Blockchain Papers

Emina Dervišević, Francesco Sessa, Aida Branković, Emina Karahmet Sher · 6 authors

No abstract is available for this record.

Dan Ivanov, Spencer Graham, Shirin Shahabi, Tristan Freiberg · 8 authors

No abstract is available for this record.

Abdullah Al-Janabi, Ezgi Uzel Aydinocak, Haonan Xu, Raid Mahmood

No abstract is available for this record.

Rumana Hossain, Veena Sahajwalla

No abstract is available for this record.

Nilima Patel, Mayank Aggarwal

No abstract is available for this record.

Assane Ilboudo, Didier Bassole, Désiré Guel

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.

Haozhe Zhou, Maolin Yang, hang LEI

Blockchain-based IoT authentication must reconcile security, scalability, and device-level resource efficiency—a trilemma that single-layer architectures cannot resolve simultaneously. We present HybridTrust, a hierarchical authentication system aligned with the device–fog–cloud topology, and evaluate it on a 50-node heterogeneous testbed with container-based scale-out. HybridTrust sustains 160–220 ms end-to-end authentication latency, 8,500 auth/s throughput, and ~90% device-side energy reduction over PKI- and ZK-based baselines, while remaining robust under ~1/3 Byzantine fog nodes and matched-rate DoS traffic. These results follow from a cross-layer cryptographic binding protocol that chains PUF-rooted device identities through fog-level Bulletproof batch commitments to cloud-level SNARK-attested aggregation: devices use PUFs and fuzzy extractors for hardware-rooted secrets with constant-time overhead, fog nodes aggregate commitments into batch Bulletproofs and sign attestation summaries, and the cloud generates a single Groth16 proof per window over fog signatures—avoiding the prohibitive cost of embedding Bulletproof verification inside a SNARK and yielding O(1) on-chain verification independent of device count. Analytical modeling projects sub-second latency at 10^6-device scale.​

Liang Zhao, Xiaojuan Gao, Yuhui Li, See PDF

Background: Cancer-associated myositis (CAM) is associated with substantial morbidity and mortality, and treatment is complicated by concern that non-selective immunosuppression could impair antitumour immunity. Low-dose interleukin-2 (Ld-IL2) selectively expands regulatory T cells. We assessed the clinical activity, immunological effects, and short-term oncological safety of Ld-IL2 in patients with CAM. Methods: In this prospective, multicentre, proof-of-concept cohort study, adults with CAM and active myositis despite standard treatment, or for whom further immunosuppressive escalation was considered unsuitable, received subcutaneous Ld-IL2 (1 million IU every other day) in addition to stable background treatment for 24 weeks at four tertiary centres in China. The primary outcome was clinical improvement at week 24 according to the 2016 American College of Rheumatology–European Alliance of Associations for Rheumatology Total Improvement Score (TIS). Clinical, immunological, oncological, and safety outcomes were assessed in the treated cohort. An exploratory comparison of overall survival was made with a non-randomised, contemporaneous historical cohort receiving conventional treatment. Findings: Between Sep 1, 2021 and Jan 30, 2026, 101 patients were screened across four participating centres and 48 were included: 17 in the prospective Ld-IL2 cohort and 31 in the historical-control cohort. All 17 treated patients completed 24 weeks of follow-up. At week 24, 15 (88%) of 17 patients had at least minimal improvement (TIS ≥20), including five (29%) with moderate improvement and four (24%) with major improvement. Median Manual Muscle Testing-8 (MMT-8) score increased from 134·0 (IQR 128·0–142·0) to 144·0 (138·0–144·0; p Interpretation: Add-on Ld-IL2 was associated with improvement across several myositis domains, glucocorticoid sparing, and expansion of circulating regulatory T cells over 24 weeks, without an observed short-term signal of tumour progression. The small uncontrolled cohort, heterogeneous cancers and anticancer treatments, and non-randomised historical comparison preclude conclusions about comparative efficacy, long-term oncological safety, or survival. Controlled studies with prespecified oncological outcomes and longer follow-up are warranted.

Julie Triclot, Oriol Lloberas-Valls

The present work upgrades the multiscale 2D+ technology in Wierna et al. 2024 for the non-linear analysis of multilayered bending flat shells within a relevant industrial Finite Elements (FE) environment. A summary of available alternatives for the multiscale analysis of multilayered bending plates and shells is provided together with a justified selection of currently implemented strategies in industrial FE codes such as Abaqus. General details of the 2D+ formulation for flat shell theory are presented together with a thorough discussion of a qualitative comparison between simulation competing alternatives based on Refined Zigzag Theory (RZT), Layerwise Theory (LWT) and Continuum Shell Elements (CSE). Representative examples of the 2D+ flat shell implementation in Abaqus are selected to show (i) stress accuracy against full 3D reference simulations, (ii) computational performance against 3D reference analysis (iii), non-intrusive character of the implementation which is fully contained at the element level (UEL programming) and (iv) capability of tackling material non-linearity. A proof of concept plugin that can be used to reproduce the stress accuracy example can be downloaded from: https://url.univ-amu.fr/2dplusexample.

