Research Pulse #53 02/21/22

  1. Cryptocurrency Privacy in Practice
    Author: Malte Möser

Cryptocurrencies like Bitcoin balance privacy and transparency goals. In these systems, all transactions are public by design, allowing nodes in a decentralized network to validate them. However, this reveals many potentially privacy-sensitive transaction details of users, whose privacy is only protected by varying degrees of pseudonymity. Understanding the privacy cryptocurrencies provide in practice is hence important for users transacting in them as well as law enforcement or regulatory agencies concerned about their illicit use.


  1. Cyclic Arbitrage in Decentralized Exchanges
    Authors: Ye Wang, Yan Chen, Haotian Wu, Liyi Zhou, Shuiguang Deng, and Roger Wattenhofer

Decentralized Exchanges (DEXes) enable users to create markets for exchanging any pair of cryptocurrencies. The direct exchange rate of two tokens may not match the crossexchange rate in the market, and such price discrepancies open up arbitrage possibilities with trading through different cryptocurrencies cyclically. In this paper, we conduct a systematic investigation on cyclic arbitrages in DEXes. We propose a theoretical framework for studying cyclic arbitrage. With our framework, we analyze the profitability conditions and optimal trading strategies of cyclic transactions. We further examine exploitable arbitrage opportunities and the market size of cyclic arbitrages with transaction-level data of Uniswap V2. We find that traders have executed 292,606 cyclic arbitrages over eleven months and exploited more than 138 million USD in revenue. However, the revenue of the most profitable unexploited opportunity is persistently higher than 1 ETH (4,000 USD), which indicates that DEX markets may not be efficient enough. By analyzing how traders implement cyclic arbitrages, we find that traders can utilize smart contracts to issue atomic transactions and the atomic implementations could mitigate users’ financial loss in cyclic arbitrage from the price impact.


  1. Pathway: a protocol for algorithmic pricing of a DAO governance token
    Authors: GC DAO, Aleksei Pupyshev, Ilya Sapranidi, and Shamil Khalilov

In this paper, we will consider a governance token pricing algorithm that conducts liquidity operations on AMM CPMM DEXs with liquidity that belongs to a decentralized autonomous organization (DAO), also called protocol-owned liquidity (POL). The primary aim of the protocol is maintaining a price peg by determining algorithmically when and how to carry out interventions that consist of two steps: extracting liquidity from an AMM liquidity pool and conducting “token swap” operations. We will cover setting up an optimal peg function as a weighted sum of certain normalized factors, which are to be determined collectively by the DAO. In particular, we will review various arithmetic invariants of liquidity intervention, which brings the price to a peg while leaving total liquidity intact.
In addition, we will demonstrate how a systematic application of Pathway protocol by DAOs can create a class of so-called algorithmic governance tokens (AGT). In the end, we will consider ways of technical implementation of Pathway using Solidity, as well as potential practical problems that may occur when implementing such a protocol on EVM (Ethereum virtual machine) blockchains.


  1. FairTraDEX: A Decentralised Exchange Preventing Value Extraction
    Authors: Conor McMenamin, Vanesa Daza, and Matthias Fitzi

An idealised decentralised exchange (DEX) provides a medium in which players wishing to exchange one token for another can interact with other such players and liquidity providers at a price which reflects the true exchange rate, without the need for a trusted third-party. Unfortunately, extractable value is an inherent flaw in existing blockchain-based DEX implementations. This extractable value takes the form of monetizable opportunities that allow blockchain participants to extract money from a DEX without adding demand or liquidity to the DEX, the two functions for which DEXs are intended. This money is taken directly from the intended DEX participants. As a result, the cost of participation in existing DEXs is much larger than the upfront fees required to post a transaction on a blockchain and/or into a smart contract.
We present FairTraDEX, a decentralised variant of a frequent batch auction (FBA), a DEX protocol which provides formal game-theoretic guarantees against extractable value. FBAs when run by a trusted third-party provide unique game-theoretic optimal strategies which ensure players are shown prices equal to the liquidity provider’s fair price, excluding explicit, pre-determined fees. FairTraDEX replicates the key features of an FBA that provide these game-theoretic guarantees using a combination of setmembership in zero-knowledge protocols and an escrow-enforced commit-reveal protocol. We extend the results of FBAs to handle monopolistic and/or malicious liquidity providers, and provide a detailed pseudo-code implementation of FairTraDEX based on existing mainstream blockchain protocols.


  1. Investigation and Application of Differential Privacy in Bitcoin
    Authors: Merve C. Kus and Albert Levi

Bitcoin is one of the best-known cryptocurrencies, which captivated researchers with its innovative blockchain structure. Examinations of this public blockchain resulted in many proposals for improvement in terms of anonymity and privacy. Generally used methods for improvement include mixing protocols, ring signatures, zero-knowledge proofs, homomorphic commitments, and off-chain storage systems. To the best of our knowledge, in the literature, there is no study examining Bitcoin in terms of differential privacy, which is a privacy notion coming up with some mechanisms that enable running useful statistical queries without identifying any personal information. In this paper, we provide a theoretical examination of differential privacy in Bitcoin. Our motivation arises from the idea that the Bitcoin public blockchain structure can benefit from differential privacy mechanisms for improved privacy, both making anonymization and privacy breaches by direct queries impossible, and preserving the checkability of the integrity of the blockchain. We first examine the current Bitcoin implementation for four query functions using the differential privacy formulation. Then, we present the feasibility of the utilization of two differential privacy mechanisms in Bitcoin; the noise addition to the transaction amounts and the user graph perturbation. We show that these mechanisms decrease the fraction of the cases violating differential privacy, therefore they can be used for improving anonymity and privacy in Bitcoin. Moreover, we showcase the noise addition to transaction amounts by using IBM Differential Privacy Library. We compare four differential privacy mechanisms for varying privacy parameter values and determine the feasible mechanisms and the parameters.

Link: IEEE Xplore Full-Text PDF: