Investment advisory services are now commonly offered by consulting firms with financial experts, typically for a monthly fee. Financial markets require specialized knowledge, but advancements in artificial intelligence have revolutionized this field. Deep learning algorithms, especially Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU), are widely used to predict asset price trends in nonlinear time-series data. However, they demand large datasets and are prone to overfitting. Recently, combining deep learning with reinforcement learning has shown promise, though it requires intensive research and computational resources. This study introduces the BTC-PDPR (Bitcoin Price Direction Prediction Robot) model, which predicts Bitcoin's daily price direction using the Random Forest Regressor. As an ensemble-based machine learning model, it works effectively with smaller datasets and identifies key technical indicators influencing price trends. The model achieved a 99.20% accuracy rate on data from March 2018 to the present. It runs efficiently in Google Colab (v5e1 configuration), producing results in just 22 seconds. This paper outlines the methodology, reviews relevant studies from 2017 to 2024, highlights gaps in the literature, and emphasizes the study’s contributions to the field.
Background Smart contracts are revolutionizing the way two or more parties subscribe to and apply an agreement. The main reason is that they promise to increase efficiency, transparency, and security. However, their inherent vulnerabilities can lead to automated exploits, resulting in significant resource losses. Among these, reentrancy is one of the most impactful security flaws. Over the past few years, reentrancy vulnerabilities have caused substantial financial damage and threatened the viability of entire blockchain ecosystems. Therefore, investigating whether reentrancy can be effectively mitigated and exploring the methodologies designed to address it is crucial. Methodology This paper aims to provide a comprehensive understanding of the impact of reentrancy vulnerabilities in Ethereum smart contracts and to assess the theoretical and practical approaches proposed to counter them. By following the PRISMA framework, we conduct a literature review of academic publications to identify, screen, and analyze relevant studies on detection and mitigation techniques. Results Our findings indicate that the estimated financial loss due to reentrancy attacks amounted to around 350 million USD by 2023, with increasing frequency and profitability of incidents. Despite advancements in mitigation tools, particularly machine learning, they only partially address vulnerabilities and remain ineffective against zero-day attacks. Contribution This paper identifies critical challenges in reentrancy detection, including the lack of standardized benchmarks and data on zero-day vulnerabilities. It emphasizes the need for unified datasets and evaluation frameworks to facilitate fair comparisons, improving detection effectiveness. Additionally, it highlights the need for tools addressing all four reentrancy vulnerability types and reporting performance results.
The integration of blockchain-based smart contracts technology has emerged as an innovative solution in banking. The utilization of blockchain technology and smart contracts offers great potential in improving operational efficiency and compliance with Shariah principles in Islamic banking products. Overall, blockchain-based smart contracts have the potential to overhaul the traditional way of providing Islamic banking services, by providing more efficient, transparent, and inclusive solutions. This research emphasizes the need for technological readiness and supportive policies for the successful implementation of this technology in the Islamic banking sector. This article discusses the potential use of smart contracts in strengthening automation and sharia compliance in Islamic banking products, focusing on the role smart contracts can play in increasing Islamic financial inclusion and expanding access to Islamic banking services and how prepared Islamic financial institutions are to adopt blockchain technology and smart contracts. That way, the utilization of blockchain-based smart contracts integration can be seen as better to bring significant changes in the Islamic banking sector, both in terms of increasing efficiency and in strengthening sharia principles which are the main foundation of the Islamic financial system.
Perusahaan-perusahaan terinspirasi untuk berinovasi dengan munculnya teknologi digital. Salah satu cara mereka melakukannya adalah dengan menggunakan blockchain dalam platform kontrak pintar. Berasal dari mata uang kripto, teknologi ini memungkinkan eksekusi transaksi secara otomatis menggunakan kode yang diubah menjadi bahasa hukum. Untuk lebih memahami penggunaan teknologi blockchain dalam perjanjian komersial Indonesia, penelitian ini akan melihat kontrak pintar sebagai instrumen hukum digital dan validitas teknologi blockchain dalam mendukungnya. Untuk menganalisis ketentuan hukum yang relevan, penelitian ini menggunakan metode yuridis normatif. Temuan-temuan ini menunjukkan masa depan teknologi yang menjanjikan dalam merampingkan dan mempermurah proses transaksi. Agar dapat berfungsi sebagaimana mestinya dan memberikan perlindungan hukum yang memadai, implementasinya memerlukan perubahan hukum dan penerimaan masyarakat.
