Mitigating Frontrunning Attacks in Ethereum

Mitigating Frontrunning Attacks in Ethereum

연구 분야: Infrastructure

학회: BSCI '22: Proceedings of the Fourth ACM International Symposium on Blockchain and Secure Critical Infrastructure

With the rising popularity of Ethereum, there is also an uptick in the number of smart contract based decentralized applications (DApps). Consequently, Ethereum transaction volume is growing steadily over the last few years, but so are the various types of attacks on it. In Ethereum vulnerable smart contracts are always taken advantage of by adversaries. One of the primary ways of exploiting Ethereum with malicious intent is through frontrunning attacks that take advantage of the waiting time of transactions in the pending pool by adjusting the gas price. Attackers willing to execute such attacks constantly monitor the pending transaction pool and try to frontrun transactions. Mitigating such attacks is a critical step for ensuring secure DApp operations in Ethereum. In this paper, we propose a model-based attack detection and prevention scheme. We extract specific features for each transaction and transform each transaction into a feature vector which is then analyzed by a machine learning model to detect if it is a frontrunning attack transaction or not in real time. Extensive experiments on a large dataset of transactions establish the effectiveness of our approach.