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

Testing method and system for attacking machine learning products

A technology of machine learning and testing methods, applied in transmission systems, electrical components, etc., can solve problems such as lack of test results, singleness, and traditional testing methods, and achieve the effects of ensuring information security, improving security, and novel angles

Active Publication Date: 2021-01-26
SICHUAN CHANGHONG ELECTRIC CO LTD
View PDF13 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] At present, when conducting security testing of machine learning products, there are limitations such as traditional, single testing methods, and lack of significant test results.

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
  • Testing method and system for attacking machine learning products
  • Testing method and system for attacking machine learning products

Examples

Experimental program
Comparison scheme
Effect test

Embodiment

[0025] like figure 1 As shown, a test method for attacking machine learning products includes the following steps:

[0026] Preconditions: the attacked machine learning product server (for example, a firewall), a PC with an operating system of WIN7 or WIN8 or WIN10 or Linux;

[0027] Step 1. Use the malicious sample test set to conduct periodic attack access to the machine learning product. The malicious test sample set includes multiple pieces of malicious access data; wherein, the number of malicious access data for attack access to the machine learning product is greater than that of the same period The normal visit volume of machine learning products, the cycle of malicious sample test set attack access to machine learning products is longer than the cycle of the defense algorithm of the machine learning products;

[0028] Step 2: The machine learning product obtains the characteristic factors of multiple pieces of malicious access data in the malicious sample test set, a...

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 test method for attacking a machine learning product, comprising the following steps: using a malicious sample test set to periodically attack and access the machine learning product; the machine learning product obtains multiple pieces of malicious access data in the malicious sample test set characteristic factors, and analyze the characteristic factors, and classify and manage the characteristic factors according to the analysis results; once again, a piece of malicious access data in the malicious sample test set is used to attack and access the machine learning product, and the machine learning product maliciously accesses the piece of data The feature factors in the access data are analyzed, and compared with the feature factors in the classified normal access feature value library and abnormal access feature value library, it is judged whether it is a normal access or an abnormal access; the judgment result is output; the invention also discloses A test system for attacking machine learning products, the invention further improves the security of machine learning products.

Description

technical field [0001] The invention relates to the technical field of Internet security testing, in particular to a testing method and system for attacking machine learning products. Background technique [0002] With the rapid development of the Internet, the security of the Internet has been paid more and more attention by people, and the attack and protection methods of the Internet are also gradually upgraded. The rise and application of machine learning have brought a great challenge to security testing. After a long period of development, the application of machine learning has emerged in various fields. Since there is no effective test method for network application modules made by machine learning, a test method for network attackers to use machine learning products to attack has emerged as the times require. [0003] At present, when conducting security testing of machine learning products, there are limitations such as traditional, single testing methods, and lac...

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): H04L29/06
Inventor 钟倩
Owner SICHUAN CHANGHONG ELECTRIC CO LTD
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