Since the mid-1990s, the evolution of internet technologies has significantly transformed global connectivity and digital interaction. Today, advances in computing and networking continue to support the development of emerging paradigms such as the metaverse and digital twins—concepts that aspire to bridge physical and digital experiences. Parallel to this, blockchain technology is reshaping traditional notions of trust by enabling immutable transaction records and smart contract automation, thereby fostering the rise of decentralized autonomous organizations (DAOs). Building on these foundations, this study presents a biometric blockchain-based e-passport system designed to improve the operational efficiency of automated border control (ABC) systems. At the core of our approach is the concept of a DAO-inspired framework for border control wherein identity verification and management tasks are executed through atomic smart contracts and recorded immutably on the blockchain. Our system incorporates biometric authentication and decentralized identity features to digitize border documentation and automate verification processes. This creates a secure, verifiable digital representation of an individual’s identity that can interact with ABC workflows. Performance evaluations conducted using Hyperledger Caliper demonstrate the potential of the proposed system, showing a 3.5-fold improvement in processing efficiency compared to traditional ABC setups.
Blockchain provides the opportunity for organizations to execute trustable collaborations through smart contract automations. However, linkability problems exist in blockchain-based collaboration platforms due to privacy leakages, which, when exploited, will result in tracing transaction patterns to users and exposing collaborating organizations and parties. Some privacy-preserving mechanisms have been adopted to reduce linkability problems through the integration of access control systems to smart contracts, off-chain data storage, usage of permissioned blockchain, etc. Still, linkability problems persist in applications deployed in both private and public blockchain networks. Zero-knowledge proof (ZKP) systems provide mechanisms for verifying the correctness of transactions and actions executed on the blockchain without revealing complete information about the transaction. Hence, ZKP systems provide a potential solution to eliminating linkability problems in blockchain-based collaboration systems. The objective of this paper is to identify various linkability problems that exist in blockchain-enabled collaboration systems and understand how ZKP algorithms and smart contract frameworks can be used in addressing the linkability problems. Furthermore, a proof of concept (PoC) is implemented and simulated to demonstrate a ZKP system for a privacy-preserving feedback mechanism that mitigates linkability problems in collaboration systems. The scenario-based results from the PoC evaluation show that a feedback system that includes project participants’ verification through membership proofs, verification of on-time submission of feedback through range proofs, and encrypted calculation of feedback scores through homomorphic arithmetic provides a privacy-aware system for executing collaborations on the blockchain without linking project participants.
This research article presents a novel architecture to empower multi-agent economies by addressing two critical limitations of the emerging Agent2Agent (A2A) communication protocol: decentralized agent discoverability and agent-to-agent micropayments. By integrating distributed ledger technology (DLT), this architecture enables tamper-proof, on-chain publishing of AgentCards as smart contracts, providing secure and verifiable agent identities. The architecture further extends A2A with the x402 open standard, facilitating blockchain-agnostic, HTTP-based micropayments via the HTTP 402 status code. This enables autonomous agents to seamlessly discover, authenticate, and compensate each other across organizational boundaries. This work further presents a comprehensive technical implementation and evaluation, demonstrating the feasibility of DLT-based agent discovery and micropayments. The proposed approach lays the groundwork for secure, scalable, and economically viable multi-agent ecosystems, advancing the field of agentic AI toward trusted, autonomous economic interactions.
ABSTRACT Companies of all sizes, including Bitcoin miners, engage in charitable giving. As Bitcoin mining evolves into a substantial industry and integrates into mainstream society, it faces challenges not only from scams and environmental criticisms but also from everyday concerns such as tax compliance. One key area is the role of deductible donations, which sits at the intersection of the cryptocurrency ecosystem and the established U.S. tax system. This paper introduces an innovative approach called “hashrate contracts,” which builds upon the long-standing framework of tolling contracts. Just as tolling contracts allow producers to manage inputs and outputs efficiently while transferring operational responsibilities, hashrate contracts enable charities to assume the income associated with mining activities. This structure not only optimizes tax deductions for Bitcoin miners but allows them to claim a charitable deduction for federal income tax purposes, bridging a key gap between the cryptocurrency ecosystem and established financial and regulatory practices. JEL Classifications: K23; K29; K34.
