Transaction fee markets are essential components of blockchain economies, as they resolve the inherent scarcity in the number of transactions that can be added to each block. In early blockchain protocols, this scarcity was resolved through a first-price auction in which users were forced to guess appropriate bids from recent blockchain data. Ethereum's EIP-1559 fee market reform streamlines this process through the use of a base fee that is increased (or decreased) whenever a block exceeds (or fails to meet) a specified target block size. Previous work has found that the EIP-1559 mechanism may lead to a base fee process that is inherently chaotic, in which case the base fee does not converge to a fixed point even under ideal conditions. However, the impact of this chaotic behavior on the fee market's main design goal -- blocks whose long-term average size equals the target -- has not previously been explored. As our main contribution, we derive near-optimal upper and lower bounds for the time-average block size in the EIP-1559 mechanism despite its possibly chaotic evolution. Our lower bound is equal to the target utilization level whereas our upper bound is approximately 6% higher than optimal. Empirical evidence is shown in great agreement with these theoretical predictions. Specifically, the historical average was approximately 2.9% larger than the target rage under Proof-of-Work and decreased to approximately 2.0% after Ethereum's transition to Proof-of-Stake. We also find that an approximate version of EIP-1559 achieves optimality even in the absence of convergence.
Jiaqi Wang, Ning Lu, Ziyang Gong, Wenbo Shi · 5 authors
With the arrival of the 5G era, wireless communication technologies and services are rapidly exhausting the limited spectrum resources. Spectrum auctions came into being, which can effectively utilize spectrum resources. Because of the complexity of the electronic spectrum auction network environment, the security of spectrum auction can not be guaranteed. Most scholars focus on researching the security of the single-sided auctions, while ignoring the practical scenario of a secure double spectrum auction where participants are composed of multiple sellers and buyers. Researchers begin to design the secure double spectrum auction mechanisms, in which two semi-honest agents are introduced to finish the spectrum auction rules. But these two agents may collude with each other or be bribed by buyers and sellers, which may create security risks, therefore, a secure double spectrum auction is proposed in this paper. Unlike traditional secure double spectrum auctions, the spectrum auction server with Software Guard Extensions (SGX) component is used in this paper, which is an Ethereum blockchain platform that performs spectrum auctions. A secure double spectrum protocol is also designed, using SGX technology and cryptographic tools such as Paillier cryptosystem, stealth address technology and one-time ring signatures to well protect the private information of spectrum auctions. In addition, the smart contracts provided by the Ethereum blockchain platform are executed to assist offline verification, and to verify important spectrum auction information to ensure the fairness and impartiality of spectrum auctions. Finally, security analysis and performance evaluation of our protocol are discussed.
Alexis Asseman, Tomasz Kornuta, Patel, Anirudh, Matt Deible · 5 authors
The Graph Protocol indexes historical blockchain transaction data and makes it available for querying. As the protocol is decentralized, there are many independent Indexers that index and compete with each other for serving queries to the Consumers. One dimension along which Indexers compete is pricing. In this paper, we propose a bandit-based algorithm for maximization of Indexers' revenue via Consumer budget discovery. We present the design and the considerations we had to make for a dynamic pricing algorithm being used by multiple agents simultaneously. We discuss the results achieved by our dynamic pricing bandits both in simulation and deployed into production on one of the Indexers operating on Ethereum. We have open-sourced both the simulation framework and tools we created, which other Indexers have since started to adapt into their own workflows.
Online data trading has grown alongside the ever-increasing use of digital services. Industries are accruing the benefits of this data access to perform mission-critical tasks by analyzing available data for greater insight. Unsurprisingly, data trading has not focused on improved data seller protection with preferences and controls. The objective of this paper is to explore the enforcement of seller preferences within smart contracts using blockchain technology. Data trading is only possible when a buyer satisfies the conditions predefined by the seller. Geographic location, type or size of buyer's company are some examples of seller preferences. A preferences algorithm provides an automated contract between seller and buyer without the involvement of any broker or third party. Hybrid simulation (HS) methods are used to test and evaluate the viability of our novel data control approach.
