Adversarial sample generation method and device, electronic equipment and storage medium

A technology against samples and samples, applied in artificial life, biological models, electrical digital data processing, etc., can solve the problems of low attack success rate and low search algorithm speed, so as to improve search speed, increase attack success rate, and good The effect of practicality

Active Publication Date: 2020-09-11
TSINGHUA UNIV
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  • Application Information

AI Technical Summary

Problems solved by technology

[0005] The embodiment of the present invention provides a method, device, electronic device and storage medium for generating an adversarial example, to solve the problem of the low speed of the search algorithm in the prior art and the The problem of low attack success rate

Method used

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  • Adversarial sample generation method and device, electronic equipment and storage medium
  • Adversarial sample generation method and device, electronic equipment and storage medium
  • Adversarial sample generation method and device, electronic equipment and storage medium

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Embodiment Construction

[0051] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments It is a part of embodiments of the present invention, but not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without creative efforts fall within the protection scope of the present invention.

[0052] The flow chart of a specific implementation of the method for generating an adversarial sample provided by the embodiment of the present invention is as follows figure 1 As shown, the method specifically includes:

[0053] Step S101: Obtain the original text;

[0054]Step S102: determining a candidate set of replacement words for each wor...

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Abstract

Embodiments of the invention provide an adversarial sample generation method and device, electronic equipment and a storage medium. The method comprises the steps of obtaining an original text; determining a replacement word candidate set of each word in the original text; and based on a particle swarm optimization algorithm, searching a sample of the attack target model from a discrete space formed by the combination of the replacement word candidate sets, and generating an adversarial sample. According to the embodiment of the invention, the particle swarm optimization algorithm is used forsearching the adversarial sample, and the particle swarm optimization is more efficient than the genetic algorithm as a meta-heuristic group evolution calculation method, so that the search speed canbe increased when the algorithm is used for searching the adversarial sample, and the attack success rate can also be increased. For different natural language processing models, the embodiment of theinvention can quickly and efficiently generate a large number of high-quality confrontation samples, successfully cheat the target model and further expose the vulnerability of the target model, andhas good practicability.

Description

technical field [0001] The present invention relates to the technical field of natural speech processing, in particular to a method, device, electronic equipment and storage medium for generating an adversarial example. Background technique [0002] Adversarial attack refers to the process of making the judgment of the target model wrong by generating adversarial samples. Adversarial attacks can expose the vulnerability of machine learning models, thereby improving the robustness and interpretability of the models. Text adversarial attack refers to the process of generating adversarial samples by modifying the original text to make the judgment of the natural language processing model wrong. [0003] Existing research shows that deep learning models are highly vulnerable to adversarial attacks, such as simple modifications to abusive texts that can fool state-of-the-art abusive detection systems. In view of the fact that the natural language processing model based on deep ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62G06N3/00G06F40/289G06F40/247
CPCG06N3/006G06F40/289G06F40/247G06F18/214
Inventor 岂凡超臧原刘知远孙茂松
Owner TSINGHUA UNIV
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