Blockchain technology has been widely explored for enhancing transparency, traceability, and security in food supply chains. However, existing blockchain implementations rely on single distributed ledgers, causing interoperability and privacy concerns. This paper introduces FoodFresh, a novel multi-chain blockchain approach that allows food supply chain stakeholders to maintain individual blockchains while ensuring interoperability via a decentralized relay hub. The system is evaluated using real-world supply chain datasets, analyzing efficiency, transaction latency, and security improvements. Results demonstrate enhanced traceability, improved data privacy, and increased scalability. Future work includes expanding cross-chain communication protocols and exploring AI integration for predictive analytics.
The traditional content monetization system is plagued by lack of transparency, delays, and inefficiencies in royalty payments. The creators struggle to receive timely and fair compensation for their work, particularly when their content is distributed across various platforms like Spotify, YouTube, and Instagram. This research proposes a novel framework utilizing blockchain technology and smart contracts to simplify and standardize royalty distributions, ensuring they are transparent, efficient, and fair for creators across multiple platforms. We examine the technical structure of the smart contract platform, analyze its financial characteristics, and demonstrate its ability to revolutionize content monetization
Coffee is consumed worldwide, with its supply chain starting with coffee growers, who benefit least from it. Across its production, distribution, and commercialization processes, there are risks and issues that could damage the safety and authenticity of this product. Therefore, the coffee industry is looking for innovative technologies that allow traceability in the coffee supply chain. In this context, blockchain technology offers a promising solution as it supports traceability via a decentralized system that allows immutable records and transparent access; it also promotes collaborative work and removes intermediaries by generating trust between participants. This systematic literature review describes the state-of-the-art in research and development about the use of blockchain technology to improve traceability in the coffee supply chain. We also outline the open challenges that remain to be addressed in this field. We use the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) methodology to achieve this goal. Our findings suggest that the developments are mainly conceptual designs and prototypes, focusing on tracing products and verifying their authenticity using the Ethereum or Hyperledger blockchains. Also, our results show various challenges on the technology side, like efficiency improvements, integration with other technologies, infrastructure, and a lack of standards. There are also challenges at the management level, like the necessity of agreements for traceability processes, data governance, willingness to invest and pay, education, and support to deploy the technology on farms. After overcoming these open challenges, blockchain technology can improve traceability and increase value for stakeholders in the coffee supply chain.
This article presents a theoretical and methodological framework for applying a multi-agent systems (MAS) approach to modeling the budgeting processes of local hromadas. MAS-based modeling enables consideration of agents’ heterogeneity, bounded rationality, and dynamic interaction structures, which traditional models typically overlook. These features allow for a more realistic reproduction of economic processes at the hromada level. The study explores the potential of MAS in solving practical problems such as resource allocation optimization, strategic planning for sustainable development, and strengthening resilience to crises. Particular attention is paid to the development of a budget auction model based on game theory, where economic actors - including local government, enterprises, and residents - engage in a structured competition for resource distribution. The auction mechanism identifies production functions and utility values for each actor, enabling iterative optimization based on predefined efficiency criteria. A proposed simulation framework combines the auction logic with reinforcement learning methods (MARL), where agents improve their strategies through interaction and feedback. The article also outlines a multi-step algorithm for modeling decision-making and coordination processes within the decentralized budget structure. Ultimately, the approach offers tools for more transparent, participatory, and efficiency-driven public finance management. Its implementation can support the digital transformation of local governance, aligning resource distribution with sustainable development goals. The proposed methodology is particularly relevant in the context of Ukraine’s decentralization reform and post-war recovery challenges, and it may serve as a foundation for the development of intelligent public finance systems in local hromadas.
Card-based cryptography enables players to compute logical and arithmetic operations securely, such as bitwise AND and addition of integers. Several multiparty computation protocols and zero-knowledge proof protocols utilizing these secure computations have been developed as its applications. However, the realization of an efficient protocol for an arithmetic operation other than addition and subtraction remains an open problem. This paper proposes card-based protocols, based on integer commitment, for multiplication, division, and square root. Compared to general constructions for protocols for these operations based on binary integer commitment, the proposed protocols exhibit superior simplicity and efficiency. Furthermore, these protocols introduce novel applications for card-based cryptography to secure statistical data aggregation.
