Blockchain Papers

Yulong Lei, Zishuo Wang, Jinglin Xu, Yuxin Peng

No abstract is available for this record.

Chunhong Liu, Yuhang Sui, Li Duan, Kun Wang · 5 authors

No abstract is available for this record.

Shubhangi Rajendra Patil, PE Ajmire

Over the past years, there has been increased risk of forging and replicating academic credentials unauthorized, and manipulation of data due to fast computerization of academic credentials. The traditional verification system that is centred on the Public Key Infrastructure (PKI), has included instances such as centralized control, the lack of transparency, and vulnerability to points of failures. Such challenges are suggesting a decentralized approach to the generation of digital certificates as well as their validation with the assistance of a blockchain Technology that is secure in nature. The suggested system will use cryptographic hashing, smart contracts using Ethereum and distributed ledger mechanisms to provide integrity, authenticity, and immutability of data. The blockchain has certificates in the hash values that can be easily verified and without the involvement of middle men. The framework will also enhance trust among the stakeholders as they will be in a position to ensure validation without disruption. As it is revealed through the experiment analysis and modular evaluation, the offered solution enhances the effectiveness of the verification towards its significant extent, the chance of fraud decrease, and offers a solution which can be further scaled and become suitable in the contemporary digital certification systems.

Fabrizio Sudiero

One of the most discussed topics in corporate law is the “real” effectiveness of shareholders’ agreements, i.e. the validity of those clauses that prevent the non-fulfilment of the agreements and that therefore ensure fulfilment of shareholders’ agreements as an alternative to compensatory remedies. In fact, as well known, especially with regard to voting trusts, their legitimacy has always been based on their merely personal and obligatory effectiveness, considering null and void those agreements that include the mentioned “real” mechanisms. In this context, technology and, in particular, the entry of blockchain and smart contracts introduces new possible frontiers that this article, taking as an example the Italian legislation (which provides for a specific regulation of smart contracts), intends to explore by also proposing an interpretative solution and a possible embryonic prototype.

Virgil Kuassi Lokossou, Aishat Bukola Usman, Issiaka Sombie, Oluomachukwu Omeje · 34 authors

BACKGROUND: Lassa fever remains a major public health threat in West Africa, requiring coordinated scientific, policy, and financing responses. Regional scientific convenings are increasingly used to connect research evidence with policy action, yet their contribution to epidemic preparedness is not well documented. METHODS: We conducted a qualitative health systems and policy analysis of the 2nd ECOWAS Lassa Fever International Conference (ELFIC 2025) in Abidjan, Côte d'Ivoire. Data sources comprised 302 scientific abstracts, plenary and ministerial session records, and the official Ministerial Joint Communiqué. Using the conference's six thematic pillars as a deductive framework, we conducted a thematic content analysis and synthesized findings into four domains: scientific advances; surveillance and laboratory systems; policy and financing insights; and cross-cutting lessons for regional preparedness. RESULTS: Progress was noted in diagnostics, therapeutics, vaccine development, decentralized laboratory capacity, genomic surveillance, and digital reporting. Persistent gaps remain at sub-national and community levels, in surveillance coverage, workforce capacity, and operational readiness. A major outcome was the Ministerial Joint Communiqué endorsing regional co-financing for Lassa fever vaccine development. CONCLUSION: ELFIC 2025 demonstrates the role of regional scientific platforms in aligning evidence with policy commitments. Sustained impact will require institutionalized coordination, strengthened accountability, and targeted investments in frontline capacity.

Shikha Mathur, Shikha Mathur

Smart contracts have become a cornerstone of modern blockchain ecosystems by enabling decentralized, transparent, and autonomous execution of digital agreements. Despite their widespread adoption, smart contracts continue to suffer from two persistent challenges: inefficient execution and critical security vulnerabilities. These limitations not only increase operational costs but also undermine trust in blockchain-based systems. This research paper presents a comprehensive and plagiarism-free investigation into smart contract optimization with a strong emphasis on security-driven design principles. The study analyzes execution inefficiencies, gas consumption patterns, and architectural constraints across major blockchain platforms, alongside prevalent vulnerabilities such as reentrancy attacks, integer overflows, access control flaws, and logic inconsistencies. Building upon this analysis, the paper proposes an integrated optimization–security framework that combines code-level optimization, modular design, formal verification, automated vulnerability detection, and hybrid on-chain/off-chain computation models. The proposed approach demonstrates how efficiency and security can be jointly enhanced rather than treated as isolated objectives. The findings aim to guide developers, researchers, and practitioners in designing smart contracts that are cost-effective, secure, and resilient within rapidly evolving blockchain environments.

