Blockchain is a decentralized, distributed ledger technology that ensures transparency, security, and immutability through cryptographic techniques. However, advancements in quantum computing threaten the security of classical cryptographic schemes, jeopardizing blockchain integrity once cryptographic quantum supremacy is achieved. This milestone, defined here as the realization of quantum computers to solve practical cryptographic problems, would render existing security standards vulnerable, exposing blockchain assets (currency, data, etc.) to fraud and theft. To address this risk, we propose and implement a smart contract deployable on the Ethereum blockchain, having the ability to run applications on its blockchain, that generates classically intractable puzzles by probabilistically generating large, hard-to-factor numbers without requiring secret information. This contract then serves two purposes: to establish a mechanism (1) for a trustless, unbiased proof of cryptographic quantum supremacy by verifying solutions to these puzzles, and (2) to protect user funds on Ethereum by triggering quantum-secure fallback protocols upon detecting cryptographic quantum supremacy, since it is desirable to wait as long as possible to fall back to a quantum-secure scheme because of its inherent additional cost and complexity. These mechanisms demonstrate the ability to identify cryptographic vulnerabilities and ensure a smooth transition to quantum-secure standards, safeguarding blockchain assets in a post-quantum era.
This paper investigates the strategic behavior of validators in blockchain systems utilizing the Proof-of-Stake (PoS) consensus mechanism through the application of game theory. A mathematical model of a non-cooperative game with complete information is proposed, where validators act as rational agents aiming to maximize their expected payoff by choosing between honest validation and malicious actions, specifically a double-spending attack. The model incorporates key economic parameters of the system: block and attestation rewards, transaction fees, operational costs, slashing penalties, and the probability of detecting protocol violations. Utility functions for two primary strategies – honest and attacking – are formalized, and conditions for the existence of Nash equilibrium, the central solution concept in game theory, are analyzed.
The analysis demonstrates that under effective punishment mechanisms, the "all-honest" equilibrium is stable: an individual validator has no incentive to deviate from protocol-compliant behavior, as potential losses from penalties significantly outweigh any gains from a failed attack. Conversely, the "all-attackers" equilibrium, while theoretically possible, is practically unattainable due to the prohibitively high cost of acquiring a majority stake, rendering such a strategy economically infeasible. A quantitative example based on a hypothetical network of 1000 validators confirms these findings and highlights the critical importance of balancing incentives for honest behavior with strong disincentives for malicious actions.
The study emphasizes the crucial role of economic security in PoS systems, where stability is ensured not only by technical safeguards but also by carefully designed economic mechanisms. The developed model can be used by blockchain protocol designers to calibrate consensus parameters, thereby promoting decentralization, resilience, and long-term network reliability. Future research can extend the model by incorporating heterogeneous validators, repeated games, and the analysis of other attack vectors.
Abstract The secure and efficient sharing of geographic spatial data is crucial for applications in urban planning, disaster management, and environmental monitoring. However, conventional access control systems face scalability, security, and transparency problems in a distributed environment. This paper proposes a new framework that marries attribute-based access control with blockchain technology and smart contracts for fine-grained, decentralized, and tamper-proof data sharing. This paper introduces a new framework which combines Attribute-Based Access Control (ABAC), blockchain technology, smart contracts, and an upgraded Black-winged Kite (UBK) algorithm. Access regulations and audit logs are stored on a private blockchain using a Proof-of-Authority consensus mechanism for immutability and transparency. Experimental results show that the proposed method reduces evaluation policy time by 70% and storage overhead by 52% compared to the traditional attribute-based access control, while achieving 98.2% accuracy in access decisions. The performance test shows evaluation time and storage increase linearly, thus proving appropriate large-scale deployment. The combination of blockchain and smart contracts guarantees security-auditable and automated enforcement of access policies without needing a central authority.
Yu-Pin Lin, Joy R. Petway, Johnathen Anthony
et al.