M. S. Sadiq, Invinder Paul Sıngh, Muhammad Makarfi Ahmad, Bashir Sanyinna Sani
Post-harvest losses represent a major challenge to global food systems, accounting for up to 30–50% of agricultural output losses, particularly in perishable crops such as fruits, vegetables, dairy, and fish. These losses significantly impact food security, farmer incomes, and national economies—most acutely in developing countries where infrastructure is limited. Cold storage technologies have emerged as one of the most effective solutions to address this issue by preserving the quality and shelf life of perishable produce. In recent years, agritech start-ups, driven by innovative youth entrepreneurs, have been at the forefront of deploying scalable and affordable cold storage solutions, ranging from solar-powered cooling units to mobile refrigeration systems and decentralized storage networks. This communication critically examines the dynamic intersection of cold storage innovations, youth entrepreneurship, and agricultural value chains. It explores the relevance of key theoretical models such as innovation diffusion theory, sustainable livelihoods framework, and supply chain integration theory to understand the adoption and impact of cold storage technologies. Through case studies and evidence from sub-Saharan Africa and South Asia, we highlight how youth-led start-ups are leveraging technology, financing, and digital platforms to bridge critical gaps in agri-logistics. Despite these promising developments, challenges persist, including high capital costs, inconsistent energy supply, inadequate technical skills, and weak policy support. As such, this study explores enabling policy frameworks, investment opportunities, and capacity-building strategies necessary for the sustainable deployment of cold storage solutions. Emphasis is placed on the transformative potential of youth-driven innovations in shaping resilient, inclusive, and climate-smart agri-food systems.
This paper develops a novel modeling framework that integrates time-varying quantile-based spillover effects into a regime-switching realized volatility model. A dynamic spillover factor is constructed by identifying the most influential contributors to Bitcoin’s realized volatility across different quantile levels. This quantile-layered structure enables the model to capture heterogeneous spillover paths under varying market conditions at a macro level while also enhancing the sensitivity of volatility regime identification via its incorporation into a time-varying transition probability (TVTP) Markov-switching mechanism at a micro level. Empirical results based on the cryptocurrency market demonstrate the superior forecasting performance of the proposed TVTP-MS-HAR model relative to standard benchmark models. The model exhibits strong capability in identifying state-dependent spillovers and capturing nonlinear market dynamics. The findings further reveal an asymmetric dual-tail amplification and time-varying interconnectedness in the spillover effects, along with a pronounced asymmetry between market capitalization and systemic importance. Compared to decomposition-based approaches, the X-RV type of models—especially when combined with the proposed quantile-driven factor—offers improved robustness and predictive accuracy in the presence of extreme market behavior. This paper offers a coherent approach that bridges phenomenon identification, source localization, and predictive mechanism construction, contributing to both the academic understanding and practical risk assessment of cryptocurrency markets.
Cryptocurrencies like Bitcoin can be considered commodities under the Commodity Exchange Act (CEA) and the Commodity Futures Trading Commission (CFTC) has jurisdiction over cryptocurrencies considered to be commodities, particularly in the context of futures trading. This paper presents a method for long and short term trend prediction of certain cryptocurrencies which is predicated on an application of the Fractal Market Hypothesis. This is an area of market theory where the self-affine properties of a fractal stochastic field are used to model a financial time series. After an introduction to the underlying theory and mathematical modelling, a fundamental analysis of Bitcoin and Ethereum to U.S. Dollar exchange markets is conducted. This analysis is based on a consideration that a changes in polarity of the 'Beta-to-Volatility' and the 'Lyapunov-to-Volatility' ratios to indicate an impending change to the Bitcoin/Ethereum price trend signal. This is used to recommend a long, a short or a hold trading position for which algorithms are provided (coded in Matlab) and 'back-tested'. An optimisation of these algorithms is conducted, leading to a strategy for implementing an ideal range of the key parameters for 'driving' the algorithms developed. This is based on maximising the accuracy and profitability to assure a high level of confidence. The application of the trading strategy developed through this approach is demonstrated to provide useful information to aid cryptocurrency investments and quantify the likelihood that the market will become bull or bear dominant. Under stable conditions, Machine Learning (using the 'TuringBot') is shown to provide useful estimates of future price values and/or fluctuations over small event horizons in time. This minimises any \lq trading delay' caused by filtering the data and increases returns by providing optimal trade positions within a \lq micro-trend' that is too fast for detection otherwise. In certain cases, this increase can reach ~10%. The results presented confirm that Bitcoin and Ethereum exchanges are self-affine (fractal) stochastic fields with L\'evy distributions, displaying a Hurst Exponent of ~ 0.32, a Fractal Dimension of ~ 1.68 and Levy Index of ~1.22. They also confirm that the Fractal Market Hypothesis and its indices provide a suitable market model, that generates returns on investments that outperform all Buy and Hold strategies based on more standard market indices.
