Sustainable finance is becoming an essential tool in addressing critical global environmental challenges such as climate change, biodiversity loss, and resource depletion with the youth generation emerging as a central driver for green investment models.The research identifies new participatory financial systems led by youth, which promote sustainable development, particularly in areas such as renewable energy, climate change, and the circular economy.We achieve this by examining the shift in investment patterns in general, as well as the specific trends among rich young entrepreneurs, activists, and technologists.This is carried out through an indepth analysis of grassroots actions, case studies, and decentralized finance (DeFi) models.The article explores new ways of engaging youth in crowdfunding platforms, green bonds, tokenized carbon credits, and venture funds that focus on environmental, social, and governance (ESG) issues, bringing sustainability finance within the reach of all and reducing the entry barrier to green innovation.Furthermore, the study sheds light on the interaction between the benefits of technology and finance, as well as the use of blockchain, AI, and other fintech solutions provided by youth-led platforms to maintain accountability, traceability, and scalability in green investment projects.The paper also examines policy gaps and institutional issues contributing to the inability of young people to access sustainable finance and provides recommendations to facilitate an environment that can foster innovation as well as inclusion in it.The study also identifies young changemakers as key drivers in achieving the United Nations Sustainable Development Goals (SDGs), specifically SDG 13 (Climate Action) and SDG 17 (Partnerships for the Goals), by placing them in perspective not just as recipients of sustainable finance, but as creators of its ecosystems.This piece of work is part of the debate around inclusive green growth and a roadmap in terms of empowering the future generation to live within the context of the sustainable economic model.
In an era marked by increasingly sophisticated cyber threats and growing vulnerabilities in national critical infrastructure, this study explores the transformative role of confidential computing in defending against emerging cryptographic attacks and enabling secure threat intelligence sharing. Traditional cybersecurity measures, while effective for protecting data at rest and in transit, fall short in securing data during active processingan area exploited by advanced persistent threats, quantum computing, and side-channel attacks. This research investigates how hardware-based trusted execution environments (TEEs), homomorphic encryption, and zero-knowledge proofs embedded in confidential-computing platforms can preserve the confidentiality of sensitive operations even within potentially compromised environments. Through detailed case studies of major U.S. institutionsincluding PGandE, Exelon, JPMorgan Chase, Wells Fargo, and Kaiser Permanentethe paper demonstrates significant improvements in detection speed, false positive reduction, and operational efficiency. Furthermore, it proposes a scalable, privacy-preserving framework for collaborative cyber defense across critical sectors such as energy, finance, and healthcare. The findings underscore that integrating confidential computing with decentralized intelligence sharing networks not only enhances cybersecurity resilience but also yields substantial economic and regulatory benefits. This work advocates for a national, and eventually global, shift toward confidential-computing-enabled infrastructures to achieve robust, cooperative, and future-proof cyber defense ecosystems.
This literature review investigates the influence of fair value accounting (FVA) on enhancing financial transparency, particularly within the evolving context of digital assets. By analyzing 103 peer-reviewed articles, the study evaluates how FVA facilitates automated, real-time, and market-based disclosures. It identifies FVA as a tool for increasing investor trust and improving the clarity of financial statements by aligning valuations with current market conditions. The review also highlights the specific challenges of applying FVA to decentralized and volatile digital assets such as cryptocurrencies and non-fungible tokens (NFTs). Although FVA contributes to more transparent and relevant reporting, the implementation of FVA for digital assets is hindered by several critical issues. These include inconsistent valuation methodologies, lack of standardized regulatory guidance, susceptibility to market manipulation, and technological limitations in tracking asset value across decentralized platforms. Furthermore, the rapid pace of innovation in digital finance outstrips the adaptability of existing accounting standards and legal frameworks, creating a gap that weakens the consistency of fair value assessments. The review proposes the integration of FVA within a broader theory of decision-making under uncertainty, emphasizing the need for adaptive and digitization-responsive accounting practices. It suggests practical frameworks that align valuation procedures with the unique characteristics of digital assets while ensuring compliance with emerging regulations. This research encourages ongoing examination and policy innovation to ensure that FVA continues to support transparency and informed decision-making in a dynamic financial landscape.
Kundan Mukhia, SR Luwang, Md. Nurujjaman, Tanujit Chakraborty · 6 authors
Scaling laws offer a powerful lens to understand complex transactional behaviors in decentralized systems. This study reveals distinctive statistical signatures in the transactional dynamics of ERC20 tokens on the Ethereum blockchain by examining over 44 million token transfers between July 2017 and March 2018 (9-month period). Transactions are categorized into four types: EOA--EOA, EOA--SC, SC-EOA, and SC-SC based on whether the interacting addresses are Externally Owned Accounts (EOAs) or Smart Contracts (SCs), and analyzed across three equal periods (each of 3 months). To identify universal statistical patterns, we investigate the presence of two canonical scaling laws: power law distributions and temporal Taylor's law (TL). EOA-driven transactions exhibit consistent statistical behavior, including a near-linear relationship between trade volume and unique partners with stable power law exponents ($γ\approx 2.3$), and adherence to TL with scaling coefficients ($β\approx 2.3$). In contrast, interactions involving SCs, especially SC-SC, exhibit sublinear scaling, unstable power-law exponents, and significantly fluctuating Taylor coefficients (variation in $β$ to be $Δβ= 0.51$). Moreover, SC-driven activity displays heavier-tailed distributions ($γ< 2$), indicating bursty and algorithm-driven activity. These findings reveal the characteristic differences between human-controlled and automated transaction behaviors in blockchain ecosystems. By uncovering universal scaling behaviors through the integration of complex systems theory and blockchain data analytics, this work provides a principled framework for understanding the underlying mechanisms of decentralized financial systems.