Sen Yang, Fan Zhang, Ken Huang, Xi Chen · 6 authors
Blockchains offer strong security guarantees, but they cannot protect the ordering of transactions. Powerful players, such as miners, sequencers, and sophisticated bots, can reap significant profits by selectively including, excluding, or re-ordering user transactions. Such profits are called Miner/Maximal Extractable Value or MEV. MEV bears profound implications for blockchain security and decentralization. While numerous countermeasures have been proposed, there is no agreement on the best solution. Moreover, solutions developed in academic literature differ quite drastically from what is widely adopted by practitioners. For these reasons, this paper systematizes the knowledge of the theory and practice of MEV countermeasures. The contribution is twofold. First, we present a comprehensive taxonomy of 30 proposed MEV countermeasures, covering four different technical directions. Secondly, we empirically studied the most popular MEV-auction-based solution with rich blockchain and mempool data. We also present the Mempool Guru system, a public service system that collects, persists, and analyzes the Ethereum mempool data for research. In addition to gaining insights into MEV auction platforms' real-world operations, our study shed light on the prevalent censorship by MEV auction platforms as a result of the recent OFAC sanction, and its implication on blockchain properties.
Lu Han, Renchao Xie, Yuzheng Ren, F. Richard Yu · 5 authors
As a recently proposed network architecture, the computing power network (CPN) combines the ability of end, edge, cloud computing, and transmission network to realize the flexible and efficient scheduling and transaction of ubiquitous multi-resources, such as computing, cache, communications, and intelligent models. However, in CPN, multi-resources are deployed in a distributed manner. So, efficient, reliable and distributed resource transaction solutions are sought. Therefore, in this paper, we propose a non-fungible token (NFT)-based resource transaction scheme for CPN. We use NFT to tokenize and describe multi-resources by metadata to enable applications to network multi-resources efficiently and ensure transaction se-curity. Also, we formulate the trading utility of sellers and buyers and present a trusted trading process. To improve the system efficiency by increasing the matching success rate and simplify the complexity of combinatorial resources matching, we design the decision and pricing policy by distributed double auction mechanism. Simulation results demonstrate the effectiveness of the proposed scheme.
Decentralized autonomous organizations (DAOs) have become an indispensable part of digital infrastructure in recent years. The unique organizational characteristics and functional structure empower them to become an effective tool for solving corporate governance issues, including contract risks, principal-agent dilemmas, etc. However, DAOs themselves also face a variety of governance issues. On one hand, as a new economic organization model, the existing corporate governance theories and methods are no longer fully applicable to DAOs. On the other hand, unpredictable logic vulnerabilities and code loopholes in the governance mechanism might cause devastating damage to DAOs. The parallel intelligence theory based on the ACP method (i.e., artificial systems, computational experiments, and parallel execution) is an elegant research paradigm and a practical approach tailored to solving these challenges. As such, we propose a novel parallel governance framework for DAOs based on the parallel intelligence theory and further discuss its technical methodology and implementation model. Furthermore, we construct a parallel governance system for GnosisDAO and conduct computational experiments to validate the effectiveness of its governance mechanism. The experimental results not only confirm the defects of the GnosisDAO governance mechanism but also illustrate parallel governance as a useful research direction to solve existing governance problems of DAOs.
Mohak Goyal, Geoffrey Ramseyer, Ashish Goel, David Mazières
Constant Function Market Makers (CFMMs) are a tool for creating exchange markets, have been deployed effectively in prediction markets, and are now especially prominent in the Decentralized Finance ecosystem. We show that for any set of beliefs about future asset prices, an optimal CFMM trading function exists that maximizes the fraction of trades that a CFMM can settle. We formulate a convex program to compute this optimal trading function. This program, therefore, gives a tractable framework for market-makers to compile their belief function on the future prices of the underlying assets into the trading function of a maximally capital-efficient CFMM. Our convex optimization framework further extends to capture the tradeoffs between fee revenue, arbitrage loss, and opportunity costs of liquidity providers. Analyzing the program shows how the consideration of profit and loss leads to a qualitatively different optimal trading function. Our model additionally explains the diversity of CFMM designs that appear in practice. We show that careful analysis of our convex program enables inference of a market-maker's beliefs about future asset prices, and show that these beliefs mirror the folklore intuition for several widely used CFMMs. Developing the program requires a new notion of the liquidity of a CFMM, and the core technical challenge is in the analysis of the KKT conditions of an optimization over an infinite-dimensional Banach space.