Andre Salem Alego, Renata Dellamatriz, Victor Dário, Edson Primo · 9 authors
The tokenization of fixed-income assets is reshaping capital markets by enabling programmable, transparent, and efficient digital representations of real-world value, and presents transformative opportunities but is significantly hindered by the pervasive issue of insecure platforms. Current solutions often lack robust security frameworks, leaving digital assets vulnerable to breaches and undermining investor confidence in both primary and secondary markets for instruments like debentures. This paper introduces CRX, a novel platform meticulously engineered to address these critical security deficiencies, offering a paradigm shift in the tokenization of fixed-income assets. CRX is built upon a foundational Zero Trust segmentation model, ensuring that every transaction and interaction is continuously verified and authorized, regardless of its origin. This core security principle is intrinsically linked to an AI-first architecture, leveraging multi-agent systems for continuous security and observability, proactively identifying and neutralizing threats. Designed to be agnostic and interoperable, CRX seamlessly connects with over 15 integrated public and permissioned blockchains, providing unparalleled flexibility. Its modular, pluggable (composability) architecture ensures adaptability and scalability, making CRX ready for both local and global markets. By prioritizing security as a fundamental design element, CRX delivers a resilient, efficient, and trustworthy infrastructure for tokenized fixedincome in the era of decentralized finance (DeFi).
The decentralization of international payments is emerging as a transformative trend in the global financial system, driven by blockchain technology, decentralized finance (DeFi), cryptocurrencies, and central bank digital currencies (CBDCs). This paper explores the shift from traditional, centralized payment infrastructures toward decentralized alternatives, assessing their impact on transaction efficiency, cost reduction, financial inclusion, and financial stability. A special focus is placed on the evolving role of the Society for Worldwide Interbank Financial Telecommunication (SWIFT), historically the backbone of international cross-border payments. Through a combination of theoretical review and empirical time series analysis based on SWIFT message data from 2014 to 2022, the study evaluates SWIFT’s resilience and adaptation in the face of decentralization pressures. The findings reveal a permanent upward trend in SWIFT traffic, coupled with seasonal fluctuations, suggesting that while decentralization is expanding, SWIFT remains a central actor by innovating its infrastructure. The study also discusses the regulatory challenges posed by decentralized systems and the need for balanced frameworks to foster innovation while safeguarding stability. This research concludes that international payments, where traditional and decentralized models seem to coexist.
Assume that, given a sequence of n integers from 1 to n arranged in random order, we want to sort them, provided that the only acceptable operation is a prefix reversal, which means to take any number of integers (sub-sequence) from the left of the sequence, reverse the order of the sub-sequence, and return them to the original sequence. This problem is called “pancake sorting,” and sorting an arbitrary sequence with the minimum number of operations restricted in this way is known to be NP-hard. In this paper, we consider applying the concept of zero-knowledge proofs to the pancake sorting problem. That is, we design card-based zero-knowledge proof protocols in which a user (the prover) who knows how to sort a given sequence with ℓ operations can convince another user (the verifier) that the prover knows this information without divulging it.