Blockchain technology, underpinned by distributed ledger systems, has evolved from a novel innovation into a transformative and integral component of enterprise digitization across industries. Since its inception with Bitcoin in 2008, blockchain has expanded beyond cryptocurrencies, with applications in operations management (OM) growing rapidly across industries. Despite its promise, however, the integration of blockchain into OM is not without challenges. Scholars have identified significant barriers to successful implementation, ranging from technological and organizational hurdles to regulatory complexities (Chod et al. 2020; Hanisch et al. 2025; Lin et al. 2022; Lumineau et al. 2021; Sodhi et al. 2022; Zhan et al. 2025). This Special Issue on Operational Perspectives on Blockchain Applications presents cutting-edge research that explores blockchain's opportunities, challenges, and implications for OM. The articles in this issue provide a diverse and empirically grounded examination of blockchain applications across industries and operational contexts. We will discuss each contribution in turn. However, prior to that, it is useful to dig into the operational nuances, opportunities, and challenges presented by the focal context. Our editorial discussion opens accordingly, outlining the technological, organizational, and regulatory challenges while identifying the conditions under which blockchain can deliver value. We also touch on the broader societal implications of blockchain, addressing its political, economic, social, environmental, and legal dimensions before describing how each of the papers in the special issue contributes to understanding, critical to operations management. Finally, our editorial discussion concludes by charting a research agenda, highlighting key questions and interdisciplinary approaches needed to advance both theoretical and practical understanding of blockchain in OM. Working processes need to be discovered, described, and understood before they can be improved, controlled, and prescribed. Quite a bit of work is needed merely to describe some of the important activities, practices, processes, and operating systems utilized in diverse organizations. Only then can we begin to sink our teeth into developing better theories about how best to manage them. For this purpose, Ilk et al. (2021) conceptualize the Bitcoin blockchain (and other mainstream permissionless blockchains) as a two-side dataspace market, where users demand a certain amount of dataspace in a future block to store their transactions, and miners compete to produce such dataspace by creating new blocks. To facilitate this market in a decentralized manner—that is, with no centralized party absorbing demand and controlling supply—users attach a transaction fee (which is higher for users with a higher waiting cost) that becomes one of the miners' sources of revenue. With the increasing popularity1 of Bitcoin and Ethereum, demand frequently exceeds supply, creating contemporaneous system congestions. The congested service pricing literature, which dates back to the management of highway tolls (Naor 1969) and electric power supply (Viswanathan and Edison 1989) and extends in modern days to subscription pricing of cloud services (Cachon and Feldman 2011) and surge pricing of gig economy platforms (Cachon et al. 2017), yields a generalized conclusion. Specifically, “offering multiple service grades that each render a different delay distribution at a different price” improves both perceived customer satisfaction and service provider profit (Van Mieghem 2000, 1249). Permissionless blockchains, as congested service systems, are no exception to this rule. Although no centralized party (i.e., firm or platform) sets the priority price menu, users bid transaction fees to differentiate the service grades (i.e., transaction confirmation speeds) they desire. More details on the process view of permissionless blockchain transactions can be found in Shang et al. (2023, 106–108). Although early Ethereum-based smart contract applications were rarely associated with OM or any other real-world assets, their ingenuity inspired a whole class of permissioned blockchains (also referred to as private or consortium chains), in which only an authorized group of users can participate, setting the stage for enterprise applications (Fan et al. 2024; Pun et al. 2021). While blockchain offers considerable potential, its successful implementation is hindered by technological, organizational, and regulatory barriers. Below, we highlight seven of the most critical challenges to blockchain implementation discussed in the press and in the literature. Low throughput and high transaction fees. The primary reason that mainstream cryptocurrency systems cannot be used for day-to-day payment is their throughput limits: 3 per second for Bitcoin and 13 per second for Ethereum.2 This limitation is in sharp contrast with the processing capacity of established financial systems like Visa, which is capable of handling approximately 5000 transactions per second (Malik et al. 2022). Such scalability limits are largely inevitable for permissionless blockchains that aim to ensure decentralization and security, widely known as the “blockchain trilemma” in the industry.3 The throughput limit results in a frequently congested service system with transaction fee spikes (Ilk et al. 2021; Shang et al. 2023), which has been 2.87 USD per transaction for Bitcoin in 2020. This hinders the economic viability of small value transactions even in situations where network latency is less of a concern (e.g., users with high waiting tolerance). Meanwhile, permissioned blockchains typically do not face throughput limits, as dataspace suppliers are usually the blockchain owners and hence do not have to be incentivized via instruments such as transaction fees. However, due to the lack of public visibility and the corporate ownership of these blockchains, this solution is unlikely to be suitable for all applications. Algorithm fairness. Advocates of permissionless blockchains often highlight their morally significant goal of improving access to money transfer services for unbanked and underbanked populations (Andreasson 2022). Importantly, much of the wealth on permissionless blockchains is created through mining/staking revenue—that is, through participation on the supply side—and small users typically cannot meet the entrance threshold for this revenue stream. Further, while large senders can develop sophisticated algorithms to estimate the desired transaction fee more accurately, small senders typically rely on the free-to-use fee recommendation tools crypto wallets provide. Encouragingly, this disparity is somewhat alleviated by new transaction fee mechanism designs (Zhao, Wu, et al. 2025). Decentralization–efficiency tradeoff. The management of a cryptocurrency system is typically maintained by a decentralized autonomous organization (DAO). A DAO's daily operational tasks include the development of, voting on, and execution of crowdsourced proposals (Zhao et al. 2022). Yet, not all project decisions are strategic enough to warrant crowdsourcing of ideas from stakeholders, and the inefficiency of doing so affects operational agility and the quality of service provided by the DAO. Further, while decentralization can improve service levels for users and providers, it reduces profits for founders, reflecting a broader tension between decentralization and efficiency (Gan et al. 2023). Governance frictions are compounded by token-weighted voting, where those holding more tokens have greater influence, creating a mismatch between token ownership and subject expertise (Benhaim et al. 2023, 2025; Tsoukalas and Falk 2020). Cross-chain interoperability. A successful blockchain application often requires coordination of activities across multiple chains. This is especially true for enterprise applications, where material flow needs to be traced on a permissioned blockchain (for obvious business confidentiality reasons) and payment of goods should preferably happen on a permissionless blockchain. In general, the lack of universal standards creates a fragmented landscape in which disparate blockchain platforms are developed in isolation. This technical challenge of interoperability is further complicated by the need to integrate blockchain with legacy systems, which typically lack the flexibility to accommodate cryptographic protocols and distributed data synchronization (Babich and Hilary 2019). Standardization of input data. Many of the cargo tracking and supply chain traceability blockchain applications assume the existence of a data on-ramp that is accessible to and standardized across participants. This is far from reality. As Fan et al. (2024, 3) put it, “a small supplier, say, in India or China, is unlikely to have the resources or expertise to set up an arrangement to access blockchain.” Even if such access is set up by a large participant of the permissioned blockchain, such as a superstore retailer, the input data from