Developers may not understand the Gas mechanism of Ethereum, so many smart contracts consume a lot of unnecessary Gas. To address this issue, existing studies have proposed several methods to optimize the code of the contracts to reduce Gas consumption. To verify the effectiveness, most of the methods deploy a private chain to make verification. However, a more reasonable way is to employ the real transactions on Ethereum to trigger the contracts before and after optimization, and then compare the Gas consumption. To achieve this goal, we proposed a method, GOV, to estimate the Gas consumption of the optimized contract by using the real transactions on Ethereum. Our method enables the optimized contract to follow the execution path of the contract before optimization, thus solving the problem of inconsistent execution paths before and after optimization. A preliminary evaluation shows that GOV can effectively estimate the Gas consumption of optimized contract.
Baowei Wang, Bin Li, Yi Yuan, Changyu Dai · 6 authors
Data has become an integral part of the modern world, and its value has led to the creation of new markets for data trading. Protecting the copyright of trading data and ensuring the fairness of transactions present significant challenges in the current trading market. Therefore, we propose a copyright-preserving data trading scheme based on smart contracts and perceptual hashing, called CPDT, which use smart contracts, combined with perceptual hashing, to prevent malicious acts of illegal reselling and to ensure fair transactions. We have also designed a perceptual hashing algorithm for our trading scheme. Extensive experiments have been conducted to demonstrate the feasibility of the scheme.
Blockchain Technology Applications and Security
Auction Theory and Applications
Advanced Steganography and Watermarking Techniques
Sandi Gec, Dejan Lavbič, Vlado Stankovski, Petar Kochovski
Distributed Ledger Technology (DLT), from the initial goal of moving digital assets, allows more advanced approaches as smart contracts executed on distributed computational enabling nodes such as Ethereum Virtual Machines (EVM) initially available only on the Ethereum ledger. Since the release of different EVM-based ledgers, the use cases to incentive the integration of smart contracts on other domains, such as IoT environments, increased. In this paper, we analyze the most IoT environment expedient quantitative metrics of various popular EVM-enabling ledgers to provide an overview of potential EVM-enabling characteristics.
Philippe Bergault, Louis Bertucci, David Bouba, Olivier Guéant
With the emergence of decentralized finance, new trading mechanisms called Automated Market Makers have appeared. The most popular Automated Market Makers are Constant Function Market Makers. They have been studied both theoretically and empirically. In particular, the concept of impermanent loss has emerged and explains part of the profit and loss of liquidity providers in Constant Function Market Makers. In this paper, we propose another mechanism in which price discovery does not solely rely on liquidity takers but also on an external exchange rate or price oracle. We also propose to compare the different mechanisms from the point of view of liquidity providers by using a mean / variance analysis of their profit and loss compared to that of agents holding assets outside of Automated Market Makers. In particular, inspired by Markowitz' modern portfolio theory, we manage to obtain an efficient frontier for the performance of liquidity providers in the idealized case of a perfect oracle. Beyond that idealized case, we show that even when the oracle is lagged and in the presence of adverse selection by liquidity takers and systematic arbitrageurs, optimized oracle-based mechanisms perform better than popular Constant Function Market Makers.
Contract management has always been a classic task for companies; the management of vendors to the remittance handling goes in a cycle, requiring constant monitoring and risk assessment. The vendor-related frauds account for a huge amount of money. It is expected that the fraud detection and prevention market is expected to reach 63.5 billion USD worldwide by 2023, with a CAGR of 26.6%. Hence, companies are looking for a unified solution that can track the phases in a traditional contract lifecycle so the escrow charges can be reduced and centralized monitoring is possible. This paper has presented how a traditional contract life cycle happens, a comparison between traditional contract and smart contract, how a smart contract functions, and its underlying technology. High-level documents like architecture diagrams should be designed in this phase. An architecture diagram depicts business logic in a pictorial format; it also helps developers to follow the correct path during the development. We have also presented the current business challenges in implementing smart contracts and the future scope and further applications.