Mechthild Schrooten

Der Text analysiert den tiefgreifenden Wandel des Finanzsystems in Zeiten der Digitalisierung. Er zeigt, wie private Fintechs und Krypto-Emittenten das staatliche Monopol der Regulierung und der Geldbereitstellung infrage stellen. Marktmacht entsteht durch Regulierungsversagen.

Kasra Zarinehbaf Asadi

Yield-Aggregatoren automatisieren den Prozess des Yield-Farming im Bereich des Decentralized Finance (DeFi), indem sie Nutzerkapital bündeln und über verschiedene Protokolle hinweg einsetzen, um Renditen zu optimieren. Aufgrund ihrer hohen Komplexität sind ihre Funktionsweisen jedoch schwer nachzuvollziehen, und die Forschung zu ihren internen Mechanismen sowie den Interaktionen mit anderen Protokollen ist bislang begrenzt. Diese Arbeit adressiert diese Forschungslücke durch die Analyse zweier Ethereum-basierter Yield-Aggregatoren: Yearn Finance und Cian Yield Layer. Hierzu wurden Blockchain-Daten über einen Zeitraum von einem Jahr (4. Mai 2024 bis 3. Mai 2025) erhoben und ausgewertet, bestehend aus 2.459 Yearn-Transaktionen mit 5.575 Token-Transfers sowie 921 Cian-Transaktionen mit 1.963 Token-Transfers. Die Arbeit kombiniert eine operative Analyse, eine Netzwerkanalyse der Kapitalflüsse und einen Vergleich der Plattformmerkmale. Die Ergebnisse zeigen unterschiedliche Strategien: Yearn investiert Kapital überwiegend in Lending-Protokolle, indem es Liquidität zur Verfügung stellt, während Cian auf gehebeltes, rekursives Staking unter Einsatz von Flash-Loans setzt, um Restaking-Erträge zu erhöhen. Yearn hat eine breite Nutzerbasis mit vergleichsweise kleinen Einzeltransaktionen, während Cian eine kleinere Nutzerbasis besitzt, die von einem höheren Anteil großer Einzahlungen geprägt ist. Auf Grundlage der Analyse wurde ein konzeptionelles Modell entwickelt, das aus zwei miteinander verbundenen Lebenszyklen besteht: dem User-Lifecycle (Einzahlungen, Halteperiode, Auszahlungen) und dem Strategy-Management-Lifecycle (Kapitalallokation, Strategieausführung, Umschichtung). Dieses Modell erfasst die grundlegenden ökonomischen Funktionen von Yield-Aggregatoren unabhängig von ihrer technischen Implementierung. Die Arbeit liefert empirische Einblicke in die Funktionsweise von Yield-Aggregatoren, identifiziert DeFi-Protokolle als Investitionsziele und stellt ein konzeptionelles Modell zum Verständnis der Mechanismen von Yield-Aggregatoren vor.

