Research Pulse #71 06/27/22

  1. Is my transaction done yet? An empirical study of transaction processing times in the Ethereum Blockchain Platform
    Authors: Michael Pacheco, Gustavo A. Oliva, Gopi Krishnan Rajbahadur, and Ahmed E. Hassan

Ethereum is one of the most popular platforms for the development of blockchain-powered applications. These applications are known as ÐApps. When engineering ÐApps, developers need to translate requests captured in the front-end of their application into one or more smart contract transactions. Developers need to pay for these transactions and, the more they pay (i.e., the higher the gas price), the faster the transaction is likely to be processed. Developing cost-effective ÐApps is far from trivial, as developers need to optimize the balance between cost (transaction fees) and user experience (transaction processing times). Online services have been developed to provide transaction issuers (e.g., ÐApp developers) with an estimate of how long transactions will take to be processed given a certain gas price. These estimation services are crucial in the Ethereum domain and several popular wallets such as Metamask rely on them. However, despite their key role, their accuracy has not been empirically investigated so far. In this paper, we quantify the transaction processing times in Ethereum, investigate the relationship between processing times and gas prices, and determine the accuracy of state-of-the-practice estimation services. Our results indicate that transactions are processed in a median of 57s and that 90% of the transactions are processed within 8m. We also show that higher gas prices result in faster transaction processing times with diminishing returns. In particular, we observe no practical difference in processing time between expensive and very expensive transactions. With regards to the accuracy of processing time estimation services, we observe that they are equivalent. However, when stratifying transactions by gas prices, we observe that Etherscan’s Gas Tracker is the most accurate estimation service for very cheap and cheap transaction. EthGasStation’s Gas Price API, in turn, is the most accurate estimation service for regular, expensive, and very expensive transactions. In a post-hoc study, we design a simple linear regression model with only one feature that outperforms the Gas Tracker for very cheap and cheap transactions and that performs as accurately as the EthGasStation model for the remaining categories. Based on our findings, ÐApp developers can make more informed decisions concerning the choice of the gas price of their application-issued transactions.


  1. Flash Freezing Flash Boys: Countering Blockchain Front-Running
    Authors: Haoqian Zhang, Louis-Henri Merino, Vero Estrada-Galinanes, and Bryan Ford

Front-running, the practice of benefiting from advanced knowledge of pending transactions, has proliferated in the cryptocurrency space with the emergence of decentralized finance. Front-running causes devastating losses to honest participants—estimated at $280M each month—and endangers the fairness of the ecosystem. We present Flash Freezing Flash Boys (F3B), an architecture to address front-running attacks by relying on a commit-and-reveal scheme where the contents of a transaction are encrypted and later revealed by a decentralized secret-management committee (SMC) when the transaction has been committed by the underlying consensus layer. To maintain legacy compatibility, we design F3B to be agnostic to the underlying consensus algorithm and compatible with existing smart contracts. A preliminary exploration of F3B shows that with a secret-management committee consisting of 8 and 128 members, F3B presents between 0.1 and 2.2 second transaction-processing latency, respectively.


  1. Rank the spreading influence of nodes using dynamic Markov process
    Authors: Jian-Hong Lin, Zhao Yang, Jian-Guo Liu, Bo-Lun Chen, and Claudio J. Tessone

Ranking the spreading influence of nodes is of great importance in practice and research. The key to ranking a node’s spreading ability is to evaluate the fraction of susceptible nodes been infected by the target node during the outbreak, i.e., the outbreak size. In this paper, we present a dynamic Markov process (DMP) method by integrating the Markov chain and the spreading process to evaluate the outbreak size of the initial spreader. Following the idea of the Markov process, this method solves the problem of nonlinear coupling by adjusting the state transition matrix and evaluating the probability of the susceptible node being infected by its infected neighbours. We have employed the susceptible-infected-recovered (SIR) and susceptible-infected-susceptible (SIS) models to test this method on real-world static and temporal networks. Our results indicate that the DMP method could evaluate the nodes’ outbreak sizes more accurately than previous methods for both single and multi-spreaders. Besides, it can also be employed to rank the influence of nodes accurately during the spreading process.


