Detect software vulnerabilities with weight biases via graph neural networks.
Huijiang LiuShuirou JiangXuexin QiYang QuHui LiTingting LiChen GuoShikai GuoPublished in: Expert Syst. Appl. (2024)
Keyphrases
- neural network
- pattern recognition
- graph theory
- source code
- computer systems
- attack graph
- fuzzy logic
- software tools
- graph representation
- structured data
- genetic algorithm
- neural network model
- graph structure
- directed graph
- directed acyclic graph
- software design
- software development
- edge weights
- security vulnerabilities
- software maintenance
- security risks
- feed forward
- software projects
- multilayer perceptron
- automatic detection
- control system
- software systems
- weight update
- bipartite graph
- artificial neural networks
- user interface
- weight function
- open source
- detection method
- graph partitioning
- countermeasures
- fault diagnosis
- graph model
- software architecture
- connected components
- graph matching