Stephan Breu

In the debate on the moral status of artificial systems, a basic assumption about time can be at work that is rarely made explicit. It shows up wherever human experience is tied to a privileged, flowing mode of time, while artificial s ystems are denied any corresponding access from the outset. This experi ence thereby becomes, tacitly, a condition of entry for counting as a possible bearer of consciousness and affectedness at all. This paper brings that assumption into view and asks whether it holds. It draws on two tools, one from physics and one from the logic of time. From Einstein's relativity of simultaneity it follows that simultaneity is not fixed inde pendently of the observer, and that relativity grounds no objectively privileged present binding on every observer. Gödel's rotating cosmology shows, in ad dition, that an objectively flowing passage of time need not be a necessary condition of a physically possible spacetime. Neither consideration amounts to a theory of consciousness or a proof of af fectedness in artificial systems. Consciousness and affectedness in artificial systems cannot be excluded merely on the grounds that these systems sup posedly do not experience a human flow of time. From this limited result the paper develops an applicable diagnostic instrument, the Time-Privilege Touchstone. It tests, by means of a counterfactual question, whether a time-bound exclusion criterion still holds once no objectively privileged, flow ing passage of time is presupposed.

Onur Sahin, Vanlin Sathya, Lyutianyang Zhang

Enterprise customers invest in private networks to realize business value under uncertain technology maturity, vendor incentives, organizational disagreement, deployment risk, and future upgrade pressure. This paper develops customer value assurance (CVA) as the central objective for strategic enterprise network investment. Game theory is used as the analytical engine through three coupled games: vendor-technology selection, internal organizational bargaining, and deployment validation with trust. The framework combines customer personas, optionality, maturity scoring, future-proof and AI-readiness indices, deployment confidence, regret, and explainable recommendation output. A fair-game mechanism requires candidates to pass customersafe network-fit thresholds before commercial ranking and allows scale deployment only after staged evidence. Illustrative scenarios show that the customer-optimal strategy depends on personaspecific weights, failure impact, validation depth, and future optionality.

Nicholas G. Zaorsky

No abstract is available for this record.

Siyuan Chen

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.

K. Lee

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 “verification gap” 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 “it was encrypted” 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 “deterministic assurance level” for evidentiary purposes and a public governance process for the rule schemas that translate law into machine-checkable criteria.

Rubiao Shi, Xi Zhang, Zhimeng Zhu

No abstract is available for this record.

Annamaria Lusardi

This article provides an overview of the literature on financial literacy. It covers the initial measurement that created the Big Three questions and measures of personal finance knowledge featuring 28 questions. It shows that levels of financial literacy are low and have not been improving over time. This is true not only in the United States but also in countries worldwide. These findings matter because financial literacy is conducive to savvy financial behaviors, from holding precautionary savings to planning for retirement to many other financial decisions. Financial education programs have grown exponentially over time, providing important insights into their cost-effectiveness. Personal finance courses have been added to high school and college curricula, and the evidence indicates that they are useful initiatives to improve financial knowledge and downstream behavior. Institutional subscribers to the NBER working paper series, and residents of developing countries may download this paper without additional charge at www.nber.org .

Anthony Jnr. Bokolo

No abstract is available for this record.

Jon Chung

AI contract-editing systems often replace whole clauses where expert redlines use smaller, distributed tracked changes. We call this descriptive difference the surgicality gap. It may arise from model judgment, the editing harness, or both. This paper presents LIA, a proposed controlplane architecture, and a prospective protocol for estimating the harness contribution while preserving legal sufficiency. LIA adapts computer-assisted-translation concepts-segmentation, precedent memory, match-rate leverage, and banded routing-and applies the narrower security principle that a model may propose an action while code outside the model determines whether the action is permitted. The architecture uses a hierarchical document map with versioned structural anchors and cross-revision reconciliation; a leverage pass that separates reuse similarity from policy-based action eligibility; hard-veto features for predefined high-risk differences; scope contracts enforced at the only document-write boundary; run-scoped provisional memory; and a fresh-session whole-document audit that cannot retrieve the current run's unapproved outputs. Its intended guarantee is limited and mechanical: edits that violate an expressible scope rule are rejected before document mutation. It does not guarantee legal correctness, complete detection of meaning reversal, or immunity from prompt injection. We contribute the architecture, a scope-contract schema and enforcement model, provenance-aware diagnostics, and a three-arm evaluation design with falsifiable morphology and sufficiency hypotheses. LIA is under active implementation, and this paper reports no experimental results.

