Ethereum has been attracting lots of attacks, hence there is a pressing need to perform timely investigation and detect more attack instances. However, existing systems suffer from the scalability issue due to the following reasons. First, the tight coupling between malicious contract detection and blockchain data importing makes them infeasible to repeatedly detect different attacks. Second, the coarse-grained archive data makes them inefficient to replay transactions. Third, the separation between malicious contract detection and runtime state recovery consumes lots of storage. In this article, we propose a scalable attack detection framework named EthScope , which overcomes the scalability issue by neatly re-organizing the Ethereum state and efficiently locating suspicious transactions. It leverages the fine-grained state to support the replay of arbitrary transactions and proposes a well-designed schema to optimize the storage consumption. The performance evaluation shows that EthScope can solve the scalability issue, i.e., efficiently performing a large-scale analysis on billions of transactions, and a speedup of around \( \text{2,300}\times \) when replaying transactions. It also has lower storage consumption compared with existing systems. Further analysis shows that EthScope can help analysts understand attack behaviors and detect more attack instances.

Ethereum is an emerging distributed computing platform that supports a decentralized replicated virtual machine at a large scale. Transactions in Ethereum are specified in smart contracts, disseminated through broadcast, accepted into the chain of blocks, and then executed on each node. In this new Dissemination-Consensus-Execution (DiCE) paradigm, the time interval between when a transaction is known (during the dissemination phase) to when the transaction is executed (after the consensus phase) offers a window of opportunity to accelerate transaction processing through speculative execution. However, the traditional speculative execution, which hinges on the ability to predict the future accurately, is inadequate because of DiCE's many-future nature.