thousands of small suppliers across the world might not be properly digitized and standardized. Both the invasive and non-invasive approaches to bridging the physical–digital interface in blockchain applications have merits and drawbacks (Klöckner et al. 2023). Buy-in from partner organizations. Lin et al. (2022) highlight buy-in from partners along with information complexity as two important drivers that determine the success of blockchain pilots in real life. They stress the importance of reducing information complexity as well as increasing buy-in among supply chain partners. Critically, the cost and hassle of implementation are borne by all organizations that the cargo passes through, including port authorities, customs agencies, shipment forwarders, trucking companies, and so on. Some of these organizations lack the basic incentive to even digitize their paperwork, let alone upload information onto a blockchain owned by another company. Regulatory uncertainty. Regulatory challenges present another significant barrier to blockchain adoption in OM. The regulatory framework for blockchain is still in a nascent stage, with many jurisdictions lacking clear guidelines regarding its use, especially in non-financial contexts such as OM (Wagner et al. 2025). The cross-border nature of many supply chains makes it even more challenging to reconcile diverse regulatory environments; thereby complicating large-scale implementations (Wamba and Queiroz 2020). In summary, blockchain presents a range of unique characteristics, implementation challenges, and potential transformative impacts. Figure 1 captures many of these, as well as presenting new opportunities to apply common theoretical lenses used by researchers to understand this new technology, including Transaction Cost Economics (TCE), Principal Agent Theory (PAT), and Resource-Based View (RBV). These features are pushing the OM community to consider additional theoretical arguments regarding blockchain-related operational dynamics so as to more comprehensively understand, anticipate, and ultimately contribute to practice and scholarship in this domain. More specifically, traditional theoretical frameworks commonly applied in OM, such as transaction cost economics, principal–agent theory, and the resource-based view, have proven effective for analyzing centralized systems where information is controlled and trust is built through well-established interorganizational relationships. However, blockchain disrupts these conventional relationships by enabling peer-to-peer interactions governed not by a central authority but by cryptographic mechanisms and consensus protocols. For instance, the immutability of recorded transactions and the inherent decentralization of blockchain networks modify the traditional calculus of trust and coordination costs. These features create “trustless” environments where the need for intermediaries is significantly reduced. This shift calls into question the applicability of many preexisting theoretical models that assume reliance on centralized control and interpersonal trust (Lumineau et al. 2023). Given these fundamental differences, one promising direction for future research is to expand network theory and social capital theory in OM by integrating the notion of distributed trust. Whereas social capital theory has been used to explain performance improvements arising from strengthened interorganizational relationships (Saberi et al. 2019), blockchain technology challenges these premises by redistributing trust across the network without necessarily relying on strong personal or organizational ties (Lumineau et al. 2023). Similarly, although transaction cost theory provides insight into how blockchain can lower the costs of verification and contracting by obviating the need for costly intermediaries, the theory does not fully account for the dynamic interplays that arise when trust is engineered digitally and contractual obligations are embedded in smart contracts (Halaburda et al. 2024). As Babich and Hilary (2019) note, new theoretical models need to capture not only the cost-saving benefits of disintermediation but also the potential trade-offs in terms of data insecurity and operational inflexibility. There is also a growing recognition that hybrid frameworks, which merge elements of institutional theory and network governance with emerging blockchain paradigms, may be necessary to understand new organizational forms like DAOs (Zhao et al. 2022). The need for novel theoretical frameworks is particularly critical when considering the impact of blockchain on various stakeholders within the OM ecosystem. Traditional models generally emphasize dyadic relationships between buyers and suppliers, but blockchain enables multi-stakeholder environments in which data transparency, provenance, and auditability permeate complex, global supply networks. For example, Chod et al. (2020) show how blockchain can improve financing in agricultural supply chains by enabling farmers to use harvest inventory as loan collateral. Using multi-signature setups tied to an immutable blockchain, transactions require confirmation from both humans (e.g., lenders or warehouse operators) and automated systems (e.g., IoT sensors). This approach allows for real-time verification of collateral, reduces information asymmetry, and unlocks capital, particularly in settings prone to fraud. Together, the articles in this Special Issue make a multifaceted contribution to OM, demonstrating the impact of blockchain technology in various operational forms on strategic decision-making, worker participation, competitive and network dynamics, and intellectual property protection across different sectors. These studies use robust empirical methods and diverse theoretical frameworks to offer novel insights into the role of blockchain in OM. Some of the studies use qualitative methods for developing theory concerning conditions for successful and failed blockchain adoption. Zhan et al. (2025) develop theory through an inductive, multi-case research design revealing the influence of founder power on blockchain adoption. Meanwhile, Hanisch et al. (2025) use an in-depth, longitudinal case study to explore the centralization–decentralization paradox of a group of studies or designs at the of or a and et al. (2025) on adoption of smart contracts and their operational studies use data from network or blockchain platforms Ethereum, and For example, (2025) and approaches to the operational impact of different consensus protocols on and worker et al. (2025) a by integrating ownership theory, and approaches to explore how decentralized ownership in DAOs et al. (2025) further develop the discussion by analyzing the transformative of blockchain on the protection of in In a et al. (2025) the impact of a on the operational the and et al. (2025) use an to the of on a decentralized and a centralized social These articles theoretical and empirical approaches to blockchain in OM, a on its strategic and operational most of the articles on or methods data from blockchain while a articles case studies and This may be due to the lack of large-scale data on OM Below, we will into the of each Zhan et al. 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(2025) how to on decentralized social which lack central authority and rely on community Using an with data from and the and show these methods in decentralized to centralized on decentralized networks and more but in a The research contributes to operations management by decentralized platforms as systems and practical insights for governance and Given the from the most research on the it clear that research questions and that might our understanding of blockchain's application opportunities and potential for OM. research question of in this framework is as do different blockchain governance impact operational efficiency and trust in on this should consider the between permissioned and permissionless blockchain how of decentralization and the role of smart contracts influence both and A study methods might performance data from blockchain with qualitative to how governance models trust among supply chain critical for effective potential of study into how blockchain can be embedded within enterprise and supply chain information systems to the and for more blockchain technology new models for inventory management of that account for customer of et al. 2024). might traditional inventory models with systems, case studies or controlled that improvements in and in with the of operations management such studies should on process details and merely the of technology and such as inventory A further further to is, can blockchain be to in supply chains This of research tracking and smart contracts the for and as well as how this technology can a role by in supply networks. studies that supply chain performance across as well as studies to blockchain's impact under various be particularly question might can blockchain be to in supply or should supply chain be with blockchain technology to or data However, these questions might also more in the of information systems particularly if their is not to operational process In future research in this will from into the multifaceted implications of blockchain technology for OM. research the impact of blockchain governance on operational efficiency and the transformative potential of blockchain for inventory management and supply chain and the capacity to in the face of central to both theoretical and practical an interdisciplinary approach that from public information technology, and organizational theory, future research can develop frameworks that the real-world challenges of blockchain in supply networks. 