications, Beijing, China / School of Electrical Engineering and Automation, Henan Polytechnic University, Jiaozuo, China ]
• Hong-xin Zhang [ School of Electronic Engineering, Beijing University of Posts and Telecommunications, Beijing, China / 3Beijing Key Laboratory of Work Safety Intelligent Monitoring (Beijing University of Posts and Telecommunications), Beijing, China ] Corresponding Author
• Qiang Li [ School of Electronic Engineering, Beijing University of Posts and Telecommunications, Beijing, China ]
• Xinjie Zhao [ Institute of North Electronic Equipment, Beijing, China ]
• Pengfei He [ School of Opto-electronic Information Science and Technology, Yantai University, Yantai, China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Signal Processing, Image Processing and Pattern Recognition

• 간기

  격월간

• pISSN

  2005-4254

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605