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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書目詳細資料
Main Authors:	NGUYEN, Huu Hoang, NGUYEN, Nhat Minh, XIE, Chunyao, AHMADI, Zahra, KUDENKO, Daniel, DOAN, Thanh Nam, JIANG, Lingxiao
格式:	text
語言:	English
出版:	Institutional Knowledge at Singapore Management University 2022
主題:	heterogeneous graphs graph embedding graph neural networks vulnerability detection smart contracts Ethereum blockchain Information Security Software Engineering
在線閱讀:	https://ink.library.smu.edu.sg/sis_research/7627 https://ink.library.smu.edu.sg/context/sis_research/article/8630/viewcontent/dsaa22mando.pdf
標簽:	添加標簽沒有標簽, 成為第一個標記此記錄!
機構:	Singapore Management University
語言:	English

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