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<ns3:p>The emergence of Web 3.0 and the Metaverse marks a transformative shift in the evolution of the internet and digital ecosystems. This paper explores the foundational principles of decentralization, user autonomy, and data transparency that underpin Web 3.0 technologies, including blockchain, smart contracts, and digital wallets. We analyze how these innovations are reshaping business models, enabling new forms of value creation, and redefining digital ownership and governance. In parallel, we examine the Metaverse as a virtual, immersive environment integrating Web 3.0 infrastructure, and its potential to revolutionize sectors such as logistics, education, finance, and data management. The study also highlights the critical role of a holistic framework encompassing technological, economic, and legal pillars. A special focus is given to data provenance, privacy-preserving computation, and the need for coherent regulatory strategies in light of GDPR, the AI Act, and the Data Act (European Parliament, 2016; European Parliament, 2023; European Parliament, 2024). Finally, we identify emerging challenges related to NFT authenticity, system sustainability, and user experience, proposing a multidisciplinary and lean governance approach to guide future developments.</ns3:p>
Caio de Souza Barbosa Costa, Anna Helena Reali Costa
Recently, reinforcement learning has achieved remarkable results in various domains, including robotics, games, natural language processing, and finance. In the financial domain, this approach has been applied to tasks such as portfolio optimization, where an agent continuously adjusts the allocation of assets within a financial portfolio to maximize profit. Numerous studies have introduced new simulation environments, neural network architectures, and training algorithms for this purpose. Among these, a domain-specific policy gradient algorithm has gained significant attention in the research community for being lightweight, fast, and for outperforming other approaches. However, recent studies have shown that this algorithm can yield inconsistent results and underperform, especially when the portfolio does not consist of cryptocurrencies. One possible explanation for this issue is that the commonly used state normalization method may cause the agent to lose critical information about the true value of the assets being traded. This paper explores this hypothesis by evaluating two of the most widely used normalization methods across three different markets (IBOVESPA, NYSE, and cryptocurrencies) and comparing them with the standard practice of normalizing data before training. The results indicate that, in this specific domain, the state normalization can indeed degrade the agent's performance.
Modeling evolving interactions among entities is critical in many real-world tasks. For example, predicting driver maneuvers in traffic requires tracking how neighboring vehicles accelerate, brake, and change lanes relative to one another over consecutive frames. Likewise, detecting financial fraud hinges on following the flow of funds through successive transactions as they propagate through the network. Unlike classic time-series forecasting, these settings demand reasoning over who interacts with whom and when, calling for a temporal-graph representation that makes both the relations and their evolution explicit. Existing temporal-graph methods typically use snapshot graphs to encode temporal evolution. We introduce a full-history graph that instantiates one node for every entity at every time step and separates two edge sets: (i) intra-time-step edges that capture relations within a single frame and (ii) inter-time-step edges that connect an entity to itself at consecutive steps. To learn on this graph we design an Edge-Type Decoupled Network (ETDNet) with parallel modules: a graph-attention module aggregates information along intra-time-step edges, a multi-head temporal-attention module attends over an entity's inter-time-step history, and a fusion module combines the two messages after every layer. Evaluated on driver-intention prediction (Waymo) and Bitcoin fraud detection (Elliptic++), ETDNet consistently surpasses strong baselines, lifting Waymo joint accuracy to 75.6\% (vs. 74.1\%) and raising Elliptic++ illicit-class F1 to 88.1\% (vs. 60.4\%). These gains demonstrate the benefit of representing structural and temporal relations as distinct edges in a single graph.
Evgeniya Ishchukova, Sergei Petrenko, A. Petrenko, Konstantin Gnidko · 5 authors
Today, blockchain technologies are a separate, rapidly developing area. With rapid development, they open up a number of scientific problems. One of these problems is the problem of reliability, which is primarily associated with the use of cryptographic primitives. The threat of the emergence of quantum computers is now widely discussed, in connection with which the direction of post-quantum cryptography is actively developing. Nevertheless, the most popular blockchain platforms (such as Bitcoin and Ethereum) use asymmetric cryptography based on elliptic curves. Here, cryptographic primitives for blockchain systems are divided into four groups according to their functionality: keyless, single-key, dual-key, and hybrid. The main attention in the work is paid to the most significant cryptographic primitives for blockchain systems: keyless and single-key. This manuscript discusses possible scenarios in which, during practical implementation, the mathematical foundations embedded in the algorithms for generating a digital signature and encrypting data using algorithms based on elliptic curves are violated. In this case, vulnerabilities arise that can lead to the compromise of a private key or a substitution of a digital signature. We consider cases of vulnerabilities in a blockchain system due to incorrect use of a cryptographic primitive, describe the problem, formulate the problem statement, and assess its complexity for each case. For each case, strict calculations of the maximum computational costs are given when the conditions of the case under consideration are met. Among other things, we present a new version of the encryption algorithm for data stored in blockchain systems or transmitted between blockchain systems using elliptic curves. This algorithm is not the main blockchain algorithm and is not included in the core of modern blockchain systems. This algorithm allows the use of the same keys that system users have in order to store sensitive user data in an open blockchain database in encrypted form. At the same time, possible vulnerabilities that may arise from incorrect implementation of this algorithm are considered. The scenarios formulated in the article can be used to test the reliability of both newly created blockchain platforms and to study long-existing ones.
Silvia Edelweiss Crusco dos Santos, Hélder Sebastião, Nuno Silva
Using daily data from November 9, 2017 to December 31, 2022, this paper uses Granger causality in the mean and the distribution to investigate the transmission of information between return, volume, volatility, and illiquidity for Bitcoin and the nine most important altcoins in terms of market capitalization. Additionally, the forecastability of Bitcoin returns is examined using linear models with different predictor spaces estimated using LASSO and the performance of several trading strategies devised upon those forecasts is assessed. The causal relationships between returns, volumes and volatilities of Bitcoin and each altcoin are more evident in the left tail of the distribution, where Bitcoin acts mostly as a transmitter of information, and in the right tail for causality regarding illiquidity. In bullish markets, Bitcoin acts mostly as a receiver of information. The best Bitcoin trading strategy is based on the model which incorporates the information on all cryptocurrencies, exhibiting a cumulative return of 331% and an annualized Sharpe ratio of 94.59%, considering an enter/exit threshold of 0.25% and after 0.5% round-trip transaction costs. These results are statistically significant when compared with the buy-and-hold strategy, which renders a cumulative return of 121% and a Sharpe ratio of 64.74%. These results point out the importance of considering information from other cryptocurrencies to forecast and trade on Bitcoin.