The modular inverse is an essential piece of computation required for elliptic curve operations used for digital signatures in Bitcoin and other applications. A novel approach to the extended Euclidean algorithm has been developed by Bernstein and Yang within the last few years and incorporated into the libsecp256k1 cryptographic library used by Bitcoin. However, novel algorithms introduce new risks of errors. To address this we have completed a computer verified proof of the correctness of (one of) libsecp256k1's modular inverse implementations with the Coq proof assistant using the Verifiable C's implementation of separation logic.
Global health emergencies, such as the COVID-19 pandemic, have exposed critical weaknesses in traditional medical supply chains, including inefficiencies in resource allocation, lack of transparency, and poor adaptability to dynamic disruptions. This paper presents a novel hybrid framework that integrates blockchain technology with a decentralized, large language model (LLM) powered multi-agent negotiation system to enhance the resilience and accountability of medical supply chains during crises. In this system, autonomous agents-representing manufacturers, distributors, and healthcare institutions-engage in structured, context-aware negotiation and decision-making processes facilitated by LLMs, enabling rapid and ethical allocation of scarce medical resources. The off-chain agent layer supports adaptive reasoning and local decision-making, while the on-chain blockchain layer ensures immutable, transparent, and auditable enforcement of decisions via smart contracts. The framework also incorporates a formal cross-layer communication protocol to bridge decentralized negotiation with institutional enforcement. A simulation environment emulating pandemic scenarios evaluates the system's performance, demonstrating improvements in negotiation efficiency, fairness of allocation, supply chain responsiveness, and auditability. This research contributes an innovative approach that synergizes blockchain trust guarantees with the adaptive intelligence of LLM-driven agents, providing a robust and scalable solution for critical supply chain coordination under uncertainty.
The financial world is at the crossroads, and digital monies, decentralized privacy, and asset tokens recreate centuries-old constructs. Blockchain options are challenging conventional clearing houses as never before, by operating outside of the set parameters. This article examines the complex interaction of old-world clearing systems with new-fangled, crypto settlement mechanisms, deconstructs prickly issues and precious opportunities facing Central Counterparty Clearing Houses. The cryptocurrency environment has developed different settlement methods, but advanced investors are eager to have safe and regulated access to digital assets. Its essence is that blockchain promises to render bypassing middlemen through direct transactions a reality, but, in the meantime, it poses a threat to current systems and presents a new way to envision clearing. This article shows how new clearing corporations can help solve the problem of finance, and even support better market performance and transparency along with stability alongside key protections because innovative hybrid enterprise models can actually become a bridge between old-fashioned finance and digital networks and even increase their reliability, integrity, and stability in the long-term future.
Ovaj završni rad bavi se analizom utjecaja regulatornih okvira na tržište kriptovaluta, pri čemu se posebna pozornost posvećuje razlikama u zakonodavnim pristupima pojedinih država i nadnacionalnih tijela. U fokusu rada su Europska unija, Sjedinjene Američke Države, Kina te druge značajne jurisdikcije koje kroz različite modele regulacije pokušavaju odgovoriti na izazove koje donosi brzo rastuće i tehnološki kompleksno kriptotržište. Istraživanje je provedeno kroz pregled relevantne literature, analizu zakonodavnih dokumenata i komparativnu analizu pravnih okvira, a rezultati upućuju na niz ključnih problema s kojima se regulatori suočavaju. Među njima se ističu pravna nesigurnost, nedovoljna zaštita potrošača, visoki rizik od zloupotrebe u svrhu financijskog kriminala, te fragmentiranost regulacije na međunarodnoj razini. Posebna se pažnja pridaje europskoj regulativi MiCA (Markets in Crypto-Assets), koja predstavlja prvi pokušaj stvaranja sveobuhvatnog zakonodavnog okvira za kriptoimovinu unutar Europske unije. Također se razmatra uloga samoregulacije i potreba za ravnotežom između podrške inovacijama i osiguravanja stabilnosti financijskog sustava. Na temelju analize, rad nudi preporuke za daljnji razvoj regulatorne politike u području kriptovaluta, s naglaskom na važnost usklađivanja zakonodavnih rješenja, institucionalne suradnje i prilagodljivosti pravnog okvira u skladu s dinamičnim razvojem tehnologije. Zaključno, ističe se važnost izgradnje dosljednog, transparentnog i učinkovitog sustava regulacije, osobito u kontekstu Europske unije i Republike Hrvatske.