Power consumption analysis method based on mean ridge regression

Abstract

The invention discloses a power consumption analysis method based on mean ridge regression. The method comprises the following steps: collecting power consumption data in the operation process of password equipment; calculating an intermediate value according to an algorithm structure; establishing a dynamic model for each hypothesis key based on association of a ridge regression thought and actually measured power consumption data, and performing equalization processing on a modeling result of each hypothesis key to establish a power consumption model; and calculating the correlation between the output value of the power consumption model and the actually measured power consumption data by adopting a Pearson's correlation coefficient, thereby realizing the analysis of internal secret information of the cryptographic algorithm and recovering the secret key information of the cryptographic equipment. According to the analysis method, the matrix dimension output by the power consumption model is effectively reduced through mean value modeling, and the calculation complexity of subsequent correlation analysis is effectively reduced. The analysis method has universality and is suitable for most block cipher algorithms.

Description

technical field [0001] The invention relates to the field of information security, in particular to a power analysis method based on mean ridge regression. Background technique [0002] The power consumption analysis method is one of the most powerful attack methods in the field of side channel attacks, which can allow attackers to make full use of the power consumption information leaked during the operation of the encryption device to recover the key. Common power analysis methods include simple power analysis (Simple Power Analysis, SPA), differential power analysis (Differential Power Analysis, DPA), correlation power analysis (Correlation Power Analysis, CPA), mutual information analysis (MutualInformation Analysis, MIA) and Template Attack (Template Attack, TA), etc. In this type of attack method, commonly used power consumption models include the Hamming weight model, the Hamming distance model, and the like. This kind of attack method has the advantages of intuitiv...

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Problems solved by technology

Therefore, people combined linear regression with power consumption analysis and proposed corresponding attack schemes. For example, Schindler et al. [1] introduced DPA based on linear regression for the first time by integrating stochastic models that can theoretically describe any leakage function; Germany BSI [2] theoretically studied a continuous model based on linear regression, fully considered the influence of feature points and noise, and reduced the error by averaging the results; in order to solve the numerical problems in the process of linear regression inversion, Wang et al[ 3] Propose a differential power analysis method based on ridge regression, add constraints to the coefficients of linear regression, and theoretically analyze the feasibility of improving data overfitting. This method is biased towards modeling analysis methods, and its experimental results are also consistent with template attacks. For comparison, although the method can be extended to non-modeling analysis methods, the paper does not elaborate

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