Bock, Stephen. 2018. Translations of urban regulation in relations between Kigali (Rwanda) and Singapore. xiii + 338 pp., figs, tables. Zurich: LIT Verlag, 2018. Hudani, Shakira E. 2024. Master plans and minor acts: repairing the city in post-genocide Rwanda. 258 pp., figs. Chicago: University Press, 2024. $32.50 (paper). Shearer, Samuel. The Kigali model: making a 21st century metropolis. Ph.D. dissertation, Duke University, 2017. Three recent ethnographies of Kigali's urban planning and development provide a welcome addition to a long tradition of such ethnographies, including Lisa Redfield Peattie's famous fieldwork in the planning of Ciudad Guayana (1968; 1987), Grace Goodell's ethnographic account of the disjunction between planning offices in Tehran and the urban settlements (sharaks) of the Khuzistan Development Project modelled on the Tennessee Vally Authority (1986), and Gökce Günel's ethnographic analysis of the disjunction between plans for, and implementation of, Mazdar City and Mazdar Institute in Abu Dhabi (2019). Kigali, often dubbed ‘the African Singapore’, provides a model for thinking about new urban formations in Africa and elsewhere (see Pype, Adunbe & Fischer 2025), the circulation of planning consultancies, and the key social issues of dealing with informal settlements, overcrowding, and rights to the city. Having worked in Singapore for the past decade or so, I was long interested in the claim of the Singapore consultancy, and town planning agency within Singapore (Surbana), to have provided the planning for Kigali as well as a number of other cities in Africa. It was one of several initiatives to sell Singapore's expertise (industrial parks in China; port management in Turkey). A two-week intensive visit to Rwanda, including to its new district hospital and University of Global Health Equity in Butaro, a poor region of the north – both initiatives of the anthropologist Paul Farmer and Partners in Health – in the company of Dr. Aalyia Sadruddin (a long-time ethnographer in Rwanda whose network gave access to several of Rwanda's strategists), enhanced my desire to further ‘read for the ethnography’. ‘Reading for the ethnography’ is my slogan for creating a detailed empirical basis for theory building, evaluation of ethnographic writing, cultural critique, and the transnational circuitry of post-globalization. Reading for the ethnography is the ‘ground-truthing’, or finer grained precision, of claims of theory, just as aerial photography requires on-the-ground verification and often alternative understandings: What is the evidence? How well does the text demonstrate linguistic and cultural competence in eliciting emic accounts? Are there other accounts in the literature, other histories of the specific places, or alternative explanations? In the present comparison of three ethnographies of the same city and administrative structures, I pay attention to the ethnographic facts that each adduces that I can use to create a mosaic understanding of different parts of the city, different local histories of settlement and redevelopment, and different evolving plans versus local resistance or counter-movements of residents, and how the interlocutors and informants evaluate, complain, or take advantage of changing effects of city planners, global financing, and of organic incremental growth and ad hoc solutions. The three ethnographies are not quite like the elephant and the three blind men, but they present remarkably different accountings of how, where, and when things happened, even if at some points they draw upon similar generalizing language about financial and administrative logics and forces. I am interested in the way their empirical ethnographic materials complement each other to create a baseline for further inquiry – on Kigali, but also for comparative work across cities that face similar (but locally different) problems. I emphasize the ethnographic history of Singapore itself to counter the cliches, again looking for the precise ethnographic and historical evolutions in its experience, and the role of the Surbana town planning consultancy in Singapore and as it attempts to sell its experiences and expertise elsewhere. Writing about Kigali in transition must negotiate visionary ambitions and promissory publicity together with ‘ground truthing’, tracking emergent forms of social organization and struggles for rights to the city, along with gender relations, and visions of the good life. The three ethnographies proved to be quite different in focus and evidentiary basis. Stephan Bock embedded himself in the urban planning ministries of Rwanda, and at the Surbana consultancy offices in Singapore, to examine the role of Surbana's master plans and building regulations for Kigali. Samuel Shearer embedded himself in the street vendor markets and informal settlements looking to how their residents try ‘to defend their collective resources against the liquidating processes of speculative urbanism’ (p. 5). Shakira Hudani focuses on three types of resettlement areas to which people evicted from informal settlements are moved. As the terms ‘master plans’ and ‘speculative urbanism’ indicate, the forces are not merely local or contained within nation-states, but are imaginaries and financial forces circulating the globe. Kigali, Shearer suggests, has joined Singapore to be ‘on the forefront in a revolution of how cities are managed, lived, and imagined everywhere’ (p. 5). But Shearer is also an excellent guide to resistance and pushback from the people being managed. He takes a critical view of the master plan process ‘written by consultants in Singapore, funded by multinational investment corporations, to be exported from Kigali’ (p. 5). The ‘world class city’ for him does not actually produce the built environment it promises, but, ‘by activating global networks of capital and expertise with a compelling visual narrative about a city's future potential’, subverts the tactics available for use by the less advantaged city residents to have a stake in the city (p. 5). He claims the ‘international team of managers and consultants have “liberated” planning from the political and economic relations that paralyze planners in other cities’ (p. 5). His own excellent ethnography shows otherwise, or at least that it is not the whole story. Following Michael Goldman (2011), he asserts that the goals of ‘speculative urbanism’ are to create real estate investment opportunities. But, as Bock points out, money is required to build a city, and money-strapped Rwanda needed private-public investment to generate urban budgets but also ways to extract money from, and give ownership to, its own population. As Beng-Huat Chua, Singapore's leading sociologist and loyal critic, demonstrates, the housing mechanism in Singapore built the state through forced savings that the state could then leverage (Chua 2024). Rwanda, too, has a state mechanism to shape investment and growth: the national pension program (eligibility is paid contributions for fifteen years). Construction, in large part, is financed by three state-connected funds (Goodfellow & Smith 2013). Rwanda's political-administrative structure of districts, sectors, cells, imidugudu (the smallest formal unit of a hundred or so households) and an informal nyumbacumi (person overseeing ten households) is analogous to the organization of Singapore's People's Action Party's voluntary organizations and community centres built into housing estates (though not down to the same formal degree of ten households). Goodfellow and Smith provide an overview of the struggle to organize the city of Kigali between 1994 and 2000, and to prevent the race riots that Singapore experienced in its early days of independence and government consolidation. What is often called the ‘Singapore model’ is just one element of planning and design in a complex process of ‘from third world to first in one generation’ (in Lee Kuan Yew's famous tag line for ‘the Singapore Story’) or from low-income to middle-income country (in Paul Kagame's). Shearer, while criticizing aspects of Singapore's consultancy in Kigali notes that the whole idea was that the plan should pay for itself by attracting foreign capital. Furthermore, ‘what is called the Singapore model’ is ‘not because it follows that city's transformation, but because it conjures an idea of what global “city-ness” should look like, with Singapore as a reference’ (p. 131). The