Chip side channel attack noise reduction preprocessing method based on residual learning

A side-channel attack and preprocessing technology, which is applied in neural learning methods, internal/peripheral computer component protection, biological neural network models, etc., can solve the serious negative impact of noise on side-channel analysis, and it is difficult to use and learn noise distribution characteristics, Reduce the adverse effects of noise and other problems, achieve the effect of small noise variance, high signal-to-noise ratio, and improve accuracy

CN113051628APending Publication Date: 2021-06-29BEIJING INST OF COMP TECH & APPL
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Publication Date
2021-06-29

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Abstract

The invention relates to a chip side channel attack noise reduction preprocessing method based on residual learning, and belongs to the technical field of chip security detection. The invention provides a chip side channel attack noise reduction preprocessing method based on residual learning, and the method comprises the steps: learning a mapping relation between an original energy trace and noise through constructing a deep residual network, thereby generating any noise corresponding to an energy trace which accords with the characteristics of collection equipment, subtracting the generated noise from the original energy trace, and completing the noise reduction pretreatment step.
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Description

technical field

[0001] The invention belongs to the technical field of chip security detection, and in particular relates to a chip side channel attack noise reduction preprocessing method based on residual error learning. Background technique

[0002] Cryptographic algorithms exist in information security systems in the form of software or hardware implementations, and these systems are usually deployed in an untrusted or even malicious environment. When any electronic device is running, it may leak physical state information closely related to its internal state (time difference, energy consumption, electromagnetic radiation, sound leakage, light radiation, heat radiation, etc.). Attackers can use the physical state information leaked when these devices are running to recover key information. This type of attack method is called a side channel attack. Side-channel attacks are passive and non-invasive. Attackers can detect and collect encrypted side information (typically ...

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Embodiment Construction

[0032] In order to make the purpose, content, and advantages of the present invention clearer, the specific implementation manners of the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments.

[0033] The present invention provides a chip side channel attack noise reduction preprocessing method based on residual learning, which learns the mapping between original energy traces and noise by constructing a deep residual network relationship, so that any noise corresponding to the energy trace corresponding to the characteristics of the acquisition device can be generated, and the noise reduction preprocessing step can be completed by subtracting the generated noise from the original energy trace.

[0034] Such as figure 1 , figure 2 As shown, a kind of chip side channel attack noise reduction preprocessing method based on residual learning provided by the present invention includes the following steps:

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