Code Characterization With Graph Convolutions and Capsule Networks

Code Characterization With Graph Convolutions and Capsule Networks

We propose SiCaGCN, a learning system to predict the similarity of a given software code to a set of codes that are permitted to run on a computational resource, such as a supercomputer or a cloud server. This code characterization allows us to detect abusive codes. Our system relies on a structural...

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Bibliographic Details
Main Authors: Poornima Haridas, Gopinath Chennupati, Nandakishore Santhi, Phillip Romero, Stephan Eidenbenz
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Capsule networks
control flow graph
GCN
similarity
Eigen values
Online Access:https://ieeexplore.ieee.org/document/9149622/

Internet

https://ieeexplore.ieee.org/document/9149622/

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