conjuring, he says, is ‘what Surbana sells’. It has sold ninety master plan projects in thirty countries mainly in Asia and Africa. These are promissory visions, and become integrated as one layer in cascades of implementation, with all the contingencies, blockages, and redesign involved. ‘Participatory planning’ is a buzz-word component (one that Lisa Redfield Peattie championed) but that Shearer points out in Rwanda today is often really participatory expropriation, letting coops and associations ‘purchase their own property and take out loans to develop that property’, often against the will (or lack of choice) of the participants (p. 139); a harsher version of the ‘forced savings’ that Beng-Huat Chua describes for Singapore. So how did this process get started? Here Bock is helpful. Pundits, Bock says, regularly give Rwanda good marks for economic development and bad marks for authoritarianism and human rights violations. But such binaries, he argues ‘do not help to disentangle the complexity of relations and interactions’. He calls for multi-locale and multi-scalar ethnographic approaches. He watched Kigali develop from 2006 when there were only a few hotels and government buildings taller than a single storey, no traffic lights, and only mini-buses for public transportation. By 2011 there were cleared areas waiting for redevelopment, traffic lights, and larger buses. In the immediate post-genocide years, emergency attention had to be given to the city, of the and and of and is an to the early of Singapore, both urban that the and were and people were into Kigali had and and City a as well as city master plan for a master plan with some from the and The first Kigali Master was by the consultancy in Singapore's Surbana was in to a master and in The dubbed Kigali Kigali as Bock and with a street of and of Shearer is for the he and Bock with real the focus with residents, and building a that had to work there were no real or have had in the in 1994 and the of the a of urban out from a public and into and with community and to on the informal settlement the markets as to be and paid and the settlements needed and use But a master plan is not just a it is a to a new city did some detailed planning for and building In an of of Kigali's But how to Bock to Singapore and in were to Singapore, and In Surbana the for detailed planning of Kigali's and A Surbana was within the Kigali planning (the Surbana of Kigali in to it to the plans and to the an to on as and a way for to from their to their be in the master were about the in the of housing needed and that into or housing than Beng-Huat Chua, in ‘Singapore as model’ (2011), that the model be only can The Singapore government of the and could and with a good Singapore could in the to or in the financial this to Surbana as claims to have planning projects in thirty countries (in and and In Singapore it has create of a In Rwanda, the structure of the political was from the in which the were given of with the to be and and work were not the and in the state to the city was not people their were Bock were in to by were to produce and But in the and early global and and a provides an that in the and from to for the of and the development of this the with and with and Bock a government a country such as the only is that of a that can and the economic some from the and the key was as of the was today in the so, a key focus was to use consultants for and but Singapore, with an that had to become participants in the planning not just of Paul in had a of to plan the development of the country from to middle-income by in 2000, a team to to about of A was to Rwanda for from the which also from countries to create a The Rwanda Development the of the Development of was to as a for Rwanda's in the global of the for The Rwanda The Development and for on to and to focus on urban use and master Hudani argues that the planning of a state is to a of social issues of rights to the city, and incremental of and social argues that one Rwanda as a of urban the was the in when the in a of and again today with the of and in and claims upon of three different and types of development Shearer that three urban are each and the urban of the built and social have the of urban and visual to and housing of are on to with on-the-ground with the people could help such in with in all three ethnographies, but to the Singapore are accounts of to as of a national to human capital. 2000, Singapore funded for and at and the of the or their own have to a number of for and have funded to and and along with multinational Rwanda is to The new and University of Global Health Equity in with and the is to provide for and across the African like the of and of the University of Rwanda in Kigali, were built with local and attention to the Kigali's economic the for (one of the of the against to an and development to provide for countries in the African the first such on the African 2024). also – of the of but to the focus on the urban planning – are of Singapore, this the on and parks on and in was an economic an plan by of & Rwanda, it the from through and the it has through the ethnographies to emergent forms of social and struggles for rights to the city, a of historical relations are a and history that further account of street and of and also of an African of that and forms of are the Rwanda has the of in than other as well as a number of government Shearer, a with a of by a local at and were to prevent from a by a street to pay a to local or community are to and but, in this not only was the but the the city's master which and the for The not only the but called a as the were the the work community the of the is a of produce and sell of produce that they have or on from or and on the in the world in and are locally and sold as in are then or by and as than as or are called is in this is than which there is also a or of into and of and and The street have their own so each or to use the to pay down are single with each and often of making a and by the that pay less than or for and in the some for were to the Shearer says, narrative of Kigali as an state with a that the and of is (p. The the the and The to down for a for a few and then the city, street informal settlements, and are a and and Shearer, the that stake for urban residents in the century is how to defend collective resources against the liquidating processes of speculative urbanism’ (p. Shearer provides and of informal settlements in of were and by the and The had to but only for the not the which it to the the and work people to to what they The residents also their own to the were just and to a new housing by the pension ethnographic is of the or of Kigali are called by their but by of other famous informal settlements (or or are or things and in in the (in poor Shearer is for the and which he by the had become he the development state of was for of the the and could well from the and with foreign and and a of and and In the In the Rwanda from The were by It Shearer says, the of the and for and from the city to out the some to the as a to use against the (p. 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He a at Duke University so He has a of on and in and and an with and an anthropologist of Rwanda on as
Efficient smart contract implementation affects gas fees required for deployment and invocation, contributing to the usability and sustainability of blockchain applications that rely on smart contracts. Optimizing smart contract codes is crucial to curb the continued rise of costs related to deploying and invocating smart contracts. This work proposes an extended version of static smart contract optimizer to reduce unnecessary gas fees caused by inefficient smart contract code implementation. Thirty open-licensed Ethereum smart contract codes in the Solidity programming language are included for optimization using the proposed static optimizer. The results show a decrease of 11,447 gas for deployment and 25 for invocation. Additional optimization using the Solidity compiler optimizer reveals a further gas reduction of 9,331 for deployment. Although there was a slight gas increase of 23 during invocation. These findings demonstrate the contribution of the proposed static optimizer in optimizing code implementation for Solidity smart contracts in terms of deployment and invocation. In addition to the gas reductions, the functionalities of the optimized smart contracts remain the same.
