Low Complexity Correlation Power Analysis by Combining Power Trace Biasing and Correlation Distribution Techniques

Side channel attack (SCA) is a class of crypt-analytic attacks for security evaluation of cryptographic and embedded microprocessor implementations. Among several SCA approaches, the correlation power analysis (CPA) is an efficient way to recover the secret key of the specific cryptographic algorithms running on the target devices such as embedded microprocessors. However, the evaluation process is time-consuming since a large number of traces are required to overcome the impact of noise. Hence, this paper proposes new methods to reduce the computation time by using Point of Interest (POI) extractor with the power trace biasing technique and the correlation distribution for the low complexity correlation power analysis (CPA). The theoretical explanations are provided and the experiments on different platforms such as ASCAD and RISC-V processor based databases are conducted to justify the proposed techniques. Especially, our experiments are performed with different protected schemes such as masking, hiding and combined hiding-masking techniques. The experimental results indicate that our proposed methods provide reliable results in comparison with the standard CPA. By using only a half of the power traces for taking the POIs, our first proposal not only decreases the execution time approximately by half but also enhances the success rate of the attack. Moreover, the second method based on power trace biasing technique is proposed in order to achieve better results and reduce the number of traces needed for selecting the POIs. With only 28.9% of given power traces needed, our second proposed technique reduces the execution time to only 2.6 times of the standard CPA.