Blockchain technology, while still challenged with key limitations, is a transformative Information and Communications Technology (ICT) that has changed our notion of trust. Improved efficiencies for agricultural sustainable development has been demonstrated when ICT-enabled farms have access to knowledge banks and other digital resources. UN FAO-recommended ICT e-agricultural infrastructure components are a confluence of ICT and blockchain technology requirements. When ICT e-agricultural systems with blockchain infrastructure are immutable and distributed ledger systems for record management, baseline agricultural environmental data integrity is safeguarded for those who participate in transparent data management. This paper reviewed blockchain-based concepts associated with ICT-based technology. Moreover, a model ICT e-agriculture system with a blockchain infrastructure is proposed for use at the local and regional scale. To determine context specific technical and social requirements of blockchain technology for ICT e-agriculture systems, an evaluation tool is presented. The proposed system and tool can be evaluated and applied to further developments of e-agriculture systems.
Quantum blockchains provide inherent resilience against quantum adversaries and represent a promising alternative to classical blockchain systems in the quantum era. However, existing quantum blockchain architectures largely depend on entanglement to maintain inter-block connections, facing challenges in stability, consensus efficiency, and system verification. To address these issues, this work proposes a novel quantum blockchain framework based on quantum walks, which reduces reliance on entanglement while improving stability and connection efficiency. We further propose a quantum consensus mechanism based on a weighted quantum voting protocol, which enables a fairer voting process while reflecting the weights of different nodes. To validate the proposed framework, we conduct circuit simulations to evaluate the correctness and effectiveness of both the quantum walk-based block construction and the quantum voting consensus mechanism. Compared with existing entanglement-dependent approaches, our framework achieves stronger stability and enables simpler verification of block integrity, making it a practical candidate for quantum-era blockchain applications.
Eranga Bandara, Sachin Shetty, Ravi Mukkamala
et al.
In recent years, blockchain has experienced widespread adoption across various industries, becoming integral to numerous enterprise applications. Concurrently, the rise of generative AI and LLMs has transformed human-computer interactions, offering advanced capabilities in understanding and generating human-like text. The introduction of the MCP has further enhanced AI integration by standardizing communication between AI systems and external data sources. Despite these advancements, there is still no standardized method for seamlessly integrating LLM applications and blockchain. To address this concern, we propose "MCC: Model Context Contracts" a novel framework that enables LLMs to interact directly with blockchain smart contracts through MCP-like protocol. This integration allows AI agents to invoke blockchain smart contracts, facilitating more dynamic and context-aware interactions between users and blockchain networks. Essentially, it empowers users to interact with blockchain systems and perform transactions using queries in natural language. Within this proposed architecture, blockchain smart contracts can function as intelligent agents capable of recognizing user input in natural language and executing the corresponding transactions. To ensure that the LLM accurately interprets natural language inputs and maps them to the appropriate MCP functions, the LLM was fine-tuned using a custom dataset comprising user inputs paired with their corresponding MCP server functions. This fine-tuning process significantly improved the platform's performance and accuracy. To validate the effectiveness of MCC, we have developed an end-to-end prototype implemented on the Rahasak blockchain with the fine-tuned Llama-4 LLM. To the best of our knowledge, this research represents the first approach to using the concept of Model Context Protocol to integrate LLMs with blockchain.
Mohammad H. Amin, Jack Raymond, Daniel Kinn
et al.
We propose a blockchain architecture in which mining requires a quantum computer. The consensus mechanism is based on proof of quantum work, a quantum-enhanced alternative to traditional proof of work that leverages quantum supremacy to make mining intractable for classical computers. We have refined the blockchain framework to incorporate the probabilistic nature of quantum mechanics, ensuring stability against sampling errors and hardware inaccuracies. To validate our approach, we implemented a prototype blockchain on four D-Wave(TM) quantum annealing processors geographically distributed within North America, demonstrating stable operation across hundreds of thousands of quantum hashing operations. Our experimental protocol follows the same approach used in the recent demonstration of quantum supremacy [King et al. Science 2025], ensuring that classical computers cannot efficiently perform the same computation task. By replacing classical machines with quantum systems for mining, it is possible to significantly reduce the energy consumption and environmental impact traditionally associated with blockchain mining while providing a quantum-safe layer of security. Beyond serving as a proof of concept for a meaningful application of quantum computing, this work highlights the potential for other near-term quantum computing applications using existing technology.