  1. Fair Voting System for Permissionless Decentralized Autonomous Organizations
    Author: Erik Hellström

The increasingly adapted technology called blockchain can be viewed as a distributed appendonly time-stamped data structure which is made possible by a distributed peer-to-peer network. The network uses cryptography and different consensus mechanisms to ensure immutability, security, transparency, and speed in a decentralized fashion. A permissionless decentralized autonomous organization (DAO) is an application deployed on a blockchain that enables people to govern and coordinate themselves in a decentralized manner through self-executing rules where anyone can join. A foundational function of a DAO is the voting system which dictates how the governance of the DAO is conducted. Voting systems in DAOs are currently not well researched and the currently used solutions have flaws, they are either not secure or they have the risk of resulting in unfair outcomes. This is the problem that this project focuses on. The problem was approached by conducting research in the field and through the conclusions of the research a new solution for a voting system was proposed and implemented. The proposed solution can be used to gain inspiration in further studies or be tested and developed to evaluate it in practice.


  1. Quadratic Voting in Blockchain Governance
    Author: Nicola Dimitri

Governance in blockchain platforms is an increasingly important topic. A particular concern related to voting procedures is the formation of dominant positions, which may discourage participation of minorities. A main feature of standard majority voting is that individuals can indicate their preferences but cannot express the intensity of their preferences. This could sometimes be a drawback for minorities who may not have the opportunity to obtain their most desirable outcomes, even when such outcomes are particularly important for them. For this reason a voting method, which in recent years gained visibility, is quadratic voting (QV), which allows voters to manifest both their preferences and the associated intensity. In voting rounds, where in each round users express their preference over binary alternatives, what characterizes QV is that the sum of the squares of the votes allocated by individuals to each round has to be equal to the total number, budget, of available votes. That is, the cost associated with a number of votes is given by the square of that number, hence it increases quadratically. In the paper, we discuss QV in proof-of-stake-based blockchain platforms, where a user’s monetary stake also represents the budget of votes available in a voting session. Considering the stake as given, the work focuses mostly on a game theoretic approach to determine the optimal allocation of votes across the rounds. We also investigate the possibility of the so-called Sybil attacks and discuss how simultaneous versus sequential staking can affect the voting outcomes with QV.

Link: Information | Free Full-Text | Quadratic Voting in Blockchain Governance | HTML

  1. Evolutionary Random Graph for Bitcoin Overlay and Blockchain Mining Networks
    Authors: Jacques Bou Abdo, Shuvalaxmi Dass, Basheer Qolomany, and Liaquat Hossain

The world economy is experiencing the novel adoption of distributed currencies that are free from the control of central banks.Distributed currencies suffer from extreme volatility, and this can lead to catastrophic implications during future economic crisis.Understanding the dynamics of this new type of currencies is vital for empowering supervisory bodies from current reactive and manual incident responders to more proactive and well-informed planners. Bitcoin, the first and dominant distributed cryptocurrency, is still notoriously vague, especially for a financial instrument with market value exceeding $1trillion. Modeling of bitcoin overlay network poses a number of important theoretical and methodological challenges. Current measuring approaches, for example, fail to identify the real network size of bitcoin miners. This drastically undermines the ability to predict forks, the suitable mining difficulty and most importantly the resilience of the network supporting bitcoin. In this work, we developed Evolutionary Random Graph, a theoretical model that describes the network of bitcoin miners. The correctness of this model has been validated using simulated and measure bitcoin data. We then predicted forking, optimal mining difficulty, network size and consequently the network’s inability to stand a drastic drop in bitcoin price using the current mining configuration.


  1. SoK: Assumptions Underlying Cryptocurrency Deanonymizations
    Authors: Dominic Deuber, Viktoria Ronge, and Christian Rückert

In recent years, cryptocurrencies have increasingly been used in cybercrime and have become the key means of payment in darknet marketplaces, partly due to their alleged anonymity. Furthermore, the research attacking the anonymity of even those cryptocurrencies that claim to offer anonymity by design is growing and is being applied by law enforcement agencies in the fight against cybercrime. Their investigative measures require a certain degree of suspicion and it is unclear whether findings resulting from attacks on cryptocurrencies’ anonymity can indeed establish that required degree of suspicion. The reason for this is that these attacks are partly based upon uncertain assumptions which are often not properly addressed in the corresponding papers. To close this gap, we extract the assumptions in papers that are attacking Bitcoin, Monero and Zcash, major cryptocurrencies used in darknet markets which have also received the most attention from researchers. We develop a taxonomy to capture the different nature of those assumptions in order to help investigators to better assess whether the required degree of suspicion for specific investigative measures could be established. We found that assumptions based on user behaviour are in general the most unreliable and thus any findings of attacks based on them might not allow for intense investigative measures such as pre-trial detention. We hope to raise awareness of the problem so that in the future there will be fewer unlawful investigations based upon uncertain assumptions and thus fewer human rights violations.


