Ethereum marked the beginning of stateful and Turing-Complete blockchains, where the final result of transactions depends on their execution order. This subtle distinction is of great import, especially in Decentralized Finance (DeFi) applications like exchanges or lending platforms, where execution order plays a key role in making profits or losses and gives adversarial actors enormous incentives to manipulate or influence the ordering of transactions on blockchains. Maximal Extractable Value (MEV) represents the potential profit block producers can gain by manipulating transaction inclusion within a block they create. Other blockchain participants can also extract MEV, often through tactics such as front-running attacks. The MEV problem also affects Layer-2 (L2) networks, which are a subset of stateful chains created to improve scalability for Layer-1 (L1) chains like Ethereum. Prominent examples of L2 networks include rollups such as Arbitrum and Optimism. To mitigate the MEV problem, many rollups are characterized by a single sequencer that employs the First-Come-First-Served (FCFS) transaction ordering policy, which prevents greedy reordering based on the value extracted per transaction. While FCFS policy guarantees order fairness by processing transactions according to receive times, it has some drawbacks, such as encouraging spam transactions to ensure early inclusion in a block, and sequencer orderings favoring users with lower latency. To reduce the risks of the FCFS ordering algorithm, we propose a fair ordering mechanism by adding fairness granularity to the original FCFS policy. We then introduce a method to measure the granularity interval of the Arbitrum chain, using a statistical technique that can be adapted for use with other L2 chains. We evaluate our proposed ordering algorithm using a dataset based on Arbitrum network specifications and quantify the accuracy of our final ordering by measuring its proximity to the ideal ordering. Our results show a high accuracy with different network latencies and different datasets. We also assess the effectiveness of our approach for MEV mitigation by reducing front-running compared to FCFS.
The emergence of decentralized finance has transformed asset trading on the blockchain, making traditional financial instruments more accessible while also introducing a series of exploitative economic practices known as Maximal Extractable Value (MEV). Concurrently, decentralized finance has embraced rollup-based Layer-2 solutions to facilitate asset trading at reduced transaction costs compared to Layer-1 solutions such as Ethereum. However, rollups lack a public mempool like Ethereum, making the extraction of MEV more challenging. In this paper, we investigate the prevalence and impact of MEV on Ethereum and prominent rollups such as Arbitrum, Optimism, and zkSync over a nearly three-year period. Our analysis encompasses various metrics including volume, profits, costs, competition, and response time to MEV opportunities. We discover that MEV is widespread on rollups, with trading volume comparable to Ethereum. We also find that, although MEV costs are lower on rollups, profits are also significantly lower compared to Ethereum. Additionally, we examine the prevalence of sandwich attacks on rollups. While our findings did not detect any sandwiching activity on popular rollups, we did identify the potential for cross-layer sandwich attacks facilitated by transactions that are sent across rollups and Ethereum. Consequently, we propose and evaluate the feasibility of three novel attacks that exploit cross-layer transactions, revealing that attackers could have already earned approximately 2 million USD through cross-layer sandwich attacks.