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

• المؤلفون الرئيسيون: NGUYEN, Huu Hoang, NGUYEN, Nhat Minh, XIE, Chunyao, AHMADI, Zahra, KUDENKO, Daniel, DOAN, Thanh Nam, JIANG, Lingxiao
• التنسيق: text
• اللغة: English
• منشور في: Institutional Knowledge at Singapore Management University 2022
• الموضوعات: heterogeneous graphs; graph embedding; graph neural networks; vulnerability detection; smart contracts; Ethereum blockchain; Information Security; Software Engineering
• الوصول للمادة أونلاين: https://ink.library.smu.edu.sg/sis_research/7627; https://ink.library.smu.edu.sg/context/sis_research/article/8630/viewcontent/dsaa22mando.pdf
• المؤسسة: Singapore Management University

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...