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Clack is Joint Field Chief Editor for the research journal Frontiers in Blockchain. Recent publications from Frontiers in Blockchain are given below:


  • DAO voting mechanism resistant to whale and collusion problems

    DAO voting mechanism resistant to whale and collusion problems

    With the widespread adoption of blockchain technology, a novel organizational structure known as Decentralized Autonomous Organizations (DAOs) has attracted considerable attention. DAOs facilitate decision-making through member voting, realizing the governance in a decentralized manner. However, DAOs face unique challenges compared to traditional organization. This paper focuses on two key challenges of governance within DAOs: the whale problem and collusion issue. The whale problem is characterized by the concentration of power among specific members, while for the collusion problem, voting results are distorted by fraudulent collaboration. In terms of voting, we consider Quadratic Voting, a voting system expected to deter the concentration of voting power among a subset of participants, analyzing its resistance to the collusion problem. We show with numerical examples that in comparison to Linear Voting, Quadratic Voting lacks resistance to collusion. Then, we propose a voting mechanism that integrates Quadratic Voting with the Vote escrow tokens, demonstrating the mitigation of the whale problem while acquiring resilience to collusion in the decision-making process. The numerical examples confirm the high efficacy of our proposed model.

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  • A comparative analysis of Silverkite and inter-dependent deep learning models for bitcoin price prediction

    A comparative analysis of Silverkite and inter-dependent deep learning models for bitcoin price prediction

    These days, there is a lot of demand for cryptocurrencies, and investors are essentially investing in them. The fact that there are already over 6,000 cryptocurrencies in use worldwide because of this, investors with regular incomes put money into promising cryptocurrencies that have low market values. Accurate pricing forecasting is necessary to build profitable trading strategies because of the unique characteristics and volatility of cryptocurrencies. For consistent forecasting accuracy in an unknown price range, a variation point detection technique is employed. Due to its bidirectional nature, a Bi-LSTM appropriate for recording long-term dependencies in data that is sequential. Accurate forecasting in the cryptocurrency space depends on identifying these connections, since values are subject to change over time due to a variety of causes. In this work, we employ four deep learning-based models that are LSTM, FB-Prophet, LSTM-GRU and Bidirectional-LSTM(Bi-LSTM) and these four models are compared with Silverkite. Silverkite is the main algorithm of the Python library Graykite by LinkedIn. Using historical bitcoin data from 2012 to 2021, we utilized to analyse the models’ mean absolute error (MAE) and root mean square error (RMSE). The Bi-LSTM model performs better than others, with a mean absolute error (MAE) of 0.633 and a root mean square error (RMSE) of 0.815. The conclusion has significant ramifications for bitcoin investors and industry experts.

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  • Integrated cybersecurity for metaverse systems operating with artificial intelligence, blockchains, and cloud computing

    Integrated cybersecurity for metaverse systems operating with artificial intelligence, blockchains, and cloud computing

    In the ever-evolving realm of cybersecurity, the increasing integration of Metaverse systems with cutting-edge technologies such as Artificial Intelligence (AI), Blockchain, and Cloud Computing presents a host of new opportunities alongside significant challenges. This article employs a methodological approach that combines an extensive literature review with focused case study analyses to examine the changing cybersecurity landscape within these intersecting domains. The emphasis is particularly on the Metaverse, exploring its current state of cybersecurity, potential future developments, and the influential roles of AI, blockchain, and cloud technologies. Our thorough investigation assesses a range of cybersecurity standards and frameworks to determine their effectiveness in managing the risks associated with these emerging technologies. Special focus is directed towards the rapidly evolving digital economy of the Metaverse, investigating how AI and blockchain can enhance its cybersecurity infrastructure whilst acknowledging the complexities introduced by cloud computing. The results highlight significant gaps in existing standards and a clear necessity for regulatory advancements, particularly concerning blockchain’s capability for self-governance and the early-stage development of the Metaverse. The article underscores the need for proactive regulatory involvement, stressing the importance of cybersecurity experts and policymakers adapting and preparing for the swift advancement of these technologies. Ultimately, this study offers a comprehensive overview of the current scenario, foresees future challenges, and suggests strategic directions for integrated cybersecurity within Metaverse systems utilising AI, blockchain, and cloud computing.