Decentralized Autonomous Organization (DAO) is an organization constructed by automatically executed rules such as via smart contracts, holding features of the permissionless committee, transparent proposals, and fair contribution by stakeholders. As of Nov 2022, DAO has impacted over \$11.2B market caps. However, there are no substantial studies focused on this emerging field. To fill the gap, we start from the ground truth by empirically studying the breadth and depth of the DAO markets in mainstream public chain ecosystems in this paper. We dive into the most widely adoptable DAO launchpad, \textit{Snapshot}, which covers 95\% in the wild DAO projects for data collection and analysis. By integrating extensive enrolled DAOs and corresponding data measurements, we explore statistical data from Snapshot and try to demystify its undiscovered truths by delivering a series of summarised insights. We also present DAO status, patterns, distribution, and trends. To our knowledge, this is the first empirical study putting concentration on DAO spaces.
Automated Market Makers (AMMs) have cemented themselves as an integral part of the decentralized finance (DeFi) space. AMMs are a type of exchange that allows users to trade assets without the need for a centralized exchange. They form the foundation for numerous decentralized exchanges (DEXs), which help facilitate the quick and efficient exchange of on-chain tokens. All present-day popular DEXs are static protocols, with fixed parameters controlling the fee and the curvature - they suffer from invariance and cannot adapt to quickly changing market conditions. This characteristic may cause traders to stay away during high slippage conditions brought about by intractable market movements. We propose a Reinforcement Learning (RL) framework to optimize the fees collected on an AMM protocol. In particular, we develop a Q-Learning Agent for Market Making Protocols (QLAMMP) that learns the optimal fee rates and leverage coefficients for a given AMM protocol and maximizes the expected fee collected under a range of different market conditions. We show that QLAMMP is consistently able to outperform its static counterparts under all the simulated test conditions.
In this paper, we investigate some economic fundamentals related to the Tezos blockchain platform under the Emmy* consensus protocol. The protocol is based on a liquid version of Proof-of-Stake, in the sense that users can temporarily delegate some or all of their Tz units to full nodes. In addition to increasing the stake of the full node, and thus the probability of being selected as a block baker/endorser, such delegation induces the property of the super-additivity of users’ selection probability of baking/endorsing a block. That is, with delegation, the selection probability may be larger than the sum of the selection probabilities without delegation. In this paper, we study how monetary holdings and stakes can evolve with time, also discussing the individual user and the market implications of delegation.
Haoxian Chen, Lan Lu, Brendan Massey, Yuepeng Wang · 5 authors
Smart contracts manage a large number of digital assets nowadays. Bugs in these contracts have led to significant financial loss. Verifying the correctness of smart contracts is, therefore, an important task. This paper presents an automated safety verification tool, DCV, that targets declarative smart contracts written in DeCon, a logic-based domain-specific language for smart contract implementation and specification. DCV proves safety properties by mathematical induction and can automatically infer inductive invariants using heuristic patterns, without annotations from the developer. Our evaluation on 20 benchmark contracts shows that DCV is effective in verifying smart contracts adapted from public repositories, and can verify contracts not supported by other tools. Furthermore, DCV significantly outperforms baseline tools in verification time.
Blockchain is a new distributed ledger system that enables for safe online transactions without need for a trusted third party. As blockchain technology continues to advance at a dizzying pace, the question of smart contracts and how they should evolve has risen to the forefront of academic and business discussions. With this paper, we want to shed light on how smart contracts built on the blockchain really function. To better grasp the whole picture, researchers are taking into account scholarly works that have been vetted for their quality and are presenting a comprehensive overview of the relevant literature. Future work on decentralized apps might benefit from this. The first part provides a high-level introduction of smart contracts, covering topics such as their rationale, structure, and use cases. In addition, a thorough analysis of other smart contract development platforms reveals that the blockchain used in research is the most effective platform for improving QoS. In other words, it is developing low-cost smart contracts for distributed applications. Further, we give simulation work that uses the Blockchain transaction as a data set to educate an AI model that can help forecast whether or not the transaction will be successful. Finally, this paper also emphasizes key difficulties and future research implications in the decentralized uses of Blockchain smart contracts.
