The objectives of this paper are to provide a methodology for applying the DeTEcT framework to modelling token economies, to formalise the configuration of the simulation environment, and to introduce an event analysis framework. A token economy is an economic system that has a unique mechanism for controlling its monetary supply, and a medium, in the form of a token or currency, for the valuation of goods and services, the settlement of transactions, and the storage of value. We show the key decisions that must be made when modelling an economy with the DeTEcT framework and showcase some numerical methods that can be used in conjunction with the framework to perform economic simulations. We also propose a framework for analysing and measuring the impacts of events on an economy, while also developing a procedure to measure the significance of these impacts. Throughout the paper, we use Bitcoin as a case study to demonstrate how to apply the frameworks and tools we proposed here. We show how a model of Bitcoin token economy can be set up, and how to measure the impacts of Bitcoin's endogenous policies (i.e., BIPs) on the wealth distribution of its economic participants.
Based on asymmetric cryptography, Passkeys Systems are a secure authentication method that can serve as an alternative to traditional authentication methods, such as usernames and passwords. In this paper, we propose a secure approach to enhance private key synchronization mechanisms in passkeys systems. Our secure service is based on Elliptic Curve Diffie-Hellman protocol and Zero-Knowledge Proofs in a peer-to-peer environment. Following a critical analysis of existing works, which highlights recurrent vulnerabilities related to authentication and confidentiality, we introduce a robust architecture using mutual identity verification, secure session key generation and encrypted passkey transfer. The security of our proposed protocol is assessed through a dual approach: an informal analysis based on potential attack modeling, and a formal validation using ProVerif and Scyther tools. The results demonstrate enhanced resistance to replay attacks, man-in-the-middle attacks, message modification, and identity impersonation, while ensuring optimized performance in terms of computational and communication costs.
Prescriptive maintenance (PsM) recommends concrete interventions from asset condition and operational constraints, increasingly relying on digital twins (DTs). In multi-stakeholder industrial settings, however, twin states, prognostic models, prescriptions, and execution outcomes are rarely linked by a verifiable audit trail. This paper presents ChainTwin-PsM, a compact conceptual framework for blockchain-anchored digital twin traceability that supports auditable PsM decisions. We define a minimal set of Traceable Twin Events (TTEs) spanning twin instantiation, state commitment, model registration, prediction, prescription, and execution feedback, together with hybrid on-chain/off-chain anchoring principles. A lightweight proof-of-concept simulates a multi-asset fleet with limited maintenance capacity and conflicting operator-service-provider incentives. It demonstrates that blockchain-backed service-level commitments can lower system cost and risk relative to weakly enforced coordination. The work is intentionally scoped as a framework-plus-PoC contribution rather than a state-of-the-art prognostics study, and keeps a C-MAPSS-compatible health interface for a subsequent data-driven extension.
On June 22, 2026, the White House issued Executive Order 14413, directing the federal government to accelerate the deployment of quantum computing and to assess "the implications for the migration to post-quantum cryptography." The order is the latest and loudest signal of a fact the legal system has not yet absorbed: the cryptographic assumptions behind nearly all digital proof carry an expiration date. Every electronic signature, every encrypted database, and every blockchain transaction rests on math that a sufficiently powerful quantum computer can break. When that computer arrives, adversaries will be able to forge the signatures and decrypt the records on which courts, regulators, and markets now rely. Data stolen today is already being warehoused for decryption tomorrow. Signatures trusted today may be forgeable tomorrow. This Article argues that the quantum transition forces the law to confront a distinction it has long been able to ignore: the difference between probabilistic verification (an intermediary's opinion, an AI confidence score, an auditor's judgment) and deterministic verification (a mathematical result that anyone can independently reproduce). Across digital identity, financial services, insurance, defense, supply chains, and digital assets, organizations prove claims through intermediaries whose honesty cannot be checked and whose methods cannot be reproduced. A small set of well-understood cryptographic tools can replace that fragmented apparatus: hardware-secured signing keys, Merkle tree timestamping, post-quantum signature standards, and zero-knowledge proofs. Together they produce verification that is reproducible, tamper-evident, and quantum-resistant from the outset. The Article makes three contributions. First, it reframes the âverification gapâ as a legal problem rather than a technical one, showing how the Federal Rules of Evidence, the Daubert reliability standard, data breach liability doctrine, and fiduciary oversight duties each already point toward deterministic proof. Second, it shows that quantum risk is collapsing the legal defenses built on classical cryptography, most visibly the âit was encryptedâ defense in breach litigation, while creating new disclosure and diligence obligations for boards. Third, it maps deterministic verification onto concrete applications in six sectors and proposes a regulatory framework, including a âdeterministic assurance levelâ for evidentiary purposes and a public governance process for the rule schemas that translate law into machine-checkable criteria.
Authentication is becoming essential due to the expansion of the Internet of Things (IoT) applications in smart cities, supply chain, and healthcare. In the healthcare sector, hospitals use centralized server-based systems to manage user information and patient medical records. However, this approach may lead to scalability, interoperability, security and privacy challenges. To address these issues, this paper presents a blockchain-based multi-factor authentication (MFA) framework for IoT healthcare systems. The framework uses the Ethereum blockchain and smart contracts to improve authentication security and minimize unauthorized access risk. It also uses the InterPlanetary File System (IPFS) to securely and efficiently store sensitive medical data. Performance and security are evaluated to show the effectiveness, reliability, and feasibility of the proposed system.
Flexible demand is increasingly important in energy systems with high renewable penetration. Bitcoin mining is often cited as a large, theoretically flexible load. Despite electricity consumption rivaling medium-sized industrial economies, the energy market behavior and impacts of Bitcoin miners remain largely unexplored. We exploit the large-scale relocation of Bitcoin mining to Texas, which became the world's largest mining hub following China's 2021 ban, to estimate its effects on local wholesale electricity prices. Combining a novel, hand-collected dataset on mining facility locations with high-frequency wholesale price data, we identify price impacts using a DiD design. We find that miners select into renewable-rich, high-GDP per capita counties with initially lower electricity prices on average. Mining entry has no significant effect on daytime prices but increases nighttime prices by 19.9%, indicating that Bitcoin miners fail to exploit their operational flexibility. Instead they increase baseload demand and reinforce fossil generation during low-renewable periods.
Saha Reno, Mohammad Jishan Ahmad Shipu, Sumaiya Hussain Tanha, Mohammad Molla Habib
ABSTRACT Securing satellite data transactions is critical as satellite communication supports global connectivity, navigation, earth observation and aviation. Sensitive interâsatellite data requires robust protection, and aircraftâground station links must prevent hazards. Vulnerabilities could breach security protocols, compromising confidentiality and incurring legal consequences. This paper presents the first integration of proofâofâauthority (PoA) consensus, ERC1155 multiâtoken standard and threshold cryptography for satellite data transactions. Unlike prior blockchainâbased proposals that rely on singleâkey encryption or energyâintensive proofâofâwork (PoW), our system (i) uses ERC1155 to batch different data types in one contract (reducing gas costs by 40%), (ii) distributes private keys via Shamir's secret sharing (kâofân) to eliminate single points of failure and (iii) implements dynamic share rotation during orbital handovers (98% success). Simulations show 12.5 ms average latency, 50 messages/second throughput and 40% lower gas costs versus PoW systems (0.0006 ETH/message). Threshold cryptography increases cracking complexity to operations, while PoA, under our simulation assumptions, achieves 100% detection of manâinâtheâmiddle attacks and 0% success for reentrancy/Sybil attacks. Dynamic share recovery during orbital handovers attains 98% success, outperforming traditional methods in resilience and efficiency.
We develop a model of aberrant behavior by Bitcoin miners and test it with a new 2017-2025 dataset.Miners' rewards, comprised partly of user fees, exhibit variability across blocks of transactions.When large reward disparities exist between adjacent blocks, miners have incentives to attempt alternative versions of prior blocks and claim other miners' rewards for themselves.Regression analysis shows that fee differentials are associated with these attacks and longer waiting times between blocks.These patterns imply potential destabilization of the Bitcoin blockchain as future mining rewards become more volatile due to gradual withdrawal of fixed block subsidies.
This paper studies the benefits of timing Bitcoin returns by upside and downside volatilities. Standard volatility management implicitly treats volatility spikes as signals of adverse states, reducing exposure when total volatility increases. However, in Bitcoin, volatility spikes are frequently due to price rallies, which typically indicate subsequent positive returns. We show that semivolatility timing rules that account for both downside and upside risk concerns yield substantially stronger risk-adjusted performance than buy-and-hold and volatility-managed strategies. This stems from the fact that high upside-driven volatility states in Bitcoin are disproportionately associated with positive returns in the next period.
Abstract Four independent fieldsâphysics, biology, economics, and cultural evolutionâhave converged on the same mathematical machinery for describing persistence-conditioned dynamics. The convergence is not metaphorical but literal: the same fitness landscapes, selection operators, and transmission kernels appear independently. We synthesize these into the Replicator-Optimization Mechanism (ROM): a unified apparatus instantiable at any scale. Key Contributions Cross-field synthesis: Physics, biology, economics, and cultural evolution share identical formal structure Political application: ROM instantiated with friction from stake-voice mismatch as primitive, legitimacy as survival probability Machine-checked proofs: Core algebraic results verified in Lean 4 with Mathlib (28 theorems, zero sorry placeholders) Key results: Simplex preservation, survival monotonicity, moving equilibrium existence, impossibility of static equilibrium under varying friction Links arXiv: arXiv:2601.06363 Lean 4 proofs: github.com/studiofarzulla/lean-formalizations ASCRI: systems.ac/4/DAI-2503 Research Lab: Dissensus AI
Smart transportation networks have the potential to significantly improve traffic flow. The Internet of Vehicles (IoV) serves as a vital component of such networks, enabling real-time connectivity and coordination among vehicles and infrastructure. The expansion of IoV-based communication and the increasing volume of data transferred across the IoV make it necessary to implement effective techniques for preserving privacy and ensuring information security. Nonetheless, traditional data-security models have notable drawbacks, primarily high computational costs. In our pseudonymous authentication framework, each vehicle first generates a publicâprivate key pair using a multidimensional lattice-based (Nth-degree truncated polynomial ring units) method. A vehicle then digitally signs its own identity with its private key and sends an authentication request to the roadside unit (RSU); the RSU then verifies that signature using the public key of the corresponding vehicle. After verification, the vehicle and RSU execute a secure ephemeral-key agreement using ephemeral supersingular isogeny DiffieâHellman to establish a shared session key. The complete authentication and session-key-agreement process is securely signed and documented on the blockchain using a lightweight enhanced delegated proof-of-stake consensus methodology to efficiently confirm the transaction and add it to the blockchain. The experimental findings show that the proposed system incurs a computational cost of 12.1 ms and a communication cost of 1184 bits. Furthermore, smart contracts are deployed on the Remix virtual machine to showcase the functionality of the proposed system within a decentralized blockchain environment. The smart contract execution costs are (681,713), (734,851), and (870,301) for the RSU registry, vehicle registry, and session AuthTrust, respectively. The proposed scheme is comparatively evaluated against existing frameworks, namely PBSCF-ITS, AAKE-BIVT, IIoT-QRSCA, and BASF-ITS, using several metrics, including both computational and communication costs. The effectiveness and security of the proposed model are also verified through a security analysis. The results confirm that the proposed system outperforms similar existing baseline models.
cloud computing environments and multi agent systems has presented huge difficulties in creating a trust system, verifying securely and largely being transparent amongst the heterogeneous entities. The traditional centralized methods continue to become unsuitable with their vulnerability to the single point of failure, breach of data and unimpeccable auditability. The decentralized and immutable nature of blockchain technology has become a promising solution, but the currently operational blockchain-based systems still present severe constraints which are associated with scalability, high computation cost, disturbing latency as well as absence of adaptive trust mechanism.The current paper suggests a set of new conceptual frameworks on the use of an efficient and secure blockchain-based trust and verification system adapted to the distributed environment. The model uses a hybrid design that combines on-chain and off-chain processing to make the performance efficient and do not compromise security. An active screening system of trust is presented to determine the trustworthiness of each of the participating nodes on the basis of transaction history, behavioral patterns as well as their success rate of validation. Also, it includes a featherweight hybrid consensus which is based on Proof of Stake (PoS) and Practical Byzantine Fault Tolerance (PBFT) to ensure that it uses less energy to execute and also enhance the speed of transactions verification.The framework also includes smart contracts to verify and control access and use of data array of cryptography methods to guarantee the integrity of data and authentication. The proposed model offers a practical and flexible solution to the current distributed system since it tackles major challenge related to the system, namely scalability, efficiency and security. The framework is applicable to various areas which have been showcased in the IoT networks, management of supply chains, data sharing in healthcare, and e-governance. Future research possibilities include incorporating the element of artificial intelligence in the adaptive trust and quantum-resistant cryptographic research.
Blockchain technology has transformed distributed systems by enabling mutually untrusted nodes to reach agreement without a central authority. Such trustless decentralized paradigm relies on the robustness of system design mainly from two components: the consensus layer governing block production and the data layer governing data consumption. However, these pillars of robustness could be undermined in a Byzantine environment, where adversarial participants may strategically misbehave, leading to biased data production and compromised data access. This thesis systematically addresses robustness vulnerabilities across both layers, ensuring that blockchain systems remain fair, predictable, and verifiable throughout the entire data lifecycle. At the consensus layer, we first address selfish mining in Proof-of-Work (PoW), which allows adversarial miners to gain disproportionate revenue. We introduce an unfairness metric based on the divergence between computing power and mining revenue, and propose Tit-for-Tat (TFT), a block-promotion strategy that detects suspicious forking behavior and selectively delays block propagation. To optimize this defense, we formulate the Delay Vector problem and develops efficient approximation algorithms. Second, we study block withholding in Byzantine Fault Tolerant Proof-of-Stake (BFT-PoS), where proposers may delay blocks to extract additional Maximal Extractable Value (MEV). To restore predictable block generation, we propose InTime, an incentive mechanism that rewards timely proposals according to transaction arrival rates observed across the network. InTime combines an Arrival Rate Incentive, a Committee Time Witness workflow, and a Shift-Mean Estimation algorithm to collect and verify timing information under adversarial conditions. At the data layer, we propose the Merkle Bloom Filter Tree (MBFT), a framework for authenticated aggregate queries with keyword and range predicates. MBFT supports efficient verification for complex on-chain queries, including time-window queries, while controlling storage overhead. We design a novel Merge Bloom Filter (MBF) for space-efficient handling of dynamic sets during query authentication.