The transformation of digital payment systems through blockchain technology has brought new challenges and opportunities in the development of secure, efficient, and decentralized crypto tokens. One emerging approach is the use of smart contract-based tokens, such as ERC-20 tokens running on the Ethereum network. This research proposes the design and implementation of the SDSPay (SDS) token as a prototype Ethereum-based ERC-20 token, with a modern smart contract approach to meet the needs of a more efficient and secure digital payment system. The SDS token adopts the basic ERC-20 standard but is equipped with advanced features that enhance functionality and security, such as role-based access control (RBAC) to regulate access and control over transactions, pauseable transactions to pause transactions if necessary, and compatibility with EIP-2612 permits that enable more efficient transaction authorization in terms of gas. These features are designed to improve the efficiency and security of transactions on blockchain networks, thus enabling the use of tokens in a more reliable digital payment system. The SDS token prototype was tested on the Sepolia Testnet using Remix IDE and MetaMask to develop and manage smart contracts. Additionally, a static security audit was conducted using Slither Analyzer to detect potential vulnerabilities. The test results showed that the SDS token was successfully deployed and performed well, with an average transaction time of 10–12 seconds and stable gas fees. The Slither audit also found no significant vulnerabilities, indicating that the smart contract structure adheres to security best practices. This study confirms that the development of standardized smart contract-based tokens can be carried out using an efficient, reliable, and replicable methodology for other applications in future blockchain-based payment systems. This implementation of the SDSPay (SDS) token can serve as a foundation for designing secure and efficient digital payment systems, paving the way for the broader development of blockchain technology.
The accelerating adoption of electric vehicles (EVs) has revealed a significant challenge: ensuring accessible, secure charging infrastructure in areas with limited internet connectivity. This study introduces EVMCSDLT, a novel payment framework that leverages Distributed Ledger Technology (DLT) to facilitate secure transactions between EV users and mobile charging stations in offline environments. Unlike conventional payment systems that require continuous Internet connectivity, EVMCSDLT employs a two-part blockchain security mechanism using QR code authentication and hashing techniques. This mechanism distributes security data across both the sender's & receiver's devices, enabling transactions to be validated & recorded locally before subsequent synchronization with the blockchain network. The system is implemented using React.js integrated with Web3, supporting both online & offline transaction processing via MetaMask wallet. It also features real time geospatial tracking of fixed and mobile charging stations through Google Maps, allowing users to locate nearby charging options efficiently. Experimental results demonstrate a reliable transaction range of up to 8.13 meters between devices, consistent QR code scanning with an average response time of 3.4 s under various lighting conditions, and strong resistance to cyber threats in simulated man-in-the-middle attacks. The EVMCSDLT framework marks a significant advancement in extending the accessibility of EV charging technology to underserved areas while ensuring transaction security and integrity regardless of the Internet connectivity status.
In the increasingly digital era demanding transparency, blockchain emerges as a technology with significant potential to support higher education services. This system offers security, efficiency, and decentralization in managing academic data and certifications. This study aims to examine the role of blockchain in improving service quality and student loyalty. Data were collected through interviews and FGDs with participants from students, faculty, and administrative staff relevant to the technology's implementation in their institutions. The findings show positive acceptance of blockchain, especially in terms of transparency and service speed. Participants also suggested digital incentives through a token system as a way to encourage active student engagement. However, challenges such as infrastructure, technological literacy, and regulations remain major obstacles. These results reinforce that blockchain can improve service quality and create loyalty based on a fair and measurable system.
Decentralized Autonomous Organizations (DAOs) represent a new form of economic organization, leveraging smart contracts and blockchain technology to manage financial operations, governance, and decision-making. This structure eliminates the need for centralized intermediaries. From an accounting and economic perspective, this article investigates DAOs, offering a comprehensive examination of their architecture, voting methods, governance procedures, smart contract vulnerabilities, and the legal environment. The article proposes a five-tiered DAO structure, demonstrating how each layer contributes to operational efficiency, transparency, and decentralized responsibility. The study emphasizes the importance of smart contract auditing tools in ensuring reliable financial transactions. According to the data presented in the study, applying traditional accounting principles to token-based transactions, decentralized decision systems, and DAO treasuries poses significant challenges such as token valuation, revenue recognition, and the absence of standardized reporting formats. The study explains how DAOs act as economic coordinators, using real-world case studies such as MakerDAO, Gitcoin DAO, and Uniswap DAO. Additionally, the research highlights the issues DAOs face regarding valuation and compliance. This article concludes with a policy-focused examination of regulatory gaps and offers suggestions for future research directions in the areas of financial integration, legal categorization, and the sustainability of DAOs. Through the integration of institutional and economic theory with the technical structure of DAOs, this research advances our understanding of DAOs as novel forms of finance and governance.
Time series forecasting plays a vital role across scientific, industrial, and environmental domains, especially when dealing with high-dimensional and nonlinear systems. While Transformer-based models have recently achieved state-of-the-art performance in long-range forecasting, they often suffer from interpretability issues and instability in the presence of noise or dynamical uncertainty. In this work, we propose DeepKoopFormer, a principled forecasting framework that combines the representational power of Transformers with the theoretical rigor of Koopman operator theory. Our model features a modular encoder-propagator-decoder structure, where temporal dynamics are learned via a spectrally constrained, linear Koopman operator in a latent space. We impose structural guarantees-such as bounded spectral radius, Lyapunov based energy regularization, and orthogonal parameterization to ensure stability and interpretability. Comprehensive evaluations are conducted on both synthetic dynamical systems, real-world climate dataset (wind speed and surface pressure), financial time series (cryptocurrency), and electricity generation dataset using the Python package that is prepared for this purpose. Across all experiments, DeepKoopFormer consistently outperforms standard LSTM and baseline Transformer models in terms of accuracy, robustness to noise, and long-term forecasting stability. These results establish DeepKoopFormer as a flexible, interpretable, and robust framework for forecasting in high dimensional and dynamical settings.
Nicknames for Group Signatures (NGS) is a new signature scheme that extends Group Signatures (GS) with Signatures with Flexible Public Keys (SFPK). Via GS, each member of a group can sign messages on behalf of the group without revealing his identity, except to a designated auditor. Via SFPK, anyone can create new identities for a particular user, enabling anonymous transfers with only the intended recipient able to trace these new identities. To prevent the potential abuses that this anonymity brings, NGS integrates flexible public keys into the GS framework to support auditable transfers. In addition to introducing NGS, we describe its security model and provide a mathematical construction proved secure in the Random Oracle Model. As a practical NGS use case, we build NickHat, a blockchain-based token-exchange prototype system on top of Ethereum.