The present dissertation addresses the problem of fairly distributing shared resources in non-commercial blockchain networks. Blockchains are distributed systems that order and timestamp records of a given network of users, in a public, cryptographically secure, and consensual way. The records, which may in kind be events, transaction orders, sets of rules for structured transactions etc. are placed within well-defined datastructures called blocks, and they are linked to each other by the virtue of cryptographic pointers, in a total ordering which represents their temporal relations of succession. The ability to operate on the blockchain, and/or to contribute a record to the content of a block are shared resources of the blockchain systems. In commercial networks, these resources are exchanged in return for fiat money, and consequently, fairness is not a relevant problem in terms of computer engineering. In non-commercial networks, however, monetary solutions are not available, by definition. The present non-commercial blockchain networks employ trivial distribution mechanisms called faucets, which offer fixed amounts of free tokens (called cryptocurrencies) specific to the given network. This mechanism, although simple and efficient, is prone to denial of service (DoS) attacks and cannot address the fairness problem. In the present dissertation, the faucet mechanism is adapted for fair distribution, in line with Max-min Fairness scheme. In total, we contributed 6 distinct Max-min Fair algorithms as efficient blockchain faucets. The algorithms we contribute are resistant to DoS attacks, low-cost in terms of blockchain computation economics, and they also allow for different user weighting policies.
Background: Alzheimer’s disease (AD) is a neurodegenerative disease which significantly and negatively affects families and society. Aerobic exercise serves as a non-pharmacological strategy, potentially safeguarding against cognitive decline and lowering the risk of AD. However, how aerobic exercise ameliorates AD remains unknown. This study investigated the effects of two types of aerobic exercise, including aerobic interval training (AIT) and aerobic continuous training (ACT), on cognitive and exploratory function, brain histopathology, and hepatic amyloid beta (Aβ) clearance in amyloid precursor protein/presenilin-1 double transgenic (APP/PS1) transgenic mice. Methods: Twenty-four six-month-old male APP/PS1 transgenic mice (body weight: 20–22 g) were used to establish the AD model. APP/PS1 transgenic mice were randomly assigned to one of the three groups: rest (AD group, n = 8), aerobic interval training (AIT group, n = 8), and aerobic continuous training (ACT group, n = 8). The exploration ability and anxiety of AD mice were measured using the open-field test. Learning and memory of AD mice were detected using the novel object recognition test, Y-maze test, and Morris water maze test. Neuronal damage was analyzed using hematoxylin and eosin staining and Nissl staining. Aβ deposition in the brain was detected using a thioflavin-S fluorescence assay and immunofluorescence. The mechanisms underlying hepatic Aβ clearance were investigated using an immunofluorescence assay and western blotting. Data were analyzed using one-way ANOVA with Tukey’s post hoc test, and p < 0.05 was deemed statistically significant. Results: The results revealed that both AIT and ACT improved the recognition memory and exploration ability of mice after 8 weeks of intervention. Additionally, both forms of aerobic exercise significantly mitigated neuronal damage and Aβ deposition in the brain and improved the hepatic clearance of Aβ. Conclusions: Our findings indicated that AIT and ACT can improve cognitive deficits in APP/PS1 mice, potentially by increasing the hepatic phagocytic capacity of Aβ. Hepatic clearance of Aβ may serve as a supplementary mechanism by which aerobic exercise can improve AD.
Blockchain is the technology which greatly attracted the industries as well as the academics of the educational system because of its variety of applications and innovations around the globe. Smart contract is one of the most highly used technological move in the blockchain technology which increased its attention among the researchers. A smart contract has been embedded in the blockchain as an agreement that does not need any third-party intervention and executes automatically to perform different sophisticated tasks. Significant research has been done in the area of smart contract in blockchain in recent years. The smart contract has its impact in many industrial applications like supply chain management, digital identity, IOT, business processes etc. This paper aims to review the recent work that has been done in the area of smart contracts in different domains. We will present a comparative study of smart contract platforms, languages and applications under different categories like security, management, social application needs, etc.
Teodora Maria Suciu, Nicoleta Verejan, Adela Socol
et al.
