Abstract—File storage platforms face inherent challenges such as censorship, limited transparency, vulnerability to single points of failure, and restricted user control over data. To address these limitations, this paper proposes a decentralized file-sharing system that integrates the Ethereum blockchain with the InterPlanetary File System (IPFS). Our design leverages smart contracts to securely manage file metadata and enforce access controls, providing an immutable and tamper-resistant record of data ownership and permissions. IPFS is utilized for efficient, distributed file storage, enhancing scalability and availability. User authentication is handled through wallet-based cryptographic verification, eliminating reliance on centralized identity providers. Additionally, the system supports micropayment- based monetization via smart contracts, enabling direct and transparent transactions between content creators and consumers. The proposed platform delivers a secure, censorship-resistant, and user-empowered file-sharing environment consistent with the principles of Web3. Keywords- Blockchain, IPFS, Smart Contracts,
Vitor Ayres Principe, Tiago Ribeiro, Samuel López‐Carril
The integration of blockchain technology in sports event management represents a significant shift towards more decentralized and efficient governance structures, particularly relevant to small and medium-sized events. Despite growing interest, its practical implementation remains limited and lacks comprehensive theoretical guidance. This study addresses this gap by proposing an integrated theoretical framework, combining the Dynamic Capabilities Framework (DCF), Collaborative Governance Theory (CGT), and the Four Modes of Governance (FMG), to systematically explore blockchain's application within sports event management. Our analysis reveals that blockchain technology can effectively foster transparency, efficiency, and enhanced stakeholder participation through Decentralized Autonomous Organizations (DAOs). These advantages are realized through key mechanisms of access, control, and incentives, which interact across external environments, governance structures, and blockchain core infrastructure. Furthermore, the study identifies critical managerial implications necessary for successful blockchain implementation, emphasizing strategic infrastructure assessments, stakeholder engagement, and risk management protocols. Ultimately, this research contributes both theoretical insights and practical guidelines, addressing existing knowledge gaps and providing a structured framework for leveraging blockchain in managing small to mediumsized sports events.
Web3 applications, such as on-chain games, NFT minting, and leader elections necessitate access to unbiased, unpredictable, and publicly verifiable randomness. Despite its broad use cases and huge demand, there is a notable absence of comprehensive treatments of on-chain verifiable randomness services. To bridge this, we offer an extensive formal analysis of on-chain verifiable randomness services. We present the first formalization of on-chain verifiable randomness in the blockchain setting by introducing the notion of Verifiable Randomness as a Service (VRaaS). We formally define VRaaS using an ideal functionality$\mathcal{F}\text{VRaaS}$in the Universal Composability model. Our definition not only captures the core features of randomness services, such as unbiasability, unpredictability, and public verifiability, but also accounts for many other crucial nuances pertaining to different entities involved, such as smart contracts. Within our framework we study a generic design of Verifiable Random Function (VRF)-based randomness service - where the randomness requester provides an input on which the randomness is evaluated as VRF output. We show that it does satisfy our formal VRaaS definition. Furthermore, we show that the generic protocol captures many real-world randomness services like Chainlink VRF and Supra dVRF. Moreover, we investigate the minimalism of the frame-work. Towards that, first we show that, the two transactions in-built in our framework are actually necessary for any randomness service to support the essential qualities. We also discover practical vulnerabilities in other designs such as Algorand beacon, Pyth VRF and Band VRF, captured within our framework.
