- The paper meticulously investigates and formalizes sandwich attacks, a sophisticated form of front-running, on Automated Market Maker (AMM) based Decentralized Exchanges (DEXs) by exploiting transaction transparency and latency.
- Empirical analysis using real-world data demonstrates that a single attacker can achieve substantial daily profits, while multiple adversaries competing significantly diminish individual profitability due to increased transaction costs and strategic counter-bidding.
- The findings highlight the intrinsic susceptibility of current DEX designs to economic exploits and suggest the need for reconsidering AMM parameters and exploring enhanced cryptographic mechanisms to mitigate such attacks.
High-Frequency Trading on Decentralized On-Chain Exchanges: An Analysis of Sandwich Attacks
The paper "High-Frequency Trading on Decentralized On-Chain Exchanges" meticulously investigates the potential for market manipulation within blockchain-based Decentralized Exchanges (DEXs), considering the unique transparency and latency characteristics inherent to these systems. Authors Liyi Zhou, Kaihua Qin, Christof Ferreira Torres, Duc V Le, and Arthur Gervais explore the vulnerabilities these factors introduce, particularly focusing on a sophisticated form of front-running known as sandwich attacks.
Decentralized exchanges have been celebrated for allowing users to trade assets without relinquishing control to centralized entities. However, the very feature that contributes to their resilience against censorship—public visibility of all transactions—can also facilitate adversarial trading tactics, primarily when compounded by the time delay for transaction confirmations. Highlighting this dual-edged nature, the authors dissect how sandwich attacks can substantially exploit these conditions for profit.
The sandwich attack, as delineated in the paper, involves two strategic moves by an adversary: front-running and back-running a target transaction. In practice, an attacker observes an impending trade and quickly submits two transactions—one just before and another immediately after the victim’s transaction. This disrupts the expected price movements to the attacker’s advantage. Such exploitation is particularly tractable in Automated Market Maker (AMM) DEXs like Uniswap, which implement deterministic pricing algorithms. The authors provide an in-depth formalization, analyzing both the theoretical underpinnings and real-world viability of this tactic across single and multi-adversary scenarios. Empirical results demonstrate that a single adversary can profit significantly, estimating daily revenues exceeding several thousand USD under optimal conditions. The results are based on actual market data and transactions extracted from Uniswap.
Remarkably, the paper extends to consider a more complex landscape where multiple adversaries could compete in such attacks, revealing that the presence of additional attackers can substantially diminish individual profitability due to increased transaction fees and strategic counter-bidding. The authors simulate diverse adversarial game settings, furnishing insights into how relative position gaming within blockchain blocks, and the ensuing gas price competition, affect attack outcomes.
The implications of this research are manifold. Practically, it urges developers and stakeholders within decentralized finance (DeFi) ecosystems to juxtapose decentralization's security promise against intrinsic susceptibility to economic exploits. The authors advocate for reconsidering AMM design parameters and suggest enhanced cryptographic mechanisms or protocol adjustments (e.g., commit-and-reveal schemes) that could mitigate such attacks without reverting to fully centralized controls or sacrificing decentralization ethos.
Moreover, the theoretical contribution here lies in quantifying attack vectors that heretofore were only speculated within the emerging DeFi domain. This analytical foundation enriches ongoing discourse on blockchain’s security and trust models, providing a basis for future exploration into resilient on-chain financial systems. Further research could explore adaptive mechanisms or alternative cryptographic primitives that safeguard trader assets while maintaining the desirable traits of DEX systems.
Overall, the paper’s findings underscore the intricate balance between transaction transparency and trader security in decentralized networks, expanding our understanding of potential economic attacks in DeFi and laying the groundwork for more robust decentralized trading infrastructures.