The primary innovation we pioneer -- focused on blockchain information security -- is called the Safe-House. The Safe-House is badly needed since there are many ongoing hacks and security concerns in the DeFi space right now. The Safe-House is a piece of engineering sophistication that utilizes existing blockchain principles to bring about greater security when customer assets are moved around. The Safe-House logic is easily implemented as smart contracts on any decentralized system. The amount of funds at risk from both internal and external parties -- and hence the maximum one time loss -- is guaranteed to stay within the specified limits based on cryptographic fundamentals. To improve the safety of the Safe-House even further, we adapt the one time password (OPT) concept to operate using blockchain technology. Well suited to blockchain cryptographic nuances, our secondary advancement can be termed the one time next time password (OTNTP) mechanism. The OTNTP is designed to complement the Safe-House making it even more safe. We provide a detailed threat assessment model -- discussing the risks faced by DeFi protocols and the specific risks that apply to blockchain fund management -- and give technical arguments regarding how these threats can be overcome in a robust manner. We discuss how the Safe-House can participate with other external yield generation protocols in a secure way. We provide reasons for why the Safe-House increases safety without sacrificing the efficiency of operation. We start with a high level intuitive description of the landscape, the corresponding problems and our solutions. We then supplement this overview with detailed discussions including the corresponding mathematical formulations and pointers for technological implementation. This approach ensures that the article is accessible to a broad audience.
Smart contracts are programs that are executed on the blockchain and can hold, manage and transfer assets in the form of cryptocurrencies. The contract's execution is then performed on-chain and is subject to consensus, i.e. every node on the blockchain network has to run the function calls and keep track of their side-effects. In most programmable blockchains, such as Ethereum, the notion of gas is introduced to prevent DoS attacks by malicious parties who might try to slow down the network by performing heavy computations. A fixed cost to each atomic operation, and the initiator of a function call pays the total gas cost as a transaction fee. This helps prevent DoS attacks, but the resulting fees are extremely high. For example, in 2022, on Ethereum alone, there has been a total gas usage of 1.77 Million ETH ~ 4.3 Billion USD. This thesis proposes "lazy contracts" as a solution to alleviate these costs. Our solution moves most of the computation off-chain, ensuring that each function call incurs only a tiny amount of gas usage, while preserving enough data on-chain to guarantee an implicit consensus about the state of the contract variables and ownership of funds. A complete on-chain execution of the functions will only be triggered in case two parties to the contract are in disagreement about the current state, which in turn can only happen if at least one party is dishonest. In such cases, our protocol can identify the dishonest party and penalize them by having them pay for the entire gas usage. Hence, no rational party has an incentive to act dishonestly. Finally, we perform extensive experiments over 160,735 real-world Solidity contracts that were involved in 9,055,492 transactions in January 2022--January 2023 on Ethereum and show that our approach reduces the overall gas usage by 55.4%, which amounts to an astounding saving of 109.9 Million USD in gas fees.
Liquidity providers (LPs) on decentralized exchanges (DEXs) can protect themselves from adverse selection risk by updating their positions more frequently. However, repositioning is costly, because LPs have to pay gas fees for each update. We analyze the causal relation between repositioning and liquidity concentration around the market price, using the entry of blockchain scaling solutions, Arbitrum and Polygon, as our instruments. Lower gas fees on scaling solutions allow LPs to update more frequently than on Ethereum. Our results demonstrate that higher repositioning intensity and precision lead to greater liquidity concentration, which benefits small trades by reducing their slippage.
Blockchains revolutionized centralized sectors like banking and finance by promoting decentralization and transparency. In a blockchain, information is transmitted through transactions issued by participants or applications. Miners crucially select, order, and validate pending transactions for block inclusion, prioritizing those with higher incentives or fees. The order in which transactions are included can impact the blockchain final state. Moreover, applications running on top of a blockchain often rely on governance protocols to decentralize the decision-making power to make changes to their core functionality. These changes can affect how participants interact with these applications. Since one token equals one vote, participants holding multiple tokens have a higher voting power to support or reject the proposed changes. The extent to which this voting power is distributed is questionable and if highly concentrated among a few holders can lead to governance attacks. In this thesis, we audit the Bitcoin and Ethereum blockchains to investigate the norms followed by miners in determining the transaction prioritization. We also audit decentralized governance protocols such as Compound to evaluate whether the voting power is fairly distributed among the participants. Our findings have significant implications for future developments of blockchains and decentralized applications.