Maria S. Aguiar, Elvira Albert, Samir Genaim, Pablo Gordillo · 7 authors
Context: Superoptimization is a synthesis technique that, given a loop-free sequence of instructions, searches for an equivalent sequence that is optimal wrt. an objective function. Superoptimization of Ethereum smart contracts aims at minimizing the size of their bytecode and the gas consumption of executing the contract’s functions. The search for the optimal solution poses huge computational demands –as the search space to find the optimal sequence is exponential on the given size-bound – being the main challenge for superoptimization today to scale up to real, industrial software. Even if the underlying problem for finding the optimal solution is decidable, practical tools often prioritize efficiency over completeness. This means they might be implemented to find a sub-optimal solution or even time out. Objective: This work aims at leveraging superoptimization to a real setting: Ethereum blockchain. This paper proposes a neural-guided superoptimization (NGS) approach which incorporates deep neural networks using (supervised) learning into superoptimization to improve scalability by predicting: (1) if a sequence is already optimal and hence the search can be skipped; (2) the size-bound for the optimal solution in order to reduce the search space. Method: We have downloaded over 13,000 smart contracts deployed on the blockchain for training and testing the machine learning models, and a disjoint set with 100 of the smart contracts with more transactions to prove our scalability gains and impact for the Ethereum community. Results: Incorporating DNNs resulted in a 16x overall speedup (12x for gas) with only 12% optimization loss (14% for gas), or a 3-4x speedup with no optimization loss. For the 100 analyzed contracts, this approach reduced the average compilation time to 3 min per contract and achieved monetary savings of $1.24M. Conclusions: The integration of machine learning models mitigates several limitations of traditional superoptimization by drastically reducing execution times while maintaining most of the original optimization gains.
Shlomi Dolev, Amit Hendin, Maurice Herlihy, Maria Potop Butucaru · 5 authors
The ability to perform repeated Byzantine agreement lies at the heart of important applications such as blockchain price oracles or replicated state machines. Any such protocol requires the following properties: (1) \textit{Byzantine fault-tolerance}, because not all participants can be assumed to be honest, (2) r\textit{ecurrent transient fault-tolerance}, because even honest participants may be subject to transient ``glitches'', (3) \textit{accuracy}, because the results of quantitative queries (such as price quotes) must lie within the interval of honest participants' inputs, and (4) \textit{self-stabilization}, because it is infeasible to reboot a distributed system following a fault. This paper presents the first protocol for repeated Byzantine agreement that satisfies the properties listed above. Specifically, starting in an arbitrary system configuration, our protocol establishes consistency. It preserves consistency in the face of up to $\lceil n/3 \rceil -1$ Byzantine participants {\em and} constant recurring (``noise'') transient faults, of up to $\lceil n/6 \rceil-1$ additional malicious transient faults, or even more than $\lceil n/6 \rceil-1$ (uniformly distributed) random transient faults, in each repeated Byzantine agreement.
Blockchain-based decentralised lending is a rapidly growing and evolving alternative to traditional lending, but it poses new risks. To mitigate these risks, lending protocols have integrated automated risk management tools into their smart contracts. However, the effectiveness of the latest risk management features introduced in the most recent versions of these lending protocols is understudied. To close this gap, we use a panel regression fixed effects model to empirically analyse the cross-version (v2 and v3) and cross-chain (L1 and L2) effectiveness of liquidation mechanisms, measured through TVL and total revenue as proxies for performance of the two most popular lending protocols, Aave and Compound, during the period Jan 2021 to Dec 2024. Our analysis reveals that liquidation events in v3 of both protocols lead to an increase in total value locked and total revenue, with stronger impact on the L2 blockchain compared to L1. In contrast, liquidations in v2 have an insignificant impact, which indicates that the most recent v3 protocols have better risk management than the earlier v2 protocols. We also show that L1 blockchains are the preferred choice among large investors for their robust liquidity and ecosystem depth, while L2 blockchains are more popular among retail investors for their lower fees and faster execution.
As blockchain technology continues to evolve and mature, smart contracts have become a key driving force behind the digitization and automation of transactions. Smart contracts greatly simplify and refine the traditional business transaction processes, and thus have had a profound impact on various industries such as finance and supply chain management. However, because smart contracts cannot be modified once deployed, any vulnerabilities or design flaws within the contract cannot be easily fixed, potentially leading to significant financial losses or even legal issues. The compiler, as a critical component in the development process, directly affects the quality and security of smart contracts. This paper innovatively proposes a method, known as the Improved Different Optimization Levels (IDOL), for testing the Solidity compiler. The key idea behind IDOL is to perform reverse optimization transformations (i.e., change optimized form into unoptimized form) to generate semantically equivalent variants of the smart contracts under test, aiming to maximize the opportunities to trigger the optimization logic of compilers. We conducted a preliminary evaluation of IDOL and three confirmed compiler optimization bugs have been uncovered at the time of writing.
