MANDO: Multi-level heterogeneous graph embeddings for fine-grained detection of smart contract vulnerabilities

MANDO: Multi-level heterogeneous graph embeddings for fine-grained detection of smart contract vulnerabilities

Learning heterogeneous graphs consisting of different types of nodes and edges enhances the results of homogeneous graph techniques. An interesting example of such graphs is control-flow graphs representing possible software code execution flows. As such graphs represent more semantic information of...

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Bibliographic Details
Main Authors: NGUYEN, Huu Hoang, NGUYEN, Nhat Minh, XIE, Chunyao, AHMADI, Zahra, KUDENKO, Daniel, DOAN, Thanh Nam, JIANG, Lingxiao
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2022
Subjects:
heterogeneous graphs
graph embedding
graph neural networks
vulnerability detection
smart contracts
Ethereum blockchain
Information Security
Software Engineering
Online Access:https://ink.library.smu.edu.sg/sis_research/7627
https://ink.library.smu.edu.sg/context/sis_research/article/8630/viewcontent/dsaa22mando.pdf
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Institution: Singapore Management University
Language: English

Internet

https://ink.library.smu.edu.sg/sis_research/7627
https://ink.library.smu.edu.sg/context/sis_research/article/8630/viewcontent/dsaa22mando.pdf

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