An Improved Correlation Electromagnetic Analysis Based On Genetic Algorithm Optimization
- Resource Type
- Conference
- Authors
- Sun, Shaofei; Zhang, Hongxin; Cheng, Weijun; Dong, Liang; Wang, Yang; Cui, Xiaotong
- Source
- 2019 International Workshop on Electromagnetics: Applications and Student Innovation Competition (iWEM) Electromagnetics: Applications and Student Innovation Competition (iWEM), 2019 International Workshop on. :1-2 Sep, 2019
- Subject
- Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Engineered Materials, Dielectrics and Plasmas
Fields, Waves and Electromagnetics
Signal Processing and Analysis
Genetic algorithms
Cryptography
Electromagnetic analysis
Correlation
Field programmable gate arrays
Correlation coefficient
AES algorithm
genetic algorithm
correlation electromagnetic analysis
interesting points
- Language
Correlation electromagnetic analysis(CEMA) is one of the most powerful ways in side channel analysis. Because it don't need to modify the target device and even can be measured at distance. But in the real scenarios, only those interesting points relevant to the target intermediate value is helpful to recover the secret key. In this paper, we proposed a novel method based on genetic algorithm to select the interesting points, and the hamming distance between S-Box input and S-Box output in first round is chosen as the target intermediate value. We perform our experiment on Sakura-G board against AES-128 algorithm. Our experiment result shows our method is more effective which decreases about 9.1% in trace number than traditional CEMA for AES crypto algorithm to recover the secret key.