Abstract Blockchain technology has emerged as a transformative force in the financial sector, offering decentralization, transparency, security, and cost-efficiency. Originally developed for cryptocurrencies, Blockchain now extends into banking, remittances, trade finance, and securities settlement. This study investigates Blockchain potential to revolutionize financial transactions by exploring real-world applications, implementation challenges, and stakeholder perceptions. Using a mixed-methods approach of surveys and expert interviews, the research provides empirical evidence of Blockchain benefits and limitations, contributing to the discourse on its role in reshaping financial ecosystems.
Bitcoin mining is highly energy-intensive, and improving its efficiency is critical for both economic and environmental sustainability. This project presents a web-based simulation tool that models key aspects of Bitcoin mining, including the SHA-256 hashing algorithm, nonce iteration, and target difficulty checks. The computational backend is integrated with real-time power and thermal models, enabling the simulator to reflect how hash rate influences energy consumption and temperature. Interactive controls for frequency, voltage, and resistance, along with graphical visualizations of power usage over time, allow users to explore trade-offs between energy efficiency and mining performance. The simulation also includes a financial trade-off analysis feature and supports extended runtime testing to evaluate long-term behavior under varying operational conditions.
The article examines the historical stages of the formation and development of financial control over local finances in Ukraine. The origins of financial control since the times of Kyivan Rus are investigated, the role of “Ruska Pravda” in the formation of the first legal principles of financial control is characterized. Particular attention is paid to the functioning of treasury chambers, control departments and state control bodies during the period of the Russian Empire, starting from the 18th century. The transformations of the financial control system in the conditions of imperial, Soviet and independent Ukrainian statehood are analyzed. The key regulatory legal acts that regulated financial control at different stages of history are identified – from the “Temporary Regulation on Control Institutions” (1866) to the Budget Code of Ukraine. It is proposed to define the following historical stages of the formation of financial control over local finances in Ukraine: 1) the Old Russian stage (X–XIII centuries) – primary forms of financial control, when the financial system was based on in-kind taxes and fees, and financial control was carried out through the princely administration, in particular through the “princely treasury”; 2) the pre-reform period (XIII century – until 1864) – financial control at the local level was weak, carried out through the governor’s office, the main attention was focused on collecting taxes and ensuring revenues to the empire’s budget; 3) the period of the zemstvo reform (1864–1917) – the creation of zemstvos – local self-government bodies with the right to draw up local budgets, the emergence of the first institutions of financial control at the local level; 4) the Soviet centralized stage (1918–1990) – complete centralization of finances, local budgets were integrated into the national budgets; 5) the beginning of independent financial control (1991–2000) – the formation of the legal foundations of local self-government, the emergence of a regulatory framework for local financial control, the formation of financial powers of local authorities; 6) codification and systematization of regulatory and legal acts regulating financial control (2001–2010); 7) the stage of decentralization and digital transformation (2010 – to date) – the activation of local self-government, digitalization of budget processes, the introduction of public control tools.
