Software vulnerability detection method and device based on quantum neural network

A quantum neural and software vulnerability technology, applied in the field of software vulnerability detection based on quantum neural network, to achieve the effect of alleviating memory bottlenecks and accurate vulnerability detection

Active Publication Date: 2022-06-28
PLA STRATEGIC SUPPORT FORCE INFORMATION ENG UNIV PLA SSF IEU
View PDF5 Cites 2 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] Aiming at the problem that software vulnerability detection based on classical machine learning has certain limita

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
  • Software vulnerability detection method and device based on quantum neural network
  • Software vulnerability detection method and device based on quantum neural network
  • Software vulnerability detection method and device based on quantum neural network

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0054] like figure 1 As shown, an embodiment of the present invention provides a software vulnerability detection method based on a quantum neural network, comprising the following steps:

[0055] S101: locate the API function in the target program to be detected;

[0056] Specifically, in order to speed up the positioning speed, the target program to be detected may be preprocessed before step S101, specifically: deleting non-ASCII characters and comments in the source code of the target program to be detected.

[0057] S102: Slice the target program to be detected according to the API function to obtain several code fragments;

[0058] Specifically, in the following combination image 3 The slicing process is illustrated, and details are not repeated here.

[0059] It should be noted that API function calls are divided into forward API function calls and backward API function calls. Forward API calls refer to API parameters that receive data directly from the socket, whi...

Embodiment 2

[0101] like Figure 5 As shown, an embodiment of the present invention also provides a software vulnerability detection device based on a quantum neural network, including: a positioning module, a slicing module, a standardization module, an encoding module and a measurement module; wherein:

[0102] The positioning module is used to locate the API functions in the target program to be detected. The slicing module is used for slicing the target program to be detected according to the API function to obtain several code fragments. The normalization module is used to normalize variable names and / or function names in each of the code snippets. The encoding module is used to construct a dictionary based on the standardized code fragments, and then encode each word in the dictionary according to the binary encoding method to obtain a binary vector corresponding to each word, and then encode the corresponding binary vector of each word. The binary vector performs quantum state ang...

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 provides a software vulnerability detection method and device based on a quantum neural network. The method comprises the following steps: step 1, positioning an API function in a target program to be detected; 2, slicing the target program to be detected according to the API function to obtain a plurality of code snippets; 3, standardizing a variable name and/or a function name in each code snippet; 4, constructing a dictionary based on the plurality of standardized code snippets, then coding each word in the dictionary according to a binary coding mode to obtain a binary vector corresponding to each word, and then performing quantum state angle coding on the binary vector corresponding to each word to obtain a quantum state corresponding to each word; and 5, inputting the quantum state corresponding to each word into the trained software vulnerability detection model based on the quantum neural network to obtain vulnerabilities in the target program to be detected.

Description

technical field [0001] The invention relates to the technical field of quantum computing and network security, in particular to a software vulnerability detection method and device based on a quantum neural network. Background technique [0002] With the rapid development and popularization of the network, network security is still a key issue to be solved urgently in the industry. As the core issue of network security, software vulnerability detection has been studied a lot, such as static analysis and dynamic analysis. With the rise of machine learning technology, software vulnerability detection based on machine learning has become a hot spot. At present, this field mainly includes attribute-based software code measurement, code similarity detection, etc. [0003] Although classical machine learning has been proven to be suitable for software vulnerability detection, this research has certain limitations, mainly in the following aspects: (1) It relies on security expert...

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
IPC IPC(8): G06F21/57G06N20/00G06N10/60
CPCG06F21/577G06N20/00G06N10/00Y02D10/00
Inventor 单征周鑫庞建民王俊超岳峰夏冰舒国强刘福东刘文甫许瑾晨郭佳郁赵博宋智辉
Owner PLA STRATEGIC SUPPORT FORCE INFORMATION ENG UNIV PLA SSF IEU
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap