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 inter‐satellite data requires robust protection, and aircraft‐ground station links must prevent hazards. Vulnerabilities could breach security protocols, compromising confidentiality and incurring legal consequences. This paper presents the first integration of proof‐of‐authority (PoA) consensus, ERC1155 multi‐token standard and threshold cryptography for satellite data transactions. Unlike prior blockchain‐based proposals that rely on single‐key encryption or energy‐intensive proof‐of‐work (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 (k‐of‐n) 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 man‐in‐the‐middle attacks and 0% success for reentrancy/Sybil attacks. Dynamic share recovery during orbital handovers attains 98% success, outperforming traditional methods in resilience and efficiency.
Areeb Sajid, Faiz Noor Khan Yusuf, Jamaluddin Jamal
The detection of Ethereum fraud is still one of the biggest problems due to the highly unbalanced nature of blockchain transactions and the sheer volume of today's cryptocurrency networks. In this paper, we compared six supervised learning models on the XBlock-ETH transaction graph with 2.97 million nodes. Using a scalable preprocessing pipeline, dimensionality reduction, and class balancing with the SMOTE technique, the training samples were extracted and processed to obtain graph-derived transaction features. The experimental results show that the ensemble-based methods always perform better than the linear based and single-tree-based methods, with SVM Nyströem achieving the highest fraud recall (0.944) and Gradient Boosting achieving the strongest ROC-AUC (0.983), indicating complementary strengths in detection sensitivity and overall discrimination. Additionally, the study shows that in the case of severe class imbalance, the overall accuracy can be misleading, as the Random Forest model can reach 0.991 accuracy but only identify 52.8% of fraudulent accounts. XGBoost has the best performance on both detection and computational costs among the evaluated models and can be a viable choice for large-scale fraud detection systems on the Ethereum network.
Bitcoin price movements are highly volatile and nonlinear over time. Traditional GARCH models are widely used for volatility modeling, but they may not adequately represent nonlinear effects of exogenous variables. In this study, we develop a weighted semiparametric EGARCH model for forecasting Bitcoin volatility by combining the parametric conditional variance from an EGARCH model with a nonlinear crude oil market volatility component estimated using the Nadaraya–Watson kernel estimator. The empirical analysis uses daily Bitcoin and crude oil price data from 2017 to 2026. The forecasting performance is compared with GARCH(1,1), EGARCH(1,1), and semiparametric EGARCH models incorporating crude oil market volatility. The root mean square error, mean absolute error, quasi-likelihood loss, and Diebold–Mariano test are computed to assess the out-of-sample forecast accuracy for various training-testing split designs. Empirical results indicate that the proposed weighted semiparametric EGARCH model achieves higher forecasting accuracy and robustness for forecasting Bitcoin volatility.
Bitcoin miners consume roughly 0.5% of global electricity and, unlike most industrial loads, can curtail consumption on subsecond timescales. I develop a contract-theoretic model of a vertically-integrated utility that jointly chooses fossil, renewable, and flexible-computing-load (FCL) capacities and then dispatches against stochastic residual demand. Under the maintained assumptions of the model I derive sufficient conditions under which introducing an FCL weakly reduces expected carbon emissions in equilibrium, with strict reduction on the interior event. I sign the comparative statics of the equilibrium carbon functional Ψ(F; θ) with respect to seven primitives and verify each sign numerically across eight residual-demand distributions, confirming five distribution-free signs and two shape-sensitive ones. On the Pareto tail I obtain a closed-form distributionally robust characterization: the worst-case tail index shifts from 2.50 to 2.10 as the Wasserstein-1 ambiguity radius grows, and the price of robustness is bounded by 0.125 units of expected profit in the tested grid. I calibrate the model to the June 2021 power purchase agreement between Cipher Mining's Odessa facility and Luminant ET Services (Vistra Corp), a 200 MW fixed-price contract with curtailment rights extending through July 2027, and show that publicly disclosed curtailment events during the summer 2022 ERCOT scarcity episodes are broadly consistent with the model's carbon-optimal dispatch rule.
