Blockchain Amplification Attack

Strategies related to the blockchain concept of Extractable Value (MEV/BEV), such as arbitrage, front-, or back-running create strong economic incentives for network nodes to reduce latency. Modified nodes, that minimize transaction validation time and neglect to filter invalid transactions in the Ethereum peer-to-peer (P2P) network, introduce a novel attack vector--a Blockchain Amplification Attack. An attacker can exploit those modified nodes to amplify invalid transactions thousands of times, posing a security threat to the entire network. To illustrate attack feasibility and practicality in the current Ethereum network (''mainnet''), we 1) identify thousands of similar attacks in the wild, 2) mathematically model the propagation mechanism, 3) empirically measure model parameters from our monitoring nodes, and 4) compare the performance with other existing Denial-of-Service attacks through local simulation. We show that an attacker can amplify network traffic at modified nodes by a factor of 3,600, and cause economic damages of approximately 13,800 times the amount needed to carry out the attack. Despite these risks, aggressive latency reduction may still be profitable enough for various providers to justify the existence of modified nodes. To assess this trade-off, we 1) simulate the transaction validation process in a local network and 2) empirically measure the latency reduction by deploying our modified node in the Ethereum test network (''testnet''). We conclude with a cost-benefit analysis of skipping validation and provide mitigation strategies against the blockchain amplification attack.

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Publication Details

Journal
Proceedings of the ACM on Measurement and Analysis of Computing Systems
Published
2025-03-06
DOI
https://doi.org/10.1145/3711697
Primary Topic
Blockchain Technology Applications and Security
Type
article
Field-Weighted Citation Impact
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article

Blockchain Amplification Attack

Liyi Zhou, Kaihua Qin, Arthur Gervais, Taro Tsuchiya et al.
Proceedings of the ACM on Measurement and Analysis of Computing Systems
Blockchain Technology Applications and Security
article

Blockchain Amplification Attack

Liyi Zhou, Kaihua Qin, Arthur Gervais, Taro Tsuchiya, Nicolas Christin
article en

Abstract

Strategies related to the blockchain concept of Extractable Value (MEV/BEV), such as arbitrage, front-, or back-running create strong economic incentives for network nodes to reduce latency. Modified nodes, that minimize transaction validation time and neglect to filter invalid transactions in the Ethereum peer-to-peer (P2P) network, introduce a novel attack vector--a Blockchain Amplification Attack. An attacker can exploit those modified nodes to amplify invalid transactions thousands of times, posing a security threat to the entire network. To illustrate attack feasibility and practicality in the current Ethereum network (''mainnet''), we 1) identify thousands of similar attacks in the wild, 2) mathematically model the propagation mechanism, 3) empirically measure model parameters from our monitoring nodes, and 4) compare the performance with other existing Denial-of-Service attacks through local simulation. We show that an attacker can amplify network traffic at modified nodes by a factor of 3,600, and cause economic damages of approximately 13,800 times the amount needed to carry out the attack. Despite these risks, aggressive latency reduction may still be profitable enough for various providers to justify the existence of modified nodes. To assess this trade-off, we 1) simulate the transaction validation process in a local network and 2) empirically measure the latency reduction by deploying our modified node in the Ethereum test network (''testnet''). We conclude with a cost-benefit analysis of skipping validation and provide mitigation strategies against the blockchain amplification attack.

Proceedings of the ACM on Measurement and Analysis of Computing SystemsVol. 9(1)
The University of Sydney (AU), Intel (United States) (US), Yale University (US), Intel (United Kingdom) (GB), University College London (GB), Carnegie Mellon University (US)
Openalex Percentile: Top 95%
Blockchain Technology Applications and Security
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