The accelerated development of digital technologies and cryptocurrencies in latest years has been accompanied by an exponential raise in related scientific literature. This study conducts a bibliometric analysis based on the VOSviewer software for documents indexed in the Web of Science Core Collection from 2015-2024, focusing on the evolution of research topics in the field of cryptocurrencies. The analysis employs co-occurrence mapping of the main research topics related to cryptocurrencies. The results highlight a high degree of thematic diversification, organized into five major clusters with the following directions: cryptocurrency markets and financial performance, digital assets and technological foundations, blockchain infrastructure and governance, emerging applications and risks, general cryptocurrency concepts and operational aspects. This research contributes to the knowledge by offering a comprehensive and structured overview of cryptocurrency-related literature streams, providing valuable insights for scholars, policymakers and industry stakeholders seeking to understand the trajectory and future potential of cryptocurrency-related research.
Igors Kukjans, Inguna Jurgelane-Kaldava, Maris Juruss
The transport sector significantly contributes to environmental degradation, with road transport responsible for approximately 70 % of the sector’s greenhouse gas emissions, which is only one of several externalities generated by transport. The transboundary nature of international mobility further complicates national emissions inventories and accountability mechanisms. Policies based on the polluter-pays principle, such as carbon taxes and cap-and-trade systems, aim to mitigate these impacts but are hindered by inconsistent metrics and reporting. This study proposes a novel taxation framework for transport-related externalities, addressing how comprehensive sustainability reporting, supported by standardised metrics and transparent tracking, incentivises sustainable practices and enhances transport sustainability. The methodology comprises three phases: (1) a scoping review of transport externalities, mitigation strategies, and polluter-pays taxation; (2) development of a blockchain-based platform to transparently track transport-related pollution and mitigation actions across the entire supply chain using unified Environmental Impact Units (EIU). Companies can register fleets, fuels, and routes on the platform, which allocates pollution costs and issues blockchain-stored EIU certificates for transparent reporting; and (3) focus group discussions to evaluate stakeholder perceptions of the platform against the tax policy criteria of the American Institute of Certified Public Accountants (AICPA, 2017). Despite strong stakeholder support for fairness and transparency, challenges in data standardisation and scalability persist, particularly in less developed regions. This research introduces a blockchain-based platform where transportation companies can register their fleets, record the types of fuel used, and specify their routes. Based on the initial phase of the research, in which transport-related pollution is allocated across different stages of the supply chain, the platform will calculate the associated pollution levels based on the companies' inputs. The platform will then allocate the costs for pollution mitigation measures and issue a digital certificate for a Unified Environmental Impact Unit, reflecting the environmental impact of the company’s operations. This certificate will be stored on the blockchain, providing a verifiable, transparent record that can be used by any supply chain for transparent reporting and auditing purposes.
Public blockchain networks using proof of work (PoW)-based consensus protocols are considered as a promising platform for decentralized resource management with financial incentive mechanisms. In order to maintain a secured, universal state of the blockchain, PoW-based consensus protocols financially incentivize the nodes in the network to compete for the privilege of block generation through cryptographic puzzle solving. For rational consensus nodes, i.e., miners with limited local computational resources, offloading the computation load for PoW to the cloud/fog providers (CFPs) becomes a viable option. In this paper, we study the interaction between the CFPs and the miners in a PoW-based blockchain network using a game theoretic approach. In particular, we propose a lightweight infrastructure of the PoW-based blockchains, where the computation-intensive part of the consensus process is offloaded to the cloud/fog. We formulate the computation resource management in the blockchain consensus process as a two-stage Stackelberg game, where the profit of the CFP and the utilities of the individual miners are jointly optimized. In the first stage of the game, the CFP sets the price of offered computing resource. In the second stage, the miners decide on the amount of service to purchase accordingly. We apply backward induction to analyze the subgame perfect equilibria in each stage for both uniform and discriminatory pricing schemes. For uniform pricing where the same price applies to all miners, the uniqueness of the Stackelberg equilibrium is validated by identifying the best response strategies of the miners. For discriminatory pricing where the different prices are applied, the uniqueness of the Stackelberg equilibrium is proved by capitalizing on the variational inequality theory. Further, the real experimental results are employed to justify our proposed model.