  1. Are decentralized finance really decentralized? A social network analysis of the Aave protocol on the Ethereum blockchain
    Authors: Ziqiao Ao, Gergely Horvath, and Luyao Zhang

Decentralized finance (DeFi) has the potential to disrupt centralized finance by validating peer-to-peer transactions through tamper-proof smart contracts and thus significantly lower the transaction cost charged by financial intermediaries. However, the actual realization of peer-to-peer transactions and the levels and effect of decentralization are largely unknown. Our research pioneers a blockchain network study that applies social network analysis to measure the level, dynamics, and impacts of decentralization in DeFi token transactions on Ethereum blockchain. First, we find a significant core-periphery structure in the AAVE token transaction network where the cores include the two largest centralized crypto exchanges. Second, we provide evidence that multiple network features consistently characterize decentralization dynamics. Finally, we document that a more decentralized network significantly predicts a higher return and lower volatilities of the DeFi tokens. We point out that our approach is seminal for inspiring future extensions related to the facets of application scenarios, research questions, and methodologies on the mechanics of blockchain decentralization.


  1. SuperDetector: A Framework for Performance Detection on Vulnerabilities of Smart Contracts
    Authors: Meiyi Dai, Zhe Yang, and Jian Guo

The technology of Ethereum blockchain enables the implementation of smart contracts. Nowadays smart contracts are one of the most successful applications of blockchain technology, which are widely used in many fields, such as finance, energy and services. The decentralization and immutability properties of Ethereum blockchain provide security for transactions from smart contracts. However, these properties are possible to lead to unfixable vulnerabilities of smart contracts. In recent years, vulnerability detection on smart contracts has attracted more attention from researchers and many related tools have emerged. Nevertheless, the existing vulnerability detection tools have not yet been put into formal use. Due to the lack of suitable smart contract sets and fair metrics with other factors, it remains complex work to conduct authoritative performance tests on these tools. In this paper, we first summarize eight common vulnerabilities of smart contracts, and then divide them into call-related and call-irrelated vulnerabilities according to whether they involve caller functions or not. In addition, we propose a detection framework called SuperDetector, which combines a variety of vulnerability detection tools based on static analysis technology. And the framework mainly measures the detection performance, which contains vulnerability coverage, detection accuracy, usability and execution time on the two types of vulnerabilities. The results indicate that the framework can analyze the performance from different perspectives, and the performance of vulnerability coverage and detection accuracy on call-related vulnerabilities is much better than that on call-irrelated vulnerabilities. Finally, we design a selector based on the detection results in the framework for improving the vulnerability coverage and detection accuracy.


  1. An Empirical Investigation on the Trade-off between Smart Contract Readability and Gas Consumption
    Authors: Anna Vacca, Michele Fredella, Andrea Di Sorbo, Corrado A. Visaggio, and Gerardo Canfora

Blockchain technology is becoming increasingly popular, and smart contracts (i.e., programs that run on top of the blockchain) represent a crucial element of this technology. In particular, smart contracts running on Ethereum (i.e., one of the most popular blockchain platforms) are often developed with Solidity, and their deployment and execution consume gas (i.e., a fee compensating the computing resources required). Smart contract development frequently involves code reuse, but poor readable smart contracts could hinder their reuse. However, writing readable smart contracts is challenging, since practices for improving the readability could also be in contrast with optimization strategies for reducing gas consumption. This paper aims at better understanding (i) the readability aspects for which traditional software and smart contracts differ, and (ii) the specific smart contract readability features exhibiting significant relationships with gas consumption. We leverage a set of metrics that previous research has proven correlated with code readability. In particular, we first compare the values of these metrics obtained for both Solidity smart contracts and traditional software systems (written in Java). Then, we investigate the correlations occurring between these metrics and gas consumption and between each pair of metrics. The results of our study highlight that smart contracts usually exhibit lower readability than traditional software for what concerns the number of parentheses, inline comments, and blank lines used. In addition, we found some readability metrics (such as the average length of identifiers and the average number of keywords) that significantly correlate with gas consumption.

Link: An Empirical Investigation on the Trade-off between Smart Contract Readability and Gas Consumption | IEEE Conference Publication | IEEE Xplore

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