The decentralized finance ecosystem has fundamentally transformed traditional financial paradigms by eliminating intermediaries and enabling permissionless financial services through smart contracts deployed on blockchain networks. However, the explosive expansion has simultaneously exposed critical vulnerabilities in existing quality assurance methodologies, which were originally designed for centralized systems with predictable failure modes and controlled environments. Traditional quality assurance approaches rely heavily on static testing protocols, periodic audits, and human-mediated verification processes that prove fundamentally incompatible with the dynamic, autonomous nature of DeFi ecosystems. The inherent characteristics of DeFi platforms create a unique risk landscape that demands innovative approaches to quality assurance, particularly given the complex interconnected protocol dependencies across major DeFi applications. This article introduces a novel dynamic risk-adaptive quality assurance framework specifically engineered for DeFi platforms that transcends traditional static analysis by implementing a self-adjusting architecture capable of continuously monitoring, evaluating, and responding to emerging threats in real-time. The framework integrates artificial intelligence-driven risk prediction algorithms with behavioral analytics to create a comprehensive defense mechanism that evolves alongside the threat landscape. Through establishing dynamic risk thresholds and implementing automated response protocols, this system represents a paradigm shift toward autonomous, intelligent quality assurance in decentralized financial ecosystems, addressing critical security challenges through four interconnected layers, including data ingestion, AI-driven risk prediction, dynamic threshold management, and automated response mechanisms.
The evolution of smart cities demands scalable, secure, and energy-efficient architectures for real-time data processing. With the number of IoT devices expected to exceed 40 billion by 2030, traditional cloud-based systems are increasingly constrained by bandwidth, latency, and energy limitations. This paper leverages the ROOF (Real-time Onsite Operations Facilitation) framework with decentralized computing at intermediary fog and peripheral edge network layers to reduce latency by processing data near its point of origin. ROOF features fog caching to avoid redundancy, ultra-low-power wireless transmission for energy savings, and AI-driven resource allocation for efficiency. Security is enhanced through TLS encryption, blockchain-based authentication, and edge-level access control. Case studies from Bhubaneswar, Barcelona and Copenhagen validate the use of ROOF in traffic systems and environmental monitoring. The paper concludes by outlining key challenges and prospects of AI-driven analytics in smart urban infrastructure.
As global financial ecosystems become increasingly digitized, the need for secure, resilient, and interoperable frameworks to protect cross-border transactions and digital financial identities has grown exponentially.Traditional perimeter-based security models have proven insufficient in addressing the sophisticated cyber threats targeting financial networks, especially in decentralized and multi-jurisdictional environments.This has spurred the adoption of Zero Trust Architectures (ZTA)-a paradigm that assumes no implicit trust across networks, devices, or users-and mandates continuous verification at every interaction point.While ZTA enhances access control and minimizes attack surfaces, it faces implementation challenges in distributed financial infrastructures due to trust management, data integrity, and auditability concerns.Simultaneously, blockchain protocols-with their decentralized consensus, immutability, and cryptographic assurance-have emerged as powerful enablers of secure, transparent, and tamperresistant financial systems.This article explores the convergence of ZTA and blockchain technologies as a transformative strategy for enhancing the confidentiality, integrity, and availability of cross-border payment systems and digital identity frameworks.It examines how smart contracts, decentralized identifiers (DIDs), and distributed ledgers can reinforce ZTA principles such as least-privilege access, continuous authentication, and micro-segmentation in a decentralized context.Drawing on real-world use cases and regulatory insights, the study proposes a layered security model integrating ZTA with permissioned blockchain infrastructures, highlighting architectural synergies, potential threats, and scalability considerations.It also addresses the interoperability challenges and governance frameworks necessary for adoption in multi-stakeholder financial environments.By bridging trustless identity verification with cryptographic consensus, this integrated approach offers a future-ready blueprint for securing global digital finance in the era of open banking, fintech innovation, and evolving cyber threats.
Particularly blockchain, distributed Ledger technology (DLT) has transformed many industries; supply Chain management (SCM) is one of the fundamental benefactor. This paintings gives FARMSUPPLY, a brand new technique the use of blockchain to enhance traceability and openness in the food supply Chain (FSC). using Ethereum blockchain and smart contracts, FARMSUPPLY guarantees confirmation of important characteristics at every supply chain level-from farmer to merchant. FARMSUPPLY provides seamless preservation and retrieval of transaction data-including photos and locations-by means of immutable ledger recording and InterPlanetary file system (IPFS) integration. FARMSUPPLY solves important FSC problems via encouraging openness and traceability, therefore promoting informed decisionmaking and building confidence among the stakeholders.The FARMSUPPLY concept is thoroughly reviewed on this examine, with precise interest to its ability to transform FSC operations, raise consumer confidence, and assist the food zone to be normally green and sustainable.