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  • Blockchain in the courtroom: exploring its evidentiary significance and procedural implications in U.S. judicial processes

    Blockchain in the courtroom: exploring its evidentiary significance and procedural implications in U.S. judicial processes

    This paper explores the evidentiary significance of blockchain records and the procedural implications of integrating this technology into the U.S. judicial system, as several states have undertaken legislative measures to facilitate the admissibility of blockchain evidence. We employ a comprehensive methodological approach, including legislative analysis, comparative case law analysis, technical examination of blockchain mechanics, and stakeholder engagement. Our study suggests that blockchain evidence may be categorized as hearsay exceptions or non-hearsay, depending on the specific characteristics of the records. The paper proposes a specialized consensus mechanism for standardizing blockchain evidence authentication and outlines strategies to enhance the technology’s trustworthiness. It also highlights the importance of expert testimony in clarifying blockchain’s technical aspects for legal contexts. This study contributes to understanding blockchain’s integration into judicial systems, emphasizing the need for a comprehensive approach to its admissibility and reliability as evidence. It bridges the gap between technology and law, offering a blueprint for standardizing legal approaches to blockchain and urging ethical and transparent technology use.

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  • Private law framework for blockchain

    Private law framework for blockchain

    Current attempts to regulate blockchain technology are mainly based on securities law framework, which considers crypto tokens and digital assets as either securities, currencies or derivatives thereof. The main limitation of such approach lies in its inability to accommodate the diverse legal rights, obligations and assets that blockchain technology can virtually reproduce. Already in 2017–2018 there were attempts to tokenize rights outside of securities law framework, these initiatives served more as makeshift solutions to circumvent securities regulations than as thorough frameworks for managing real-world assets and commercial activities. This article conducts a comparative and historical analysis of blockchain regulatory initiatives in Europe and the US, positing that the regulation of blockchain technology through a securities law lens is driven by reactionary opportunism. Such a basis is deemed inappropriate and insufficient, as securities laws being a field of public law were not designed to govern real-world assets and commerce, which fundamentally rely on the principles of laissez-faire and freedom of contract inherent in private law. A regulatory stance focused solely on public law overlooks the full potential of blockchain technology, and risks stifling innovation and practical applications. To illustrate this, the article presents case study of tokenization of contractual rights demonstrating that securities law-focused legal regulations, such as the EU Regulation 2023/1114 on Markets in Crypto-Assets (MiCA) and Regulation 2022/858 on Distributed Ledger Technology (DLT), inadequately address the field of private commerce. Based on the analysis, the article concludes that comprehensive legal framework for blockchain technology shall combine public and private law regime akin to the regulation of traditional rights, obligations and assets.

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  • Universal basic income on blockchain: the case of circles UBI

    Universal basic income on blockchain: the case of circles UBI

    The paper reviews Circles UBI as an illustrative case study of implementing the idea of universal basic income (UBI) on blockchain. Circles was born out of the Gnosis Chain as a more democratic alternative to Bitcoin coupled with the ambitious political project of algorithmically distributing UBI. Backed by the Gnosis Chain, Circles Coop was founded in 2020 to implement this idea in Berlin. Examining the failure of the Berlin pilot helps us draw substantial conclusions with regard to the implementation of UBI on blockchain. UBI alone, on blockchain or not, is not enough to solve the problems its proponents argue against. UBI would be helpful as a tool if plugged into a model of production embedded into a political strategy aiming to fix key problems of current societies such as gaping inequalities and climate change. We give a snapshot here of the model of open cooperativism as a counter-hegemonic political project vis-à-vis neoliberalism. Circles UBI could plug into the model of open cooperativism as a distribution and liquidity injection mechanism to foster the transition towards a commons-based ethical and sustainable post-capitalist economy.