Rami Cherri

Machine Law Engine (MLE) v1.2.0 presents a formal computational architecture that reconceives regulatory compliance from a retrospective, documentary discipline into a pre-emptive, cryptographically enforced state property. Where classical GRC tooling observes violations after they occur, the MLE enforces legal constraints before execution — making non-compliant operations computationally impossible rather than merely detectable. The architecture introduces three original contributions to the field of computational law and applied cryptography: (1) The Admissibility Vector — a four-dimensional formal scoring function (authority α, evidence ε, context γ, transition legality τ) that evaluates every regulated operation at execution time against all applicable legal rules. The collapse axiom τ=0 → Φ=0 produces terminal refusals for legally impossible state transitions that cannot be overridden by any combination of authority or evidence. (2) The Challenger Provenance Architecture — a novel mechanism, without precedent in published GRC frameworks, that enforces structural independence of AI-assisted compliance reasoning. If a challenger input cannot demonstrate cryptographic divergence (CPD ≥ 0.70, path_overlap ≤ 0.20) from the primary reasoning path, the gate cannot achieve full institutional binding — operationalising DORA Art.15, EU AI Act Art.9(9), and BCBS 239 Principle 11 as cryptographic invariants rather than policy obligations. (3) The Seven Formal Invariants — hard computational constraints governing the MLE's correctness properties, with mathematical predicates, three-tier runtime monitoring (write-time, scheduled, continuous), and automated violation response protocols including cryptographically evidence-hashed remediation workflows. The reference implementation integrates: four hardware TEE providers (AWS Nitro Enclave, Azure Confidential Computing, Intel SGX/TDX, AMD SEV-SNP) with PCR register semantic attestation; a post-quantum cryptographic stack fully standardised under NIST FIPS 203/204/205 (CRYSTALS-Kyber-1024, CRYSTALS-Dilithium-3, SPHINCS+) providing 30-year evidence integrity against harvest-now-decrypt-later attacks; four PLONK-based Zero-Knowledge proof circuits on BLS12-381 (128-bit soundness) resolving privacy-compliance paradoxes for OFAC sanctions screening, FinCEN BSA threshold verification, DORA Art.28 vendor certification, and GDPR right-to-erasure evidence chains; a bi-temporal append-only ledger with DORA Art.11 automated retro-simulation; a seven-stage NLP-to-enforcement-code compilation pipeline with Kyber-1024 tamper detection and dual-approval protocol; a multi-framework conflict engine covering six active cross-regulatory conflict pairs (GDPR × FINMA, GDPR × FinCEN BSA, DORA × NIS2, EU AI Act × GDPR, eIDAS 2 × CCPA) with five deterministic resolution strategies; and nine Interactive Verification Layer modules enabling complete live regulatory demonstration in 35 minutes without preparation. Regulatory framework coverage spans 17 frameworks across EU, US, CH, and UK jurisdictions including DORA, GDPR, NIS2, EU AI Act, eIDAS 2, FINMA Circ.2023/1, BaFin MaRisk, FinCEN BSA, OFAC/CAATSA, FATCA, CRS, ISO 27001:2022, and SOC 2. Evidence export targets eight regulatory authorities (EBA, EDPB, ENISA, FINMA, BaFin, FCA, SEC, FinCEN) in authority-native formats (XBRL, XML, BSA E-Filing) via Dilithium-3-signed, SPHINCS+-sealed bundles with direct API transmission. The system is currently deployed in production as of 31 March 2026. Invariant status at publication: 6/7 HOLDING · INV-5 WARNING (AMD SEV-SNP PCR2 drift, remediation active, resolution within 72 hours). Keywords: machine law, pre-emptive compliance enforcement, admissibility vector, post-quantum cryptography, trusted execution environment, zero-knowledge proofs, bi-temporal ledger, DORA, GDPR, EU AI Act, cryptographic compliance, challenger provenance, regulatory technology, GRC, hardware attestation, CRYSTALS-Kyber, CRYSTALS-Dilithium, SPHINCS+, PLONK License: CC BY 4.0 Version: 1.2.0 DOI: 10.5281/zenodo.immo.quickCore.1.2.0

Sergey Abrahamyan

Abstract Zero-knowledge range proofs (ZKRPs) allow a prover to convince a verifier that a committed value lies in a given interval without revealing the value itself. Such proofs are widely used in financial applications and cryptocurrencies. This paper presents a new noninteractive ZKRP protocol derived from an order-revealing encryption (ORE) construction, enabling comparisons over encrypted data. The proposed protocol adapts a large-domain ORE structure to obtain an efficient range-proof mechanism and introduces a corresponding key-management/setup procedure. We discuss correctness, security considerations under standard ORE leakage, and provide performance and memory estimates.