Virtual currencies in general, and Bitcoin in particular, are currently the most used and famous compared to other circulated cryptocurrencies. Bitcoin is considered one of the currencies that has been fully implemented. A cryptocurrency is a decentralized peer-to-peer virtual currency. Exchange operations between users are conducted without resorting to a bank to manage the transactions. This explains one of the major advantages offered by this system: low costs or low transaction fees, which are much lower than those provided by banks in terms of modern and traditional payment methods. To ensure the validity of transactions and the dissemination of this type of money, encryption technology is used.
With the shifting from traditional grids to smart grids, there is an immense shift towards decentralized energy trading wherein “prosumers” can enter peer-to-peer transactions. This model decreases dependence on centralized utilities and maximizes efficient, flexible, and resilient energy distribution. It enhances transparency and trust by automating and securing trades via smart contracts. No intermediaries are required; hence transaction costs are low. However, an attack that would breach the security guarantees of blockchain systems-by tremendous quantum computers-might break a few of the older cryptographic methods or even reveal very significant portions of their keys. This paper introduces a blockchain-based decentralized framework for energy trading in smart grids, with a strong emphasis on post-quantum cryptography to safeguard transactions against quantum threats. We explore post-quantum cryptographic techniques, particularly lattice-based algorithms due to its compact signature sizes and strong security capability for the future-proof blockchain enabled smart grids. The proposed system model ensures secure and decentralized energy trading while incorporating off-chain signature validation to enhance computational efficiency. Unlike previous studies that primarily focus on market structure or consensus protocols, this work introduces a quantum-resilient architecture with an off-chain transaction validation mechanism, enabling high-throughput trading secured against future cryptographic vulnerabilities. The novel feature of the proposed model is the integration of off-chain post-quantum cryptographic verification into a blockchain energy trading architecture that is practically deployable on embedded hardware. Compared to existing solutions, the proposed method ensures quantum-resilient authentication while reducing gas costs by 40% and improving computational efficiency achieving a signing time of 0.327 ms and verification time of 0.127 ms. The proposed framework represents a significant step toward future-proofing blockchain-enabled smart grids while maintaining performance, transparency, and resilience. The outcome of this research work presents a quantum-safe solution that strengthens the resilience of smart grid operations and ensures the security of decentralized energy trading.
The rapid proliferation of cryptocurrencies has presented significant challenges to tax authorities and financial regulators worldwide. This study critically examines the legal, institutional, and regulatory frameworks governing cryptocurrency taxation across jurisdictions, focusing on the inconsistencies, loopholes, and enforcement difficulties that hinder effective compliance and oversight. The decentralized nature of blockchain-based financial systems, alongside the anonymity of cryptocurrency transactions, complicates traditional taxation and regulatory models. The primary objective is to identify and analyse the key regulatory challenges, evaluate legal frameworks in selected jurisdictions, and provide recommendations for policy harmonization and improved compliance mechanisms. Using a systematic literature review of 40 peer-reviewed articles from 2013 to 2024, this study synthesizes academic insights across legal, financial, and technological domains. Inclusion criteria focused on papers discussing cryptocurrency taxation, DeFi, AML, and regulatory policy analysis. The review reveals fragmented tax treatment, limited enforcement capacity, growing use of DeFi tools to evade compliance, and the lack of international regulatory alignment. Current regulatory models are outdated and jurisdiction-specific, making them ineffective against borderless crypto activity. The study recommends global regulatory harmonization, adoption of risk-based frameworks, public-private cooperation, and investment in regulatory technology and capacity building.