This paper presents a novel reference architecture for blockchain-enabled federated learning (BCFL), a state-of-the-art approach that amalgamates the strengths of federated learning and blockchain technology. We define smart contract functions, stakeholders and their roles, and the use of interplanetary file system (IPFS) as key components of BCFL and conduct a comprehensive analysis. In traditional centralized federated learning, the selection of local nodes and the collection of learning results for each round are merged under the control of a central server. In contrast, in BCFL, all these processes are monitored and managed via smart contracts. Additionally, we propose an extension architecture to support both cross-device and cross-silo federated learning scenarios. Furthermore, we implement and verify the architecture in a practical real-world Ethereum development environment. Our BCFL reference architecture provides significant flexibility and extensibility, accommodating the integration of various additional elements, as per specific requirements and use cases, thereby rendering it an adaptable solution for a wide range of BCFL applications. As a prominent example of extensibility, decentralized identifiers (DIDs) have been employed as an authentication method to introduce practical utilization within BCFL. This study not only bridges a crucial gap between research and practical deployment but also lays a solid foundation for future explorations in the realm of BCFL. The pivotal contribution of this study is the successful implementation and verification of a realistic BCFL reference architecture. We intend to make the source code publicly accessible shortly, fostering further advancements and adaptations within the community.
The current Proposer-Builder Separation (PBS) equilibrium has several builders with different backgrounds winning blocks consistently. This paper considers how that equilibrium will shift when transactions are sold privately via order flow auctions (OFAs) rather than forwarded directly to the public mempool. We discuss a novel model that highlights the augmented value of private order flow for integrated builder searchers. We show that private order flow is complementary to top-of-block opportunities, and therefore integrated builder-searchers are more likely to participate in OFAs and outbid non integrated builders. They will then parlay access to these private transactions into an advantage in the PBS auction, winning blocks more often and extracting higher profits than non-integrated builders. To validate our main assumptions, we construct a novel dataset pairing post-merge PBS outcomes with realized 12-second volatility on a leading CEX (Binance). Our results show that integrated builder-searchers are more likely to win in the PBS auction when realized volatility is high, suggesting that indeed such builders have an advantage in extracting top-of-block opportunities. Our findings suggest that modifying PBS to disentangle the intertwined dynamics between top-of-block extraction and private order flow would pave the way for a fairer and more decentralized Ethereum.
Jan 1, 2023·2nd International Workshop on Decentralized Governance Design at the 35th International Conference on Advanced Information Systems Engineering 2023
In this article, we develop an interdisciplinary analysis of MEV which desires to merge the gap that exists between technical and legal research supporting policymakers in their regulatory decisions concerning blockchains, DeFi and associated risks. Consequently, this article is intended for both technical and legal audiences, and while we abstain from a detailed legal analysis, we aim to open a policy discussion regarding decentralized governance design at the block building layer as the place where MEV occurs. Maximal Extractable Value or MEV has been one of the major concerns in blockchain designs as it creates a centralizing force which ultimately affects user transactions. In this article, we dive into the technicality behind MEV, where we explain the concept behind the novel Proposal Builder Separation design as an effort by Flashbots to increase decentralization through modularity. We underline potential vulnerability factors under the PBS design, which open space for MEV extracting adversarial strategies by inside participants. We discuss the shift of trust from validators to builders in PoS blockchains such as Ethereum, acknowledging the impact that the later ones may have on users' transactions (in terms of front running) and censorship resistance (in terms of transaction inclusion). We recognize that under PBS, centralized (dominant) entities such as builders could potentially harm users by extracting MEV via front running strategies. Finally, we suggest adequate design and policy measures which could potentially mitigate these negative effects while protecting blockchain users.
