Detecting abnormal behaviors in smart contracts using opcode sequences

Abstract

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.