The convergence of Web3 technologies and AI agents represents a rapidly evolving frontier poised to reshape decentralized ecosystems. This paper presents the first and most comprehensive analysis of the intersection between Web3 and AI agents, examining five critical dimensions: landscape, economics, governance, security, and trust mechanisms. Through an analysis of 133 existing projects, we first develop a taxonomy and systematically map the current market landscape (RQ1), identifying distinct patterns in project distribution and capitalization. Building upon these findings, we further investigate four key integrations: (1) the role of AI agents in participating in and optimizing decentralized finance (RQ2); (2) their contribution to enhancing Web3 governance mechanisms (RQ3); (3) their capacity to strengthen Web3 security via intelligent vulnerability detection and automated smart contract auditing (RQ4); and (4) the establishment of robust reliability frameworks for AI agent operations leveraging Web3's inherent trust infrastructure (RQ5). By synthesizing these dimensions, we identify key integration patterns, highlight foundational challenges related to scalability, security, and ethics, and outline critical considerations for future research toward building robust, intelligent, and trustworthy decentralized systems with effective AI agent interactions.
S M Mostaq Hossain, Sheikh Ghafoor, Kumar Yelamarthi, Venkata Prasanth Yanambaka
Physically Unclonable Function (PUF) offers a secure and lightweight alternative to traditional cryptography for authentication due to their unique device fingerprint. However, their dependence on specialized hardware hinders their adoption in diverse applications. This paper proposes a novel blockchain framework that leverages SoftPUF, a software-based approach mimicking PUF. SoftPUF addresses the hardware limitations of traditional PUF, enabling secure and efficient authentication for a broader range of devices within a blockchain network. The framework utilizes a machine learning model trained on PUF data to generate unique, software-based keys for each device. These keys serve as secure identifiers for authentication on the blockchain, eliminating the need for dedicated hardware. This approach facilitates the integration of legacy devices from various domains, including cloud-based solutions, into the blockchain network. Additionally, the framework incorporates well-established defense mechanisms to ensure robust security against various attacks. This combined approach paves the way for secure and scalable authentication in diverse blockchain-based applications. Additionally, to ensure robust security, the system incorporates well-established defense mechanisms against various attacks, including 51%, phishing, routing, and Sybil attacks, into the blockchain network. This combined approach paves the way for secure and efficient authentication in a wider range of blockchain-based applications.
This paper explores neural network-based approaches for algorithmic trading in cryptocurrency markets. Our approach combines multi-timeframe trend analysis with high-frequency direction prediction networks, achieving positive risk-adjusted returns through statistical modeling and systematic market exploitation. The system integrates diverse data sources including market data, on-chain metrics, and orderbook dynamics, translating these into unified buy/sell pressure signals. We demonstrate how machine learning models can effectively capture cross-timeframe relationships, enabling sub-second trading decisions with statistical confidence.
Generative modeling of high-frequency limit order book (LOB) dynamics is a critical yet unsolved challenge in quantitative finance, essential for robust market simulation and strategy backtesting. Existing approaches are often constrained by simplifying stochastic assumptions or, in the case of modern deep learning models like Transformers, rely on tokenization schemes that affect the high-precision, numerical nature of financial data through discretization and binning. To address these limitations, we introduce ByteGen, a novel generative model that operates directly on the raw byte streams of LOB events. Our approach treats the problem as an autoregressive next-byte prediction task, for which we design a compact and efficient 32-byte packed binary format to represent market messages without information loss. The core novelty of our work is the complete elimination of feature engineering and tokenization, enabling the model to learn market dynamics from its most fundamental representation. We achieve this by adapting the H-Net architecture, a hybrid Mamba-Transformer model that uses a dynamic chunking mechanism to discover the inherent structure of market messages without predefined rules. Our primary contributions are: 1) the first end-to-end, byte-level framework for LOB modeling; 2) an efficient packed data representation; and 3) a comprehensive evaluation on high-frequency data. Trained on over 34 million events from CME Bitcoin futures, ByteGen successfully reproduces key stylized facts of financial markets, generating realistic price distributions, heavy-tailed returns, and bursty event timing. Our findings demonstrate that learning directly from byte space is a promising and highly flexible paradigm for modeling complex financial systems, achieving competitive performance on standard market quality metrics without the biases of tokenization.
Yonas Teweldemedhin Gebrezgiher, Sekione Reward Jeremiah, Xianjun Deng, Jong Hyuk Park
Vehicle-to-everything (V2X) communication is a fundamental technology in the development of intelligent transportation systems, encompassing vehicle-to-vehicle (V2V), infrastructure (V2I), and pedestrian (V2P) communications. This technology enables connected and autonomous vehicles (CAVs) to interact with their surroundings, significantly enhancing road safety, traffic efficiency, and driving comfort. However, as V2X communication becomes more widespread, it becomes a prime target for adversarial and persistent cyberattacks, posing significant threats to the security and privacy of CAVs. These challenges are compounded by the dynamic nature of vehicular networks and the stringent requirements for real-time data processing and decision-making. Much research is on using novel technologies such as machine learning, blockchain, and cryptography to secure V2X communications. Our survey highlights the security challenges faced by V2X communications and assesses current ML and blockchain-based solutions, revealing significant gaps and opportunities for improvement. Specifically, our survey focuses on studies integrating ML, blockchain, and multi-access edge computing (MEC) for low latency, robust, and dynamic security in V2X networks. Based on our findings, we outline a conceptual framework that synergizes ML, blockchain, and MEC to address some of the identified security challenges. This integrated framework demonstrates the potential for real-time anomaly detection, decentralized data sharing, and enhanced system scalability. The survey concludes by identifying future research directions and outlining the remaining challenges for securing V2X communications in the face of evolving threats.
Cryptocurrency, atau mata uang kripto, merupakan bentuk aset digital yang memanfaatkan teknologi kriptografi untuk mengamankan transaksi, mengontrol penciptaan unit-unit baru, serta memverifikasi transfer aset yang ada. Mata uang kripto yang pertama kali diperkenalkan adalah Bitcoin. Salah satu keunikan dari cryptocurrency, termasuk Bitcoin, adalah sifatnya yang terdesentralisasi, artinya tidak diatur oleh lembaga pusat seperti bank atau pemerintah, melainkan menggunakan teknologi blockchain. Perubahan harga Bitcoin dapat terjadi secara cepat dan drastis dalam waktu singkat, sehingga sulit diprediksi secara akurat. Untuk menangani permasalahan prediksi harga pada aset yang sangat volatil seperti Bitcoin, digunakan berbagai pendekatan algoritma pemodelan data, salah satunya adalah algoritma Long Short-Term Memory (LSTM). Berdasarkan hasil penelitian dapat disimpulkan bahwa time step harian (1 hari) menghasilkan nilai RMSE terkecil, yaitu 1823.24 atau 2.86% dari rata-rata nilai aktual.