Short dated Bitcoin binary contracts settle over horizons brief enough that expected drift is negligible, which reduces their fair value to a function of current spot and short horizon volatility alone. This paper frames the contract as a cash or nothing digital option, derives a driftless fair value, and defines an entry rule that acts when the implied price and fair value differ by at least a fixed buffer, sizing by a model edge score. On 182 resolved contracts traded across 22 to 23 June 2026, the rule realised a positive statistical edge, a win rate of 67.6 percent against the 63 percent break even rate implied by the mean entry price of 0.63, an edge of 4.6 percentage points. The point estimates are positive across the headline measures, but the sample is too small to establish significance: bootstrap intervals on the edge include zero, and the model fair value does not improve on the market price as a probability forecast. The realised gain is concentrated in a small number of trades and coincides with a directional position, and an edge threshold selection rule does not persist out of sample. The result is interpreted as a statistical edge documented within a single window, whose significance and source, a genuine pricing signal against the established favorite longshot bias, remain open questions pending a larger sample. The contribution is the pricing framework and its evaluation.
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.
Bitcoin fees allocate scarce settlement priority and finance proof-of-work security, but paid fees also contain wallet and payment wedges. Using 18.26 million first-seen mempool transactions, we estimate a structural priority-queue model that maps fee ranks to confirmation outcomes. Structural priority prices are 4.3% of fitted mean paid fees; a re-estimation bootstrap gives a 2.5%-10.1% interval. Capacity expansions lower fees and delays; fee floors raise payments without improving confirmation. Because fees are only 0.56% of current miner rewards, security effects are small today but first-order in fee-only futures.
Susan Ledger, Claire Bates, Jordan Smith, Elena Prieto · 6 authors
: Initial teacher education (ITE) programs are shaped by diverse political, cultural, and policy contexts, resulting in varied approaches to preparing secondary teachers. This study presents a global scoping review of postgraduate ITE (PG-ITE) programs across 58 countries, examining four key characteristics: program duration, entry requirements, curriculum, and practicum structure. Findings reveal substantial variation across all dimensions, reflecting differing national priorities and workforce pressures. While common structural features are evident, program design is shaped by underlying policy logics and assumptions about teacher preparation. By systematically mapping these patterns, this study provides a comparative contribution to the field and offers insights to inform the development of future teacher education policy and practice.
Background. Contemporary financial risk models — Value-at-Risk, Expected Shortfall, Black–Scholes– Merton, Merton default, CAPM, Vasicek/HJM term-structure models, Solvency II, Basel III/IV, IFRS 9/17 — are one-dimensional projections of an intrinsically higher-dimensional decision phenomenon. The projections perform within a narrow regime and generate the very tail instability they purport to measure outside that regime. Recurrent crises (1987, 1998, 2000, 2008, 2020, 2023) are not statistical anomalies but structural artefacts of dimensional reduction. Objective. This paper proposes and axiomatises Economic Determinism: a deterministic reformulation of the full financial risk calculus on a five-dimensional manifold, hereafter the Curzi Manifold M⁵, and demonstrates that the incumbent framework is recovered as a rigorous limiting case. Methods. We construct M⁵ over the axes (i) ordinal position ω (well-ordered sequence, not cardinal magnitude), (ii) rational magnitude r ∈ ℝ, (iii) logical validity ℓ ∈ [0,1] with an Aristotelian syllogistic kernel, (iv) imaginary phase iφ ∈ iℝ carrying non-commutative structure, and (v) choice χ, an agential– temporal coordinate exhibiting Heisenberg-type observation dependence. On M⁵ we impose (a) the Coverage Hyperbola invariant r · ℓ ≥ 1.8; (b) the Zero-Preserving Division (ZPD) axiom x/(0·y) = y, resolving denominator pathologies without singularities; (c) the Fibonacci-Signed Paradox-Resolution Algebra (FS-PRA), a graded signed calculus in which contradictions at level n are annihilated by Fibonacci-count balanced postulate pairs at level n+1; (d) a financial wave-function analog Ψ(χ, t) with Hamiltonian H generating deterministic evolution of choice-conditioned exposure; and (e) a quantumatom-theory analog quantising sovereign reserve shells with selection rules and a Pauli-analog exclusion on double-pledged collateral. Each incumbent risk operator is re-expressed as a deterministic map ρ: M⁵ → ℂ, red-teamed for logical consistency, operational feasibility, and regulatory compatibility, and