Detecting Rug Pull Scams on Blockchain via Feature Fused Graph Classification

Author:

Qiao Ye,Li Guang,Zhou Jieying,Wu Weigang

Publisher

Springer Nature Singapore

Reference31 articles.

1. Agarwal, R., Thapliyal, T., Shukla, S.K.: Vulnerability and transaction behavior based detection of malicious smart contracts. In: Meng, W., Conti, M. (eds.) Cyberspace Safety and Security. LNCS, vol. 13172, pp. 79–96. Springer, Cham (2022). https://doi.org/10.1007/978-3-030-94029-4_6

2. Agarwal, S., Atondo Siu, J., Ordekian, M., Hutchings, A., Mariconti, E., Vasek, M.: Defi deception–uncovering the prevalence of rugpulls in cryptocurrency projects (2023)

3. Bianchi, F.M., Grattarola, D., Alippi, C.: Mincut pooling in graph neural networks. arXiv preprint arXiv:1907.00481 (2019)

4. Buterin, V., et al.: A next-generation smart contract and decentralized application platform. White Paper 3(37), 2-1 (2014)

5. Cernera, F., Morgia, M.L., Mei, A., Sassi, F.: Token spammers, rug pulls, and sniper bots: an analysis of the ecosystem of tokens in ethereum and in the binance smart chain (BNB). In: 32nd USENIX Security Symposium (USENIX Security 23), pp. 3349–3366. USENIX Association (2023)

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