Informally, a distributed system is grassroots if it is permissionless and can have autonomous, independently-deployed instances - geographically and over time - that may interoperate voluntarily once interconnected. More formally, in a grassroots system the set of all correct behaviors of a set of agents P is strictly included in the set of the correct behaviors of P when they are embedded within a larger set of agents P' ⊃ P. Grassroots systems are potentially important as they may allow communities to conduct their social, economic, civic, and political lives in the digital realm solely using their members' networked computing devices (e.g., smartphones), free of third-party control, surveillance, manipulation, coercion, or rent seeking (e.g., by global digital platforms such as Facebook or Bitcoin). Client-server/cloud computing systems are not grassroots, and neither are systems designed to have a single global instance (Bitcoin/Ethereum with hardwired seed miners/bootnodes), and systems that rely on a single global data structure (IPFS, DHTs). An example grassroots system would be a serverless smartphone-based social network supporting multiple independently-budding communities that can merge when a member of one community becomes also a member of another. Here, we formalize the notion of grassroots distributed systems; describe a grassroots dissemination protocol for the model of asynchrony and argue its safety, liveness, and being grassroots; extend the implementation to mobile (address-changing) devices that communicate via an unreliable network (e.g. smartphones using UDP); and discuss how grassroots dissemination can realize grassroots social networking and grassroots cryptocurrencies. The mathematical construction employs distributed multiagent transition systems to define the notions of grassroots protocols, to specify the grassroots dissemination protocols, and to prove their correctness. The protocols use the blocklace - a distributed, partially-ordered counterpart of the replicated, totally-ordered blockchain.
This paper studies the effects of unexpected changes in US monetary policy on digital asset returns. We use event study regressions and find that monetary policy surprises negatively affect BTC and ETH, the two largest digital assets, but do not significantly affect the rest of the market. Second, we use high-frequency price data to examine the effect of the FOMC statements release and Minutes release on the prices of the assets with the higher collateral usage on the Ethereum Blockchain Decentralized Finance (DeFi) ecosystem. The FOMC statement release strongly affects the volatility of digital asset returns, while the effect of the Minutes release is weaker. The volatility effect strengthened after December 2021, when the Federal Reserve changed its policy to fight inflation. We also show that some borrowing interest rates in the Ethereum DeFi ecosystem are affected positively by unexpected changes in monetary policy. In contrast, the debt outstanding and the total value locked are negatively affected. Finally, we utilize a local Ethereum Blockchain node to record the activity history of primary DeFi functions, such as depositing, borrowing, and liquidating, and study how these are influenced by the FOMC announcements over time.
Blockchain has shown great potential in various fields due to its technical advantages such as peer-to-peer, timestamp, consensus algorithm and encryption. In blockchain, the protection method of transaction data or copyright is crucial and cryptographic digital signature technology has been applied as one of the copyright protection methods. The multi-signature scheme provides higher security than single-signature schemes, enhances the transparency of transactions and contracts, and is widely used in distributed systems utilizing distributed ledger technology in blockchain. Multisignature requires multiple parties to cooperate in order to produce a valid signature, reducing the risk of exposing the entire system to a single point of failure when compared to single-signature schemes. This is an important role in transactions or contracts that require consensus among multiple parties, where each party can sign to implement the agreement, increasing transparency and preventing disputes. However, the cryptographic digital signature is resource consuming and inefficient because the verification of the signature consumes lots of computational resources and excessive number of communications. Therefore, we have proposed an efficient multi-signature scheme based on Schnorr for copyright protection on Ethereum.
This study provides an in-depth analysis of cryptocurrency research, examining the trends, geographical distribution, and future research directions within this rapidly evolving field. Using a comprehensive dataset, we consider whether such research varies by journal ranking. Our findings reveal a significant increase in the number of publications on cryptocurrencies and blockchain technology from pre-2019 to 2022, with a growing interest in diverse digital assets and related concepts. When considering cryptocurrency-based research, we identify prominent keywords such as “Security,” “Return,” “Investor,” “Risk,” “Volatility,” “COVID,” and “Ethereum,” highlighting the ongoing concerns and interests of researchers in this field. The geographical distribution of author affiliations reveals the prominent role of China and the United States in contributing to cryptocurrency research, with European countries and emerging economies experiencing substantial growth in their number of publications. Based on these findings, we propose several future research directions, including exploring the role of cryptocurrencies in financial inclusion, addressing cybersecurity and privacy concerns, examining the regulatory landscape, and investigating the environmental impact of digital assets. Our study underscores the importance of a multidisciplinary approach to cryptocurrency research, considering the broad societal impacts and implications of this rapidly developing field.
