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

Encryption algorithm identification method based on deep learning graph network

An encryption algorithm and deep learning technology, applied in the field of computer software security, can solve problems such as various file formats, inability to identify encryption, and difficulty in judging whether the encryption mechanism is compliant, so as to facilitate research and reduce the difficulty of research

Active Publication Date: 2020-07-28
NORTHWEST UNIV(CN)
View PDF3 Cites 10 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0014] 3. The file formats are diverse, and it is impossible to identify whether to encrypt, and it is even more difficult to judge whether the encryption mechanism adopted is compliant;

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
  • Encryption algorithm identification method based on deep learning graph network
  • Encryption algorithm identification method based on deep learning graph network
  • Encryption algorithm identification method based on deep learning graph network

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0036] First of all, the applicant explains the technical terms involved in the present invention as follows:

[0037] Basic block: refers to the sequence of statements executed sequentially in the program, in which there is only one entry and one exit, the entry is the first statement in it, and the exit is the last statement in it. A function in code consists of multiple basic blocks.

[0038] Crawling: Refers to the online-to-local copying process of source codes such as web pages, open source libraries, and code hosting platforms using reptile tools such as Octoparse.

[0039]The encryption algorithm identification method based on the deep learning graph network of the present invention is designed with the idea of ​​converting the traditional "binary encryption algorithm identification problem" into a "binary similarity detection problem".

[0040] see figure 1 , the present embodiment provides an encryption algorithm identification method based on a deep learning graph...

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

An encryption algorithm identification method based on a deep learning graph network is composed of a training process and an inspection process, and comprises the following steps: training: constructing a basic source code library for crawled source code data related to encryption; carrying out cross-compiled preprocessing, obtaining a binary code library, respectively extracting statistical characteristics and structural characteristics of a binary encryption algorithm, integrating the statistical characteristics and the structural characteristics to generate an encryption algorithm graph, embedding the encryption algorithm graph into a neural network to become vectors, judging whether codes are similar or not by comparing distances among the vectors, and obtaining a model for judging whether embedded vectors of the encryption algorithm graph are similar or not through training; checking: generating a standard encryption algorithm library, selecting one copy of encryption algorithm which is standardized and has been determined in type; generating an encryption algorithm graph, generating an encryption algorithm graph for the to-be-detected encryption algorithms of unknown types,embedding the encryption algorithm graph into the trained model, sequentially comparing the vector distances with the embedding of the standard encryption algorithm library, and taking the standard algorithm type with the shortest vector distance to the to-be-detected encryption algorithms as the type of the to-be-detected encryption algorithms.

Description

technical field [0001] The invention belongs to the field of computer software security, relates to algorithm encryption and identification, and in particular to an encryption algorithm identification method based on a deep learning graph network. Background technique [0002] 1.1 Related technical background [0003] Information security has now risen to the strategic position of national security. As the core of data transmission security, encryption algorithm is widely used in politics, finance, communication and other aspects. With the development of LoT technology, embedded systems are increasingly used in various loT devices, and their security is also one of the focuses of current information security research. For a long time, in industries with high security requirements such as financial enterprises and government agencies, in addition to using internationally accepted cryptographic algorithm systems and standards such as 3DES, SHA-1, and RSA, there is also a set ...

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 Applications(China)
IPC IPC(8): G06F21/60G06K9/62G06N20/00
CPCG06F21/602G06N20/00G06F2221/2107G06F18/22G06F18/214Y02D10/00
Inventor 龚晓庆常原海汤战勇李朋叶贵鑫陈晓江房鼎益
Owner NORTHWEST UNIV(CN)
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