Block-gram: Mining Knowledgeable Features for Smart Contract Vulnerability Detection
Author:
Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-28124-2_52
Reference19 articles.
1. Wang, S., Ouyang, L., Yuan, Y., Ni, X., Han, X., Wang, F.-Y.: Blockchain-enabled smart contracts: architecture, applications, and future trends. IEEE Trans. Syst. Man Cybern. Syst. 49(11), 2266–2277 (2019)
2. Ma, F., et al.: EVM*: from offline detection to online reinforcement for ethereum virtual machine. In: 2019 IEEE 26th International Conference on Software Analysis, Evolution and Reengineering (SANER), pp. 554–558. IEEE (2019)
3. Sai, A.R., Holmes, C., Buckley, J., Gear, A.L.: Inheritance software metrics on smart contracts. In: Proceedings of the 28th International Conference on Program Comprehension, pp. 381–385 (2020)
4. Durieux, T., Ferreira, J.F., Abreu, R., Cruz, P.: Empirical review of automated analysis tools on 47,587 ethereum smart contracts. In: Proceedings of the ACM/IEEE 42nd International Conference on Software Engineering, pp. 530–541 (2020)
5. Wang, W., Song, J., Xu, G., Li, Y., Wang, H., Su, C.: ContractWard: automated vulnerability detection models for ethereum smart contracts. IEEE Trans. Netw. Sci. Eng. 8(2), 1133–1144 (2020)
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