With the popularity of cryptocurrencies and the remarkable development of blockchain technology, decentralized applications emerged as a revolutionary force for the Internet. Meanwhile, decentralized applications have also attracted intense attention from the online gambling community, with more and more decentralized gambling platforms created through the help of smart contracts. Compared with conventional gambling platforms, decentralized gambling have transparent rules and a low participation threshold, attracting a substantial number of gamblers. In order to discover gambling behaviors and identify the contracts and addresses involved in gambling, we propose a tool termed ETHGamDet. The tool is able to automatically detect the smart contracts and addresses involved in gambling by scrutinizing the smart contract code and address transaction records. Interestingly, we present a novel LightGBM model with memory components, which possesses the ability to learn from its own misclassifications. As a side contribution, we construct and release a large-scale gambling dataset at https://github.com/AwesomeHuang/Bitcoin-Gambling-Dataset to facilitate future research in this field. Empirically, ETHGamDet achieves a F1-score of 0.72 and 0.89 in address classification and contract classification respectively, and offers novel and interesting insights.
翻译:随着隐秘的普及和黑链技术的显著发展,分散应用成为互联网革命力量;与此同时,分散应用也引起了在线赌博界的高度关注,通过智能合同建立了越来越多的分散赌博平台;与传统的赌博平台相比,分散赌博有透明的规则,参与门槛较低,吸引大量赌徒;为了发现赌博行为,确定赌博所涉合同和地址,我们提议了一个名为ETHGamDet的工具。该工具能够通过仔细检查智能合同代码和处理交易记录,自动发现涉及赌博的智能合同和地址;有趣的是,我们展示了一个带有记忆部分的新颖的 LightGBMM 模型,该模型具备了从自身分类错误中学习的能力。作为附带贡献,我们在https://github.com/Aweome-Huang/Bitcoin-Gambling-Dataset 上建立和发布一个大型赌博数据集,以便利该领域的未来研究。Ensimic、ETGamDet分别实现F1-9和0.8和0.7系列的令人感兴趣的解释和估价。