shown to reduce continuously to its legacy form under a specified projection π: M⁵ → ℝ. Results. Thirty-one papers (EDP-000 through EDP-030) reformulate the canonical apparatus across credit, market, liquidity, counterparty, IRRBB, operational, portfolio, derivatives, fixed-income, equity, sovereign, FX, balance-of-payments, monetary transmission, structured products, systemic, contagion/network, insurance solvency, actuarial reserving, pension/LDI, commodity, energy, agricultural, fair-value/impairment, consolidation, hedge-accounting, digital-asset, climate, and algorithmic-risk domains, terminated by a master glossary. Principal formal results: (i) rehypothecation chains that violate the Coverage Hyperbola are provably paradoxical under FS-PRA and admit a unique deterministic annihilation; (ii) the Merton–Black–Scholes call price recovers as the ℓ → 1, iφ → 0, χ collapsed limit of the deterministic derivative operator; (iii) VaR-style tail metrics recover as the ordinal-flattened, choiceintegrated projection of an unfolded M⁵ exposure surface; (iv) sovereign default is a shell-transition event with a selection rule expressible in closed form; and (v) systemic risk becomes a coverage-hyperbola violation counted with Fibonacci multiplicity. Contribution. The paper (a) formalises the first deterministic risk calculus that is dimensionally complete with respect to observable market structure; (b) supplies backward-compatible reductions to every current regulatory metric (Basel, Solvency, IFRS); (c) proposes a three-tier adoption pathway (shadow reporting → parallel books → primary ledger) preserving legal and accounting continuity; and (d) unifies the NineCapital taxonomy and the Triple-Ledger (Nostro / Vostro / Lux) architecture within a single risk-theoretic object. Implications. If the framework is correct, the persistent excess volatility, correlation breakdowns, liquidity air-pockets, and cross-asset contagion that classical risk systems misclassify as fat tails are instead deterministic consequences of operating a five-dimensional system with two-dimensional instruments. Adoption is optional, gradual, and reversible until the terminal tier; the reduction property guarantees that no institution is worse off at any adoption depth. The framework is offered as a convergent, cooperative, and non-coercive completion of the existing risk canon.
Abstract Four independent fields—physics, biology, economics, and cultural evolution—have 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 public–private 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 Diffie–Hellman 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.
Bezpečnostné zlyhania blockchainových systémov zriedkavo vyplývajú z prelomenia kryptografie. Častejšie vznikajú z ekonomických stimulových nekompatibilít, chybných protokolových predpokladov a implementačných nedostatkov, ktoré môžu byť naprieč architektonickými vrstvami. Doterajší výskum prevažne analyzuje jednotlivé vrstvy blockchainov izolovane. Avšak takýto prístup nie vždy dokáže detegovať zraniteľnosti, ktoré sa môžu objavovať na hraniciach medzi jednotlivými vrstvami. Predkladaný výskum rieši túto poukázanú bezpečnostnú medzeru prostredníctvom systematickej medzivrstvovej analýzy založenej na bezpečnostnej referenčnej architektúre pre blockchainy. Použitá metodológia kombinuje modelovanie protokolov pomocou teórie hier, rozsiahle diskrétne a stochastické sieťové simulácie, návrh a prototypovanie protokolov, systematickú analýzu 36 kryptomenových peňaženiek a dôkazy s nulovou znalosťou typu zk-SNARK. Na vrstve konsenzu je formálne dokázané, že náhodný výber transakcií v protokoloch Proof-of-Work založených na orientovanom acyklickom grafe netvorí Nashovou rovnováhou. Simulácie s viac ako 8000 uzlami potvrdzujú, že táto zraniteľnosť pretrváva pri realistickom sieťovom rozsahu. Vyhodnotenie sebeckej ťažby s viacerými útočníkmi ukazuje, že prah ziskovosti v Nakamotovom konsenze klesá z 33% pri jednom útočníkovi na približne 14% až 17% pri piatich súčasných útočníkoch, a ukazuje, že Strongchain je konzistentne najodolnejší protokol vo všetkých testovaných konfiguráciách. Na rozhraní medzi konsenzom a sieťovou vrstvou dosahuje protokol Proof-of-Stake s integrovaným cibuľovým smerovaním anonymizáciu navrhovateľa blokov pri priepustnosti približne 110 transakcií za sekundu. Na aplikačnej vrstve formálna taxonómia autentifikácie odhaľuje, že väčšina analyzovaných kryptomenových peňaženiek poskytuje iba jednofaktorovú autorizáciu overovanú blockchainom napriek zdanlivej zložitosti ich rozhrania. Architektúra synchronizácie založená na zk-SNARK znižuje nároky mobilného klienta na úložisko zo 71MB na 3,5MB a nahrádza dôveru v servery tretích strán kryptografickou verifikáciou. Tieto závery a vykonaný výskum spoločne preukazujú, že bezpečnosť blockchainov je vo svojej podstate medzivrstvová vlastnosť, a zároveň poskytujú analytické nástroje, empirické referenčné hodnoty, protokolové mechanizmy a kryptografické návrhy pre budovanie odolnejších decentralizovaných systémov.