Cryptocurrency is a popular digital currency due to its security and peer-to-peer transferability. Predicting cryptocurrency prices is crucial for investors and traders to make informed decisions on buying, selling, or holding cryptocurrencies based on their expected value, potential risks, and returns. This study aims to identify the optimal model for predicting the prices of cryptocurrencies, such as Bitcoin (BTC) and Ethereum (ETH), using Deephaven for Data curation. The study involves extracting data from both cryptocurrencies by Deephaven and selecting the most correlating parameters through time lag adjustment. We use correlating cryptocurrency data to train models, such as Artificial Neural Networks (ANN), Long-Short Term Memories (LSTM), and Gated Recurrent Units (GRU). Where the trial-and-error technique was applied for selecting optimized hyper-parameters for each model. The models are then evaluated by statistical evaluators, such as Mean Absolute Error (MAE), Root Mean Square Error (RMSE), and Mean Absolute Percentage Error (MAPE), separately for training and testing datasets. For Bitcoin, the results showed that the LSTM model outperform ANN and GRU models in both training and testing data with MAE, RMSE, and MAPE average values of 0.079, 1.16, and 0.0006, respectively. While for Ethereum, the results also revealed that LSTM model performance is superior with MAE, RMSE, and MAPE average values of 0.0025, 0.124 and 0.0002, respectively. While GRU (MAE 0.012, RMSE 0.117, MAPE 0.002) performs robustly against ANN (MAE 0.035, RMSE 0.149, MAPE 0.003) model.
Advancements in digital technologies have made the storage, sharing, and verification of educational credentials extremely important for entities such as students, universities, institutions, and companies. Digital credentials play an important role in students’ lives as a lifelong learning passport. The educational field is experiencing numerous issues such as academic record forgery, record misuse, credential data tampering, time-consuming verification procedures, and issues related to ownership and control. Modern-day technology, Blockchain, is an appropriate alternative to resolve these issues and increase trust among entities. In this research, we intend to propose a Blockchain-based educational digital credential issuance, and verification model that addresses these issues in the education system using Ethereum Blockchain and smart contracts. The method we propose offers a way to demonstrate the correctness of specific credential attributes without revealing other attributes, thereby leading to ownership, minimal disclosure, and control. We offer an interface for storing massively encrypted academic records in a decentralized file system like Interplanetary File System (IPFS). Furthermore, Ethereum provides tamper-resistant chains to maintain the integrity of digital credentials. Finally, in comparison with the time it requires to issue credentials, our model safely accelerates the verification process by about 8%.
The advent of smart contract technology in blockchain networks has ushered in a new era of possibilities for implementing complex decentralized finance protocols. Over time, these protocols have gained significant traction, reaching a Total Value Locked (TVL) of over 150 billion US dollars. While blockchain networks offer inherent benefits such as immutability, transparency, decentralization, and security, they still grapple with a critical challenge – the inability to ensure a predictable order of transactions within produced blocks. This limitation has given rise to the Maximal Extractable Value (MEV) phenomenon. MEV represents the maximum potential benefit that certain network participants, primarily miners and validators, can extract by wielding their exclusive capability to influence transaction order. In this work, we embark on an exhaustive exploration of the MEV phenomenon and delve deep into its impact on the broader blockchain ecosystem. We shed light on the pressing issue of transaction ordering in blockchain networks and provide an in-depth survey of the vast body of scholarly publications focused on MEV extraction. This comprehensive review allowed us to conduct a retrospective analysis of the MEV phenomenon, categorize its most common manifestations, and uncover current development trends. Intriguingly, during this analysis, parallels were drawn with similar manipulations witnessed in the realm of high-frequency algorithmic trading within traditional financial markets. A vital conclusion that emerged from our study pertains to possible strategies for addressing the MEV problem within decentralized finance protocols. We systematically outline the current research directions concerning MEV, explore the methodologies and tools employed in these studies, and present concrete examples of MEV extraction within the Ethereum network, accompanied by quantitative estimations. In summary, the MEV phenomenon has cast an overwhelming negative impact on blockchain networks and decentralized finance. Our analysis of existing publications within a specific subcategory reveals the current absence of an effective solution to the MEV extraction problem. This underscores the importance of further research aimed at mitigating the adverse effects of MEV on blockchain networks and decentralized finance protocols.
Spanish Abstract: La presente aportación examina la tecnología blockchain y sus retos legales desde sus principales plataformas en atención a sus usuarios: Blockchain y Ethereum. Por ello, examina la adhesión en los contratos B2C mediante la plataforma Blockchain, y el papel de los consumidores 2.0 en esta plataforma. Asimismo, analiza la plataforma Ethereum, más especializada, y que permite personalizar un smart contract y sus prestaciones. Seguidamente, trata la responsabilidad civil por los errores de programación en la blockchainización de las prestaciones, y finaliza mediante un análisis de la protección de datos y la encriptación de datos de carácter personal desde una perspectiva jurídica. English Abstract: This contribution examines blockchain technology and its legal challenges from its main platforms for its users: Blockchain and Ethereum. It therefore examines adhesion in B2C contracts through the Blockchain platform, and the role of consumers 2.0 on this platform. It also analyses the more specialised Ethereum platform, which allows the customisation of a smart contract and its services. It then deals with civil liability for programming errors in the blockchainisation of services, and ends with an analysis of data protection and the encryption of personal data from a legal perspective.