With the continuous development of blockchain technology, its applications have expanded into a wide range of fields. The consensus algorithm serves as the core of blockchain, with its performance directly influencing the overall efficacy of the blockchain system. Delegated Proof of Stake (DPoS) selects block producers through elections and offers advantages such as high performance, low energy consumption, and strong scalability. However, the election mechanism also brings several challenges, including vote bribery, low voter participation, and high degree of centralisation. To address these issues, we propose an improved DPoS algorithm based on the Technique for Order Preference by Similarity to Ideal Solution(TOPSIS) decision-making method, named BKT-DPoS, which enhances the consensus mechanism from a new perspective of multi-attribute decision-making. Specifically, a dynamic balanced clustering algorithm is introduced to constrain the voting range of certain nodes; the voting results are transformed into node influence scores using complex network theory; and the historical performance of nodes is dynamically assessed based on block production outcomes. A TOPSIS model is constructed to select the final block producers by considering node influence and historical behaviour values as decision attributes. After each round, the behavioural values of nodes are updated to incentivise honest nodes and penalise malicious ones. We conducted extensive simulations on networks ranging from 200 to 5,000 nodes over 1,00 to 10,000 rounds, and performed a comparative analysis against other improved algorithms.Experimental results demonstrate that the proposed algorithm significantly improves decentralisation, enhances resistance to vote bribery, and effectively mitigates the impact of malicious nodes.
The research focuses on the mechanisms, challenges, and consequences that UHC reform in Kenya has, conceptualizing UHC as a long-term government policy project that cuts across the governance, financing, and state capacity nexus. Based on theoretical frameworks of policy learning, incrementalism, and institutional capacity, the article evaluates the effects of Kenya's devolved system of health and strategic purchasing mechanism on UHC implementation and equity outcomes. Using qualitative policy analysis of government reports and academic publications, the research unveils structural constraints of the social health insurance program over time, the presence of inequalities in the delivery of services, and constraints of governance that mitigate the effects of reforms. These results bring into focus the necessity to strengthen the institutional capacity, strategic purchasing, and intergovernmental mobilization to achieve equitable and sustainable UHC. The article is a policy theory contribution to intricate social reforms through the way in which iterative policy learning and governance structure frame reform paths in a lower- and middle-income setting.
DIGITAL ASSETS AND THE LAW: AN INDIAN PERSPECTIVE WITH COMPARATIVE LESSONS FROM THE US AND UAE Tassaduq Hussain, Fourth-Year, B.A.LL. B (Hons.) Student, School of Law, University of Kashmir, Srinagar, J&K (India) Download Manuscript doi.org/10.70183/lijdlr.2025.v03.225 Digital assets have rapidly emerged as a defining feature of the global financial ecosystem. Cryptocurrencies, stablecoins, non-fungible tokens (NFTs), and Digital assets have rapidly emerged as a defining feature of the global financial ecosystem. Cryptocurrencies, stablecoins, non-fungible tokens (NFTs), and Central Bank Digital Currencies (CBDCs), all rooted in blockchain technology, are reshaping our understanding of value, ownership, and financial systems. In India, while adoption has surged, the regulatory and legal framework remains fragmented, reactive, and ambiguous.
Open access
Innovations and Analysis in Business and Education
D C Saputro, Noor A Setiawan, Azkario Rizky Pratama, Avinanta Tarigan
The increasing adoption of blockchain technology in education has introduced alternative approaches to identity verification beyond centralized credential systems. This study proposes and implements a decentralized authentication mechanism for Moodle LMS using ERC-721 non-fungible tokens (NFTs) verified through MetaMask. Developed as a proof-of-concept following a design science methodology, the system links on-chain identity tokens to Moodle accounts without storing usernames or passwords. The architecture integrates Ethereum smart contracts, nonce-based digital signature verification, and Moodleâs Role-Based Access Control (RBAC) framework. Functional testing confirms that access is granted exclusively to users possessing valid ERC-721 tokens and verified wallet signatures. Replay attack simulations demonstrate effective resistance through nonce validation, while ensuring that no sensitive credential data is exposed during the authentication process, in contrast to default Moodle login mechanisms. Performance evaluation using Apache JMeter indicates stable operation under moderate loads. Although scalability and token management limitations remain, the results demonstrate the technical feasibility and enhanced security advantages of NFT-based authentication for learning management systems.