Class template attack method based on deep learning convolutional neural network

A convolutional neural network and deep learning technology, applied in the field of template-like attacks based on deep learning convolutional neural networks, can solve problems such as inaccurate template construction, improve the attack success rate, overcome construction inaccuracy, and strengthen generalization effect of ability

Active Publication Date: 2019-07-23
UNIV OF ELECTRONICS SCI & TECH OF CHINA
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Problems solved by technology

[0004] The purpose of the present invention is to overcome the inaccuracy of template construction in the prior art, and to propose a class template based on deep learning convolutional neural netwo

Method used

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  • Class template attack method based on deep learning convolutional neural network
  • Class template attack method based on deep learning convolutional neural network
  • Class template attack method based on deep learning convolutional neural network

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[0026] Specific embodiments of the present invention will be described below in conjunction with the accompanying drawings, so that those skilled in the art can better understand the present invention. It should be noted that in the following description, when detailed descriptions of known functions and designs may dilute the main content of the present invention, these descriptions will be omitted here.

[0027] figure 1 It is a flow chart of a specific implementation of the template-like attack method based on the deep learning convolutional neural network of the present invention.

[0028] In this example, if figure 1 As shown, the class template attack method of the present invention based on deep learning convolutional neural network comprises the following steps:

[0029] Step S1: Build a deep learning convolutional neural network

[0030] Convolutional neural network (CNN) in deep learning is a special type of neural network inspired by the physiological process of ...

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Abstract

The invention discloses a class template attack method based on a deep learning convolutional neural network. The method aims at characteristics of energy traces and types of Hamming weights, a deep learning convolutional neural network with a unique five-layer structure is built and is used for predicting Hamming weight of the attack energy trace; the dependence of traditional template attack ontemplate construction is well solved, the deep learning convolutional neural network is used as a class template for predicting the energy trace Hamming weight, the problem that template constructionis inaccurate is solved, the attack success rate is increased, and meanwhile the energy trace Hamming weight prediction method has high generalization capacity.

Description

technical field [0001] The invention belongs to the technical field of cryptographic algorithm analysis and detection, and more specifically, relates to a template-like attack method based on a deep learning convolutional neural network. Background technique [0002] Template attack is a very powerful side channel attack method. In the prior art, template attack is divided into two stages: template construction and template matching. [0003] In the Chinese invention patent application published on January 22, 2019, the publication number is CN109257160A, and the name is "a side-channel template attack method based on decision tree", a template attack method is announced: first collect energy traces, Establish the energy consumption matrix U, build a decision tree model, select the features that appear from the root node to the leaf node, and then extract the energy consumption matrix U according to the selected features, establish the energy consumption matrix T, and then ...

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Application Information

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IPC IPC(8): H04L9/00H04L9/06G06N3/04
CPCH04L9/002H04L9/0631G06N3/045
Inventor 居太亮于赛倪志杰
Owner UNIV OF ELECTRONICS SCI & TECH OF CHINA
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