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  • Challenges of user data privacy in self-sovereign identity verifiable credentials for autonomous building access during the COVID-19 pandemic

    Challenges of user data privacy in self-sovereign identity verifiable credentials for autonomous building access during the COVID-19 pandemic

    Self-sovereign identity is an emerging blockchain technology field. Its use cases primarily surround identity and credential management and advocate the privacy of user details during the verification process. Our endeavor was to test and implement the features promoted for self-sovereign identity through open- and closed-source frameworks utilizing a scenario of building access management to adhere to health risk and safety questionnaires during the COVID-19 pandemic. Our investigation identifies whether user data privacy could be ensured through verifiable credentials and whether business practices would need to evolve to mitigate storing personal data centrally.

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  • Enhancing blockchain scalability with snake optimization algorithm: a novel approach

    Enhancing blockchain scalability with snake optimization algorithm: a novel approach

    Scalability remains a critical challenge for blockchain technology, limiting its potential for widespread adoption in high-demand transactional systems. This paper proposes an innovative solution to this challenge by applying the Snake Optimization Algorithm (SOA) to a blockchain framework, aimed at enhancing transaction throughput and reducing latency. A thorough literature review contextualizes our work within the current state of blockchain scalability efforts. We introduce a methodology that integrates SOA into the transaction validation process of a blockchain network. The effectiveness of this approach is empirically evaluated by comparing transaction processing times before and after the implementation of SOA. The results show a substantial reduction in latency, with the optimized system achieving lower average transaction times across various transaction volumes. Notably, the latency for processing batches of 10 and 100 transactions decreased from 30.29 ms to 155.66 ms–0.42 ms and 0.37 ms, respectively, post optimization. These findings indicate that SOA is exceptionally efficient in batch transaction scenarios, presenting an inverse scalability behavior that defies typical system performance degradation with increased load. Our research contributes a significant advancement in blockchain scalability, with implications for the development of more efficient and adaptable blockchain systems suitable for high throughput enterprise applications.

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  • Data depth and core-based trend detection on blockchain transaction networks

    Data depth and core-based trend detection on blockchain transaction networks

    Blockchains are significantly easing trade finance, with billions of dollars worth of assets being transacted daily. However, analyzing these networks remains challenging due to the sheer volume and complexity of the data. We introduce a method named InnerCore that detects market manipulators within blockchain-based networks and offers a sentiment indicator for these networks. This is achieved through data depth-based core decomposition and centered motif discovery, ensuring scalability. InnerCore is a computationally efficient, unsupervised approach suitable for analyzing large temporal graphs. We demonstrate its effectiveness by analyzing and detecting three recent real-world incidents from our datasets: the catastrophic collapse of LunaTerra, the Proof-of-Stake switch of Ethereum, and the temporary peg loss of USDC–while also verifying our results against external ground truth. Our experiments show that InnerCore can match the qualified analysis accurately without human involvement, automating blockchain analysis in a scalable manner, while being more effective and efficient than baselines and state-of-the-art attributed change detection approach in dynamic graphs.

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  • Enhanced scalability and privacy for blockchain data using Merklized transactions

    Enhanced scalability and privacy for blockchain data using Merklized transactions

    Blockchain technology has evolved beyond the use case of electronic cash and is increasingly used to secure, store, and distribute data for many applications. Distributed ledgers such as Bitcoin have the ability to record data of any kind alongside the transfer of monetary value. This property can be used to provide a source of immutable, tamper-evident data for a wide variety applications spanning from the supply chain to distributed social media. However, this paradigm also presents new challenges regarding the scalability of data storage protocols, such that the data can be efficiently accessed by a large number of users, in addition to maintaining privacy for data stored on the blockchain. Here, we present a new mechanism for constructing blockchain transactions using Merkle trees comprised of transaction fields. Our construction allows for transaction data to be verified field-wise using Merkle proofs. We show how the technique can be implemented either at the system level or as a second layer protocol that does not require changes to the underlying blockchain. This technique allows users to efficiently verify blockchain data by separately checking targeted individual data items stored in transactions. Furthermore, we outline how our protocol can afford users improved privacy in a blockchain context by enabling network-wide data redaction. This feature of our design can be used by blockchain nodes to facilitate easier compliance with regulations such as GDPR and the right to be forgotten.

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