Răzvan Mihai, Omer Faruk Ozkul, Gora Datta, Nicolae Goga · 6 authors
Economic transactions are based upon implicit or explicit contracts that set out the rights and obligations of the parties to the transactions. Blockchain technology can address fundamental financial, economic, and accounting challenges. We propose a blockchain-based prototype capable of capturing the essence of recurring economic transactions. For this purpose, we have devised an asset rental contract to show how economic transactions are recorded and tracked more effectively, efficiently, and in quasi-real-time, thus changing the traditional way of account keeping and auditing. We use the Ethereum blockchain as the most evolved and widely used smart contract platform. We showcase a significant discovery related to current blockchain technology limitations to making automatic non-custodial recurring payments. We show how the prototype can be extended to a range of recurring transactions.
Abstract Information asymmetry caused by centralized databases is the main factor hindering the improved performance of river chief governance, and blockchain can solve this dilemma. In view of the mismatch between traceable feature of blockchain and the heavy punishment mechanism, a model of river governance was constructed based on principal–agent theory, and an incentive mechanism of river chiefs in the context of blockchain was designed. The results we conducted will enable the real river management information to be stored permanently in the distributed ledger. These measures are conducive to long‐term river management and improve the overall environmental and social benefits.
Siwei Cui, Gang Zhao, Yifei Gao, Tien Tavu · 5 authors
Solana is a rapidly-growing high-performance blockchain powered by a Proof of History (PoH) consensus mechanism and a novel stateless programming model that decouples code from data. With parallel execution on the PoH Sealevel runtime (instead of PoW), it achieves 100X-1000X speedups compared to Ethereum in terms of transactions per second. With the new programming model, new constraints (owner, signer, keys, bump seeds) and vulnerabilities (missing checks, overflows, type confusion, etc.) must be carefully verified to ensure the security of Solana smart contracts.
We study the competition between blockchains in a multi-chain environment, where a dominant EVM-compatible blockchain (e.g., Ethereum) co-exists with an alternative EVM-compatible (e.g., Avalanche) and an EVM-incompatible (e.g., Algorand) blockchain. While EVM compatibility allows existing Ethereum users and developers to migrate more easily over to the alternative layer-1, EVM incompatibility might allow the firms to build more loyal and "sticky'' user base, and in turn a more robust ecosystem. As such, the choice to be EVM-compatible is not merely a technological decision, but also an important strategic decision. In this paper, we develop a game theoretic model to study this competitive dynamic, and find that at equilibrium, new entrants/developers tend to adopt the dominant blockchain. To avoid adoption failure, the alternative blockchains have to either (1) directly subsidize the new entrant firms or (2) offer better features, which in practice can take form in lower transaction costs, faster finality, or larger network effects. We find that it is easier for EVM-compatible blockchains to attract users through direct subsidy, while it is more efficient for EVM-incompatible blockchains to attract users through offering better features/products.
En Wang, Jiatong Cai, Yongjian Yang, Wenbin Liu · 7 authors
With the development of communications, networking, and information technology, Crowdsensed Data Trading (CDT) becomes a novel data trading paradigm. In CDT, the data requesters publish crowdsensing tasks with specific data requirements, and then workers complete these tasks, upload the data and obtain corresponding rewards. To efficiently deal with data trading, most of the existing CDT systems assume a trusted centralized platform. However, we argue that the platform may collude with workers or requesters to trick others for achieving more benefits. For example, according to the workers’ uploaded data, the platform can modify the reward functions by colluding with the requester. Similarly, the platform might collude with workers to let them know the reward function, then workers could forge data. Meanwhile, requesters and workers may also be malicious. For example, requesters may post tasks but fail to pay and workers can upload wrong data to mislead the system. To solve the above problems, we combine the Crowdsensed Data Trading system with intelligent Blockchain (CDT-B), which contains a smart contract called CDToken. As a credible third-party, the CDToken is used to record the requesters’ reward function and workers’ data uploading function to avoid targeted trick. At the same time, we not only design a Data Uploading and Preprocessing (DUP) mechanism in CDToken to collect and process the workers’ sensed data, but also propose a Grouping Truth Discovery (GTD) to evaluate their data quality for determining the payments. Moreover, to hold a large number of requesters and workers in CDT-B, we propose a Layered Sharding blockchain based on Membership Degree (LSMD) to solve the blockchain inefficiency problem. Finally, we deploy CDToken to an experimental environment based on Ethereum and demonstrate its efficient performance and practicability.