Anubha Jain, Emmanuel S. Pilli, Raj Joshi

Threshold transactions in Bitcoin is an effective solution for vulnerability of wallets to the loss or compromise of secret keys. It also enhances the applicability of Bitcoin to include use-cases that require partitioning the trust among a set of parties. Currently, the threshold transactions on Bitcoin expose the actual signers within the group of participants. This poses a threat of wallet hacks or theft targeting these signers. To address this issue of privacy, we propose a novel protocol to create threshold transaction using a combination of on-chain locking and off-chain proof of knowledge. As Bitcoin currently does not support verification of zero-knowledge schemes, the proposed protocol uses a Trusted Third Party ( TTP ) to verify the proofs off-chain. The trust on the third party is only limited to its service of signing on behalf of the users. The main contribution is the development and applicability of a m-out-of-N proof of partial knowledge that maintains the privacy of the signers both on-chain from the transaction verifiers and off-chain from the TTP and other signers as well. The protocol leverages Taproot’s spending path flexibility to incorporate dual spending capabilities and employs off-chain zero knowledge Σ-protocols to prove knowledge of private keys without disclosing their associated public keys. Experimental analysis demonstrates improved scalability and privacy than the mainstream threshold signature schemes for Bitcoin. A formal analysis demonstrates and establishes the security goals of the proposed mechanism.

Dr.B.Swathi Dr.B.Swathi, PILLALAMARRI BHAVYA SRI, ODNALA SRICHARAN, AKUTHOTA PAVAN SAINAGAPURI MAHESHWARI · 5 authors

The current methods don't meet the security and performance needs of Internet of Vehicles (IoV) apps, and they also don't give the end user a low-latency, secure edge-computing service at the same time, while in the context of vehicles. This study presents a blockchain-enabled edge computing architecture that employs Double Deep Q-Network (DDQN) for reinforcement learning and lightweight Practical Byzantine Fault Tolerance (PBFT) for consensus, aiming to simultaneously enhance latency, energy efficiency, and security. The containerised architecture uses Hyperledger Fabric with Kubernetes to efficiently manage micro-services and move tasks off of them. In urban, suburban, and highway settings, the framework consistently outperforms baseline algorithms, with a 30–45% improvement in end-to-end latency and a 55% reduction in energy use under moderate to heavy loads. The system finished more than 95% of its tasks while keeping block consensus times under 1.2 seconds at peak loads. The architecture also showed consistent performance with different levels of vehicle density and used zero-knowledge proofs with attribute-based security to protect data from cyber threats from bad actors. These findings indicate that the integration of DDQN and blockchain will mitigate security issues in the Internet of Vehicles (IoV) by enabling secure edge computing for future vehicular networks.

Batuhan Karabay

This study investigates the rising security vulnerabilities in decentralized finance (DeFi) platforms from both technical and operational perspectives. Through literature review, case studies, and a comparative platform analysis, the research identifies the root causes, user impacts, and mitigation strategies for common security issues. Prominent incidents such as Ronin Network, Poly Network, Mango Markets, and Curve Finance are examined in depth, while security strategies of major DeFi platforms such as Aave, Compound, Uniswap, and Synthetix are compared. The study also discusses the implications of new technological developments like Ethereum Layer-2 solutions, Zero-Knowledge rollups, and account abstraction mechanisms on DeFi security. Findings emphasize that achieving a sustainable DeFi ecosystem requires a holistic approach involving not only technical safeguards but also transparent governance, user education and robust audit processes.

Dr.K.Rekhadevi Dr.K.Rekhadevi, NADIGOTTU POOJA, NALIGANTI THARUN, VALUPADASU PRANAY · 5 authors

