Mempool Privacy via Batched Threshold Encryption: Attacks and Defenses

Authors: 

Arka Rai Choudhuri, NTT Research; Sanjam Garg, Julien Piet, and Guru-Vamsi Policharla, University of California, Berkeley

Abstract: 

With the rising popularity of DeFi applications it is important to implement protections for regular users of these DeFi platforms against large parties with massive amounts of resources allowing them to engage in market manipulation strategies such as frontrunning/backrunning. Moreover, there are many situations (such as recovery of funds from vulnerable smart contracts) where a user may not want to reveal their transaction until it has been executed. As such, it is clear that preserving the privacy of transactions in the mempool is an important goal.

In this work we focus on achieving mempool transaction privacy through a new primitive that we term batched-threshold encryption, which is a variant of threshold encryption with strict efficiency requirements to better model the needs of resource constrained environments such as blockchains. Unlike the naive use of threshold encryption, which requires communication proportional to O(nB) to decrypt B transactions with a committee of n parties, our batched-threshold encryption scheme only needs O(n) communication. We additionally discuss pitfalls in prior approaches that use (vanilla) threshold encryption for mempool privacy.

To show that our scheme is concretely efficient, we implement our scheme and find that transactions can be encrypted in under 6 ms, independent of committee size, and the communication required to decrypt an entire batch of B transactions is 80 bytes per party, independent of the number of transactions B, making it an attractive choice when communication is very expensive. If deployed on Ethereum, which processes close to 500 transaction per block, it takes close to 2.8 s for each committee member to compute a partial decryption and under 3.5 s to decrypt all transactions for a block in single-threaded mode.

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BibTeX
@inproceedings {299647,
author = {Arka Rai Choudhuri and Sanjam Garg and Julien Piet and Guru-Vamsi Policharla},
title = {Mempool Privacy via Batched Threshold Encryption: Attacks and Defenses},
booktitle = {33rd USENIX Security Symposium (USENIX Security 24)},
year = {2024},
isbn = {978-1-939133-44-1},
address = {Philadelphia, PA},
pages = {3513--3529},
url = {https://www.usenix.org/conference/usenixsecurity24/presentation/choudhuri},
publisher = {USENIX Association},
month = aug
}

Presentation Video