Abdullah A. Aljughaiman, Mosab I. Tabash, Suzan Sameer Issa, Abdulateif A. Almulhim
Most prior studies explain cross-country volatility interconnectedness without accounting for exogenous global uncertainty factors that influence equity returns. This study is the first to explore how major global uncertainty indicators such as U.S. and European financial market uncertainty indices (CBOE volatility index (VIX), VSTOXX-50), Global Financial Stress Indices (FSI) and Bitcoin Sentiment Indices (BSI) transmit shocks to the conditional volatility of Gulf Cooperation Council (GCC) stock markets. Using a novel ‘Extended Joint’ time-varying parameter vector autoregression (TVP-VAR) connectedness framework, the analysis addresses rolling-window limitations, enhances robustness to outliers, accommodates structural shifts and explains the shock transmission mechanism for the overall investment horizon. To capture transitory (short-term) and enduring (long-term) shock transmission channels from global uncertainty indicators toward the GCC financial system, a frequency-domain TVP-VAR is also employed. Furthermore, for the portfolio optimization, we also employ the hedge ratio and optimal portfolio weight strategy based on the DCC-GARCH-t copulas. Findings reveal that the conditional volatility of equity markets in Oman, Qatar, Saudi Arabia and the UAE is more sensitive to shocks from global uncertainty indicators such as VIX, VSTOXX-50 and the FSI, while Bahrain’s market shows relatively lower exposure. Kuwait’s equity market volatility exhibits the highest long-term sensitivity to FSI, VIX and VSTOXX-50, whereas the UAE demonstrates the highest sustained exposure to VIX and VSTOXX-50. Results from the DCC-GARCH-t copula model indicate that in stable periods (pre-COVID-19), optimized portfolio allocations significantly improved diversification, reducing risk by up to 83%. However, during financial stress events like COVID-19, hedge ratio strategies provided more effective risk mitigation, with reductions ranging from 3% to 43%.
S. Jagan, B. Girirajan, Manisha Bhimrao Mane, Hussana Johar R B · 6 authors
The convergence of quantum computing and artificial intelligence (AI) has introduced innovative opportunities to accelerate deep learning, particularly within decentralized cloud architectures. This study develops an adaptive quantum AI model leveraging hybrid quantum-classical algorithms to optimize deep learning processes such as training, inference, and resource allocation. The proposed model integrates Variational Quantum Circuits (VQCs) and Quantum Approximate Optimization Algorithms (QAOAs), which enable efficient handling of high-dimensional data and complex optimization tasks inherent in distributed environments. By addressing challenges like latency, energy efficiency, and computational overhead, the quantum AI model demonstrates significant performance gains in decentralized cloud systems.Experimental evaluations on benchmark datasets reveal a 40% reduction in training time, a 30% improvement in resource efficiency, and a 20% increase in prediction accuracy compared to classical deep learning frameworks. This study highlights the transformative potential of quantum computing in AI-driven decentralized cloud architectures, offering insights into its application for computationally intensive tasks across industries such as healthcare, finance, and logistics. Future work will focus on refining quantum hardware compatibility, developing quantum error correction methods, and exploring federated learning applications to expand the scope of quantum AI in privacy-preserving and distributed systems.
M Y Khan, Shaik Rehan, Mohammed Abdullah, Marwan Ali
In the rapidly evolving world of digital finance,there remains a growing need to bridge the gapbetween decentralized crypto assets and traditionalfiat currency systems. RupXpay is a robust andsecure payment application designed to meet thisdemand by enabling users to convert their cryptocurrency into Indian Rupees (INR) and alsoperform direct INR transfers through their bankaccounts. The app begins by allowing users toconnect any Web3 wallet of their choice (such asMeta Mask, Trust Wallet, etc.). Upon successfulconnection, RupXpay displays the user’s real-timewallet balance, providing full visibility andtransparency. When a user wants to convert theircrypto holdings into INR, they simply enter thedesired amount, select the block chain network,choose the crypto currency, and the preferredpayment method. To initiate the transaction, theuser must provide a digital wallet signature, whichnot only authorizes the transaction but alsotriggers a temporary wallet lock for five minutes.This lock mechanism ensures the transaction dataremains secure and unaltered during theverification process, significantly reducing the riskof fraud. The system calculates applicable gas feesbased on the selected network and applies a fixed1% fee for network processing and a 2% service feecharged by RupXpay for conversion services. Onceverified, the INR amount is credited to the user’slinked bank account. In addition to crypto-basedconversions, RupXpay supports traditional bankto-bank INR transfers. By linking their bankaccount within the app, users can send moneydirectly to other users without involving cryptocurrency, making RupXpay a complete, dual-modepayment solution. By combiningblock chain technology with traditional financialinfrastructure, RupXpay provides users with areliable, efficient, and secure platform to makecrypto spendable in everyday life. It is a futurereadyfinancial tool that redefines how digitalassets are used in the real economy.