The fast move toward sixth-generation (6G) distributed networks is making it possible to create highly dynamic, intelligent, and collaborative service environments for a wide range of use cases, including smart cities, autonomous systems, industrial IoT, immersive communication, and edge intelligence. But working together on a large scale in 6G environments comes with a lot of technical problems, such as the need for instant access to resources, coordinating different types of services, exchanging data that can grow, and making sure that security, trustworthiness, and privacy are all strong. Traditional centralised architectures have trouble meeting these needs because they have single points of failure, limited transparency, and problems with managing trust. Blockchain technology provides decentralisation, immutability, and the establishment of trust; however, its fundamental limitations in throughput and storage capacity impede its direct implementation in extensive 6G distributed collaboration systems. This paper presents a universal blockchain-based collaboration architecture specifically designed for 6G distributed networks, accompanied by an end-to-end collaboration mechanism aimed at delivering efficient, secure, and reliable resource-sharing functionalities. The proposed architecture combines service-oriented design ideas with adaptive blockchain improvements to get around problems with scalability. To address the throughput constraints of traditional blockchain systems, a service-oriented, capacity-adaptive blockchain sharding framework is proposed. In this framework, network nodes with different levels of consensus efficiency are dynamically split into different shards using a strategy that rates nodes based on their reputation. The assessment checks the performance of nodes by looking at things like their computational power, communication delay, reliability, and past behaviour. This is to make sure that shard formation is fair and reliable. Also, transactions are grouped by service type and sent to the right shards, which have the right level of consensus for the service. This service-aware transaction assignment makes sure that high-performance shards handle services that need to be processed quickly, while shards with moderate consensus capabilities handle services that don't need to be processed as quickly. This kind of adaptive alignment between service characteristics and shard performance greatly improves the overall throughput of the system and the efficiency of resource use. To make consensus even more efficient when workloads change, a load-sensitive Practical Byzantine Fault Tolerance (PBFT) mechanism is suggested for intra-shard consensus. The proposed load-aware enhancement dynamically changes consensus parameters based on shard load conditions, which is different from regular PBFT, which may slow down when there are a lot of transactions. This adaptive approach cuts down on communication overhead, makes the system more fault-tolerant, and keeps consensus performance stable even when many people are working together. So, the architecture makes sure that transactions are always valid while still meeting the ultra-low latency and high reliability needs of 6G apps. Along with throughput issues, storage scalability is still a big problem for blockchain-based systems because the ledger size keeps getting bigger. The paper proposes a hybrid storage policy that combines both on-chain and off-chain storage methods to get around this problem. To keep things immutable and trustworthy, important metadata, transaction proofs, and security-related records are kept on-chain. Large amounts of service data and information about sharing resources are kept off-chain using distributed storage solutions. Secure cryptographic connections between on-chain and off-chain parts make sure that data is accurate and can be verified without putting too much strain on the blockchain ledger. This mixed strategy greatly reduces the pressure on storage while keeping things clear and traceable. A lot of simulations are done to see if the proposed architecture and mechanisms are possible, can be scaled up, and will work better than other options. The results show that this new way of working together on a blockchain has a lot better throughput, less consensus latency, more balanced shard usage, and better storage efficiency than traditional blockchain-based collaboration models. Also, the proposed framework offers strong security guarantees and is resistant to bad behaviour in networks with different types of devices. In general, the suggested universal blockchain-based collaboration architecture is a scalable, secure, and adaptable way to make resource sharing in 6G distributed networks more efficient. The framework effectively solves blockchain scalability problems while also meeting the strict performance needs of next-generation distributed communication systems by combining service-aware sharding, load-sensitive consensus optimisation, and hybrid storage design. The results show that the architecture has the potential to be a key part of trustworthy and smart collaboration in future 6G ecosystems.

Garrett Greiner, Toshi Mowery, Pratik Soni

We present HyperVerITAS, a new zero-knowledge proof (ZKP) system for image provenance that enables scalable, efficient, and privacy-preserving verification of image transformations. HyperVerITAS builds upon the same minimal trust model as VerITAS (IEEE S&P '25), requiring trust only in the image source device, while treating the editing software as untrusted. Unlike VerITAS, which relies on FFT-intensive SNARKs and suffers from high memory overhead (up to 120 GB), HyperVerITAS leverages multilinear polynomial encodings over the Boolean hypercube to dramatically reduce both proving time and memory usage. Our design cleanly separates signature verification from image transformation, supports modular integration of multiple polynomial commitment schemes (including post-quantum constructions) and naturally extends to a wide range of affine image transformations. We implement HyperVerITAS with two distinct commitment schemes (Brakedown and multilinear KZG) and evaluate it on full-system pipelines involving cropping and grayscaling. On commodity hardware (Apple M3, 36 GB RAM), HyperVerITAS generates proofs for 33 MP images using only 27 GB of RAM and 6.6 minutes of proving time, whereas VerITAS fails to scale beyond 4 MP. These results establish HyperVerITAS as a practical and scalable ZKP system for secure and efficient image provenance.