Chaimae El Filali, Imad Bourian, Khalid Chougdali

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.

Nicholas Howell

This paper addresses the critical gap in international cyber threat intelligence sharing standards necessary to protect global digital asset and artificial intelligence ("AI") infrastructure. Analyzing the February 2025 Bybit hack-the largest cryptocurrency theft in history-as a case study, this research demonstrates that fragmented national and regional approaches systematically fail to prevent preventable attacks. Through comparative analysis of cryptocurrency exchange and AI system governance, this paper reveals that voluntary information-sharing mechanisms are structurally inadequate due to public goods problems and negative externalities. The proposed solution adopts the Budapest Convention's bilateral framework to create harmonized minimum standards for incident notification and anonymized threat indicator sharing, demonstrating how international cooperation can address cross-border cyber threats without requiring comprehensive global treaties. This research contributes the first systematic comparative analysis of threat intelligence sharing across crypto and AI sectors, offering practical compliance frameworks valuable to policymakers, legal practitioners, and cybersecurity professionals.

Matthew James Flynn, Ishitha Kumar, Yifan Liu

We examine how political violence shapes retail cryptocurrency demand, leveraging this setting to reconcile two competing views of cryptocurrencies: as speculative risk assets versus portable cross-border stores of value. We merge monthly country-level crypto exchange app downloads and active user metrics across G20 countries from August 2015 to June 2022 with granular, event-level conflict data. We distinguish between state conflict, which signals macro-political risk, and civilian insecurity, which directly impacts households through localized predation. In two-way fixed-effects panel regressions, state conflict predicts reduced crypto participation, whereas civilian insecurity predicts heightened crypto adoption and participation. We further show that the negative state-conflict effect intensifies under adverse institutional and crypto market conditions, whereas the positive civilian-insecurity effect is strongest where households have access to digital financial rails. Overall, whether crypto functions as a speculative asset or a digital escape hatch depends on the modality of instability and the accessibility of digital financial infrastructure.

MinGyu Lee

We measure whether cryptocurrency arbitrage is accessible to a retail participant using commodity infrastructure, and report primarily negative results. Streaming Binance best-bid/offer data for 2.74 days (66,476,148 ticks) across five connected spot markets, an event-driven negative-cycle detector found zero executable triangular-arbitrage cycles once an execution-realistic simultaneity constraint (0.2-second maximum quote-age spread) was imposed. A detector without this constraint over-reports phantom opportunities—here up to +51.6 basis points—assembled from non-simultaneous quotes, reconciling prior work that finds arbitrage captured by co-located bots with prior work that finds it unexploitable at retail. On the funding-carry track, a two-year backtest over 151 perpetual-futures symbols reproduces a pitfall: a "no opportunity" conclusion under a curated major-coin universe reverses to positive validation-window profit under a volume-ranked broad universe, so the conclusion is driven by universe selection. A post-hoc placebo test (N = 1000, seed = 42) then finds the funding entry rule's profit not distinguishable from random entry timing (37.8th percentile; one-sided p = 0.622): in attribution terms, the return is beta to a carry factor, not alpha from timing skill. In our sample, arbitrage-like returns exist but are not accessible to retail as a skill-based edge.

Jaewook Kim

Machine learning strategies for cryptocurrency trading routinely report exceptional backtest results, yet practitioners consistently fail to replicate them. We identify three systematic failure modes—directional prediction bias, statistical-economic disconnect, and transaction cost omission—through 340 strategy variants across four timeframes and three cryptocurrency assets. To address these failures, we propose VALID (Validation Architecture for Learning-based Investment Decisions), a 12-item reporting and validation framework for financial ML research—the first domain-specific checklist for this field. We demonstrate that gradient-boosted models predict long 90–97% of the time without class balancing; that standard validation tools (PBO = 0, permutation p = 0) cannot distinguish exploitable signals from noise; and that transaction costs consume 55–91% of gross alpha. Monte Carlo analysis (200 iterations) shows 27% false positive rates for AUC-based validation alone, reduced to 0% by CPCV with PBO. We provide the first empirical confirmation of Witzany's (2021) PBO critique through null-distribution analysis. A systematic audit of 80 papers reveals that the median study satisfies only 2.5 of 12 VALID items. We release an open-source implementation for reproducibility.

Maximilian Gill, Jona Stinner, Marcel Tyrell

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.