Shakil Ahmed, Muhammad Kamran Saeed, Ashfaq Khokhar
Quantum communication is poised to become a foundational element of next-generation networking, offering transformative capabilities in security, entanglement-based connectivity, and computational offloading. However, the classical OSI model-designed for deterministic and error-tolerant systems-cannot support quantum-specific phenomena such as coherence fragility, probabilistic entanglement, and the no-cloning theorem. This paper provides a comprehensive survey and proposes an architectural redesign of the OSI model for quantum networks in the context of 7G. We introduce a Quantum-Converged OSI stack by extending the classical model with Layer 0 (Quantum Substrate) and Layer 8 (Cognitive Intent), supporting entanglement, teleportation, and semantic orchestration via LLMs and QML. Each layer is redefined to incorporate quantum mechanisms such as enhanced MAC protocols, fidelity-aware routing, and twin-based applications. This survey consolidates over 150 research works from IEEE, ACM, MDPI, arXiv, and Web of Science (2018-2025), classifying them by OSI layer, enabling technologies such as QKD, QEC, PQC, and RIS, and use cases such as satellite QKD, UAV swarms, and quantum IoT. A taxonomy of cross-layer enablers-such as hybrid quantum-classical control, metadata-driven orchestration, and blockchain-integrated quantum trust-is provided, along with simulation tools including NetSquid, QuNetSim, and QuISP. We present several domain-specific applications, including quantum healthcare telemetry, entangled vehicular networks, and satellite mesh overlays. An evaluation framework is proposed based on entropy throughput, coherence latency, and entanglement fidelity. Key future directions include programmable quantum stacks, digital twins, and AI-defined QNet agents, laying the groundwork for a scalable, intelligent, and quantum-compliant OSI framework for 7G and beyond.
We propose \textit{OpenAlpha}, a community-led strategy validation framework for decentralised capital management on a host blockchain network, which integrates game-theoretic validation, adversarial auditing, and market-based belief aggregation. This work formulates treasury deployment as a capital optimisation problem under verification costs and strategic misreporting, and operationalises it through a decision waterfall that sequences intention declaration, strategy proposal, prediction-market validation, dispute resolution, and capital allocation. Each phase of this framework's validation process embeds economic incentives to align proposer, verifier, and auditor behaviour, producing confidence scores that may feed into a capital allocation rule. While OpenAlpha is designed for capital strategy assessment, its validation mechanisms are composable and extend naturally to evaluating external decentralised applications (DApps), enabling on-chain scrutiny of DApp performance, reliability, and integration risk. This architecture allows for adaptive, trust-minimised capital deployment without reliance on centralised governance or static audits.
Kai-Yuan Chen, Kai-Hsin Chen, Jyh-Shing Roger Jang
We propose a profitable trading strategy for the cryptocurrency market based on grid trading. Starting with an analysis of the expected value of the traditional grid strategy, we show that under simple assumptions, its expected return is essentially zero. We then introduce a novel Dynamic Grid-based Trading (DGT) strategy that adapts to market conditions by dynamically resetting grid positions. Our backtesting results using minute-level data from Bitcoin and Ethereum between January 2021 and July 2024 demonstrate that the DGT strategy significantly outperforms both the traditional grid and buy-and-hold strategies in terms of internal rate of return and risk control.