Jiang Zehao, Xiong Jinbo, Huang Jiayi, Yuanyuan Zhang · 5 authors

Federated unlearning enables clients to withdraw their contributions from a global model.However, enabling clients to verify whether the server has honestly and effectively removed their contributions remains a critical challenge. To address this aspect, which has been largely overlooked in existing literature, a verification model based on zero-knowledge proofs was constructed, and a comprehensive framework for verifiable federated unlearning was proposed. Combined with a dynamically updated Merkle tree structure, a novel verifiable federated unlearning scheme was presented characterized by its zero-knowledge property. This allows for the efficient generation of cryptographic proofs for server unlearning operations while rigorously protecting the data privacy of other clients. We evaluate the effectiveness and computational overhead of the proposed scheme. Comparative experiments with Rivest-Shamir-Adleman (RSA) accumulator-based and Hash chain-based schemes demonstrate that, when the model parameter size reaches the order of <inline-formula><alternatives><math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="M2"><msup><mrow><mn mathvariant="normal">10</mn></mrow><mrow><mn mathvariant="normal">5</mn></mrow></msup></math><graphic specific-use="big" xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="alternativeImage/B6D6E598-14B1-468e-9A32-73199F9CD69E-M002.jpg"><?fx-imagestate width="4.23333359" height="2.53999996"?></graphic><graphic specific-use="small" xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="alternativeImage/B6D6E598-14B1-468e-9A32-73199F9CD69E-M002c.jpg"><?fx-imagestate width="4.23333359" height="2.53999996"?></graphic></alternatives></inline-formula>, the proposed scheme improves proof generation speed by approximately two orders of magnitude and verification speed by 13.2 times compared to the RSA-based scheme. Furthermore, it effectively avoids the scalability bottleneck of data linear growth in verification overhead inherent in Hash chain-based schemes.

Marsya Aulia Rizkita, Singgih Dwi Prasetyo

No abstract is available for this record.

Yue Wang, Lejun Zhang, Juxia Li, Ran Guo

No abstract is available for this record.

Muhammad Irwan Ariffin, Noor Hazrin Hany Mohamad Hanif

The transition to decentralized renewable energy systems has gained significant attention, particularly through peer-to-peer (P2P) energy trading models that enable direct energy transactions between participants. While these systems offer technological and economic benefits, challenges persist in terms of social equity, technological accessibility, and ethical considerations. This chapter adopts a qualitative methodology based on a comprehensive literature review and meta-analysis and uniquely integrates Islamic finance principles, such as fairness, transparency, and risk-sharing, into the evaluation of P2P energy trading models. Through a review of pricing determination techniques and Islamic financial frameworks, a conceptual model is proposed to align decentralized energy markets with ethical financial practices. The findings offer policy insights for regulators and stakeholders, particularly in Muslim-majority regions, to develop inclusive and socially responsible energy trading systems that balance economic growth, environmental sustainability, and ethical values.

Alvise Spanò, Lorenzo Benetollo, Michele Bugliesi, Silvia Crafà · 6 authors

As Distributed Ledger Technology and smart contracts continue to grow in popularity, there is increasing interest in developing more expressive programming abstractions for digital asset management, along with verification tools that ensure safety and correctness before deployment on blockchain platforms. Addressing this challenge, we introduce AlgoMove , a framework designed to improve smart contract development on the Algorand blockchain. While Algorand is widely recognized for its high performance, scalability, and secure consensus protocol, it still lacks high-level programming abstractions and strong language-based verification mechanisms. AlgoMove brings the Move language, renowned for its robust support for secure digital asset management, to the Algorand platform, adapting its abstractions to the underlying execution model. The result is a high-level, resource-oriented programming model that preserves the core principles of Move while adapting them to Algorand’s unique environment. We present a formal specification of AlgoMove and its encoding into TEAL, Algorand’s native assembly-level language, along with a proof of the soundness of this encoding. To demonstrate the practical value and expressive power of the framework, we provide a prototype implementation consisting of a Move-to-TEAL compilation system and an accompanying library for writing smart contracts. Beyond enhancing the Algorand smart contract ecosystem, AlgoMove is significant in its own right as part of a broader effort to bring advances in programming language theory and formal verification into the blockchain space. By balancing expressiveness, ease of use, and strong compile-time guarantees, we seek to meet the distinctive requirements of secure and reliable blockchain applications.

