Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

A method, system and terminal for generating highly transferable adversarial samples

An anti-sample, high transfer technology, applied in the field of deep learning, can solve problems such as low transferability, and achieve the effect of improving transferability, high transferability, and reducing overfitting

Active Publication Date: 2022-05-17
SOUTHWEST PETROLEUM UNIV
View PDF8 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0008] The purpose of the present invention is to overcome the problem of low transferability of adversarial samples generated in the prior art in model attacks, and provide a method, system and terminal for generating adversarial samples with high transferability

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • A method, system and terminal for generating highly transferable adversarial samples
  • A method, system and terminal for generating highly transferable adversarial samples
  • A method, system and terminal for generating highly transferable adversarial samples

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0047] The technical solutions of the present invention will be clearly and completely described below in conjunction with the accompanying drawings. Apparently, the described embodiments are part of the embodiments of the present invention, but not all of them. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.

[0048]In the description of the present invention, it should be noted that the terms belonging to "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer" etc. The indicated direction or positional relationship is based on the direction or positional relationship described in the drawings, and is only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the referred device or element must have a specific o...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention discloses a method, system and terminal for generating highly transferable adversarial samples, which belong to the field of deep learning technology. The low-frequency information of the first target image is added to the randomly selected original image to obtain the first sample; the first sample is obtained randomly from the model pool. Select a first-level sampling model; input the first sample into the first-level sampling model; iteratively calculate the aggregated gradient of the sampling model based on the low-frequency information of the first target image added to the original image, and normalize the aggregated gradient; update the sampling model based on the sign of the gradient The generated adversarial samples are constrained on the value of the adversarial samples, and the first-level temporary adversarial samples are output as the input of the lower-level sampling model; the above steps are repeated to obtain the final generated samples. This application has a multi-level sampling model, which improves the transferability of the final generated adversarial samples. At the same time, the samples of the input sampling model are superimposed with target low-frequency information different from its own category, which can further improve the transferability of adversarial samples.

Description

technical field [0001] The present invention relates to the technical field of deep learning, in particular to a method, system and terminal for generating highly transferable adversarial samples. Background technique [0002] In recent years, with the rapid development of deep learning, its intelligent applications in image recognition, face recognition, unmanned driving, target detection, medical treatment and other fields have become a reality. Compared with traditional methods, deep learning has shown extremely high performance in various fields. However, some studies have shown that deep learning is vulnerable to adversarial attacks due to the existence of adversarial samples. In today's highly informatized and intelligent world, the security guarantee of deep learning algorithms is an unprecedented difficulty and pain point. [0003] The adversarial samples generated by the attacker through carefully designed perturbations are indistinguishable from the real samples t...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
Patent Type & Authority Patents(China)
IPC IPC(8): G06V20/10G06V10/774G06V10/764G06V10/82G06K9/62G06N3/04G06N3/08
Inventor 郑德生陈继鑫周永柯武平张秀荣李政禹温冬吴欣隆
Owner SOUTHWEST PETROLEUM UNIV
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products