Open access
2 source records
Blockchain Technology Applications and Security
Neuroethics, Human Enhancement, Biomedical Innovations
Delays in finance impose real costs, yet they are difficult to measure in traditional settings. Leveraging Ethereum's on-chain data and fee market, I estimate a structural queuing model that maps fee bids to time preferences and quantify delay costs in decentralized finance. The median transaction bears a 7.1 bps implicit cost, with costs highly skewed and totaling $9.88 million per day. Counterfactuals show that a flexible block gas limit as in EIP-1559 cuts the loss from delay by 32.9%, and doubling block frequency with half-size blocks cuts it by 13.6%. Combined, the two policies reduce losses by a striking 63.9%.
Credit is one of the cornerstones of modern society, and credit governance is an important means of maintaining economic and social stability. However, credit governance has always faced challenges due to problems such as information asymmetry, fraudulent behavior, and lack of trust. The emergence of blockchain technology has brought new hopes and opportunities to enhance the level of credit governance. It creates conditions for establishing a more transparent and trustworthy credit system through decentralized credit records, immutable credit history, the application of smart contracts, privacy and authorization management, and cross-border collaboration. For example, in the financial field, smart contracts can also enable automated financial contracts and transactions. Based on the Ethereum blockchain's smart contract platform, this paper aims to propose a reward and punishment mechanism that can be used for participant management in a credit scoring system. This mechanism rewards or punishes participants' behavior based on their scores through the "coin-day destruction" mechanism, incentivizing positive behavior and penalizing misconduct. This paper believes that blockchain technology has significant potential for application in credit governance. However, the application of blockchain technology also faces challenges in terms of technology, law, and regulation, requiring joint efforts from all parties to truly enhance the level of credit governance.
We employ a novel framework to measure the asymmetric nexus between the cryptocurrency market and the carbon futures market based on different market conditions. Specifically, we use a quantile-on-quantile regression (QQR) approach to explore the correlation between cryptocurrencies (Bitcoin, Ethereum, and Ripple) and European Union Allowance (EUA) futures. We find that there is an asymmetric relationship between markets that is affected by different cryptocurrencies and market conditions. Overall, Bitcoin or Ethereum are positively correlated with the carbon market, while the results of Ripple are more complex. Under certain conditions, EUA futures can be a better hedge against cryptocurrency risk.
Triet M. N, Khanh H. V, Huong H. L, Khiem H. G · 13 authors
Medical waste is deemed hazardous due to its potential health implications and the predominant practice of discarding it post six months of utilization. Furthermore, the reusable proportion of such waste is minimal. The implications of this scenario were brought to the fore during the COVID- 19 pandemic when sub-optimal medical waste management was identified as a factor exacerbating the spread of the virus worldwide. The predicament is particularly grave in developing nations, such as Vietnam, where the underdeveloped state of medical infrastructure renders efficient waste management a daunting task. The waste management challenge also stems from the significant roles played by different stakeholders (healthcare workers and patients confined to isolation wards), whose actions directly influence waste classification, impact the waste treatment process, and indirectly contribute to environmental pollution. Given that waste management involves a chain of activities requiring the coordinated efforts of medical, transportation, and waste treatment personnel, inaccuracies in the initial stages, such as waste sorting, can negatively impact subsequent processes. In light of these issues, our study puts forth a unique model aimed at enhancing waste classification and management practices in Vietnam. This model innovatively integrates Blockchain technology, smart contracts, and non-fungible tokens (NFTs) with the intent to foster an increased individual and collective consciousness towards effective waste classification within healthcare settings. Our research is notable for its four-fold contribution: (a) suggesting a unique mechanism based on blockchain technology and smart contracts, designed specifically to improve medical waste classification and treatment in Vietnam; (b) introducing a model for instituting rewards or penalties based on NFT technology to influence behaviors of individuals and organizations; (c) demon-strating the feasibility of the proposed model through a proof-of-concept; (d) executing the proof-of-concept on four prominent platforms that support ERC721 - NFT of Ethereum and EVM for executing smart contracts programmed in the Solidity language, namely BNB Smart Chain, Fantom, Polygon, and Celo.