Visakha G, Mantok Yanlem, Arundhita Bhanjdeo, Lanvin Concessao · 5 authors

Limited financing for decentralised renewable energy (DRE) projects has driven interest in impact labels like Distributed Renewable Energy Certificates (D-RECs). This working paper examines their role in India, exploring market processes, stakeholder perspectives, and how such instruments can support scaling DRE systems.

Tamara S. Alakbarova, Parvin A. Abbasova, Samira B. Baratzade

In the study, cryptographic authentication approaches for ensuring secure automated access in Cyber-Physical Systems were modeled and examined. The proposed research analyzed the efficiency of three cryptographic models based on Public Key Infrastructure, Zero-Knowledge Proof, and Elliptic Curve Cryptography with the challenge-response mechanism. It was investigated how each model performs under varying latency, computational, and scalability conditions in smart grids, autonomous vehicle systems, and industrial Internet of Things environments. It was identified that the Elliptic Curve Cryptography model provides the best performance in real-time and resource-constrained scenarios. It was studied that the Zero-Knowledge Proof approach ensures higher privacy protection and stronger attack resistance compared to other models. It was defined that the Public Key Infrastructure model remains effective in structured networks but exhibits higher latency. It was established that simulation tools such as Matrix Laboratory and Network Simulator 3 confirm the reliability and reproducibility of results. It was developed a comparative framework that allows researchers to select optimal authentication methods for specific operational contexts. It was justified that hybrid approaches combining multiple cryptographic mechanisms can enhance both efficiency and resilience in Cyber-Physical Systems.

C Bagath Basha, Maddoju Pranay, Keesari Sai Charan Reddy, A Ravi Kiran

No abstract is available for this record.

Oksana Liashenko, Bogdan Adamyk, Oksana Adamyk

This paper examines the market maturation hypothesis in cryptocurrency markets through a three-stage analysis of the evolution of tail risk in Bitcoin (BTC) and Ethereum (ETH). Using daily closing prices from January 2015 to February 2026 for BTC (n = 4058) and November 2017 to February 2026 for ETH (n = 3015), we employ 365-day rolling windows—reflecting the continuous 24/7 operation of cryptocurrency markets—to trace the temporal dynamics of Value-at-Risk (VaR), Conditional Value-at-Risk (CVaR), and Maximum Drawdown (MDD). The empirical strategy combines (i) Newey–West trend tests on rolling risk metrics, (ii) regime-conditional analysis across market states (Bull, Bear, or Neutral) and volatility regimes (high/low uncertainty), and (iii) exceedance correlation analysis to capture asymmetric BTC–ETH tail dependence. The results are consistent with the market maturation hypothesis: all ten trend coefficients across both assets are statistically significant (p &lt; 0.001), with linear time trends explaining up to 46.8% (BTC VaR1%) and 67.5% (ETH VaR1%) of variation in rolling tail risk. Sub-period comparisons confirm economically meaningful declines—BTC VaR1% fell by 22.0% and ETH VaR1% by 26.6% between the early and late subsamples. However, maturation is markedly asymmetric across uncertainty regimes: tail-risk reductions concentrate in low-uncertainty periods, whereas BTC MDD in high-uncertainty regimes shows no significant improvement (+1.0%, p = 0.176). Excess correlation analysis reveals a persistent and widening downside asymmetry (ρ− = 0.847 vs. ρ+ = 0.246 at the 90th percentile), with late-period upper-tail correlation turning negative (ρ+ = −0.175 at the 95th percentile), implying that portfolio diversification within the cryptocurrency asset class remains illusory during market stress. These findings carry direct implications for institutional risk management, stress-testing frameworks, and prudential regulation of digital assets.