With the fast growth of blockchain technology, blockchain as a decentralized distributed ledger technology has become more widely used and is gradually changing our way of life. But it also raises more and more security issues. As there are more and more smart contracts on the blockchain, and smart contracts cannot be changed once they are added to the blockchain, there is an opportunity for hackers to attack smart contracts. If not handled properly, it will cause serious economic losses to users. In this paper, we introduce a unique method for identifying abnormal behaviors of smart contract vulnerabilities using opcode sequences. We aim to identify the control flow paths triggered by transactions to capture the abnormal behaviors of smart contracts. The control flow paths are the traces on which the transaction is executed. Using Geth instrumentation, we collect the opcode sequences executed on the traces to represent the control flow paths. It should be noted that the process of detecting abnormal behaviors introduces some additional time overhead. However, our experimental results show that this method achieves high abnormal detection accuracy with minimal overhead. This suggests that our proposed method is effective in identifying potential security issues in smart contracts without significantly impacting the overall execution time.

中文翻译：

---

使用操作码序列检测智能合约中的异常行为

随着区块链技术的快速发展，区块链作为一种去中心化的分布式账本技术得到了越来越广泛的应用，正在逐渐改变我们的生活方式。但它也引发了越来越多的安全问题。由于区块链上的智能合约越来越多，而且智能合约一旦加入区块链就无法更改，这就给黑客攻击智能合约提供了机会。如果处理不当，将会给用户造成严重的经济损失。在本文中，我们介绍了一种使用操作码序列识别智能合约漏洞异常行为的独特方法。我们的目标是识别交易触发的控制流路径，以捕获智能合约的异常行为。控制流路径是执行事务的轨迹。使用 Geth 检测，我们收集在迹线上执行的操作码序列来表示控制流路径。应该注意的是，检测异常行为的过程会引入一些额外的时间开销。然而，我们的实验结果表明，该方法以最小的开销实现了较高的异常检测精度。这表明我们提出的方法可以有效识别智能合约中的潜在安全问题，而不会显着影响整体执行时间。