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...
Saved in:
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: | |
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 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Singapore Management University |
Language: | English |
Similar Items
-
MANDO-GURU: vulnerability detection for smart contract source code by heterogeneous graph embeddings
by: NGUYEN, Huu Hoang, et al.
Published: (2022) -
MANDO-HGT: Heterogeneous graph transformers for smart contract vulnerability detection
by: NGUYEN, Huu Hoang, et al.
Published: (2023) -
Heterogeneous graph neural network with multi-view representation learning
by: SHAO, Zezhi, et al.
Published: (2023) -
Learning on heterogeneous graphs using high-order relations
by: Lee, See Hian, et al.
Published: (2021) -
The 4th workshop on heterogeneous information network analysis and applications (HENA 2021)
by: SHI, Chuan, et al.
Published: (2021)