Over time, the security of traditional public-key infrastructures in blockchain systems and in decentralized applications is threatened by the rise of quantum-enabled adversaries.Due to incomplete protocol specifications, unclear validation semantics, and contradictory experimental reporting, it is challenging to apply lattice-based cryptography, which serves as a foundation for quantum-secure primitives, to blockchain-based AKE frameworks.For decentralized applications that use CRYSTALS-Kyber-768 as a lattice-based Key Encapsulation Mechanism (KEM), this study suggests a formally defined blockchain-enabled post-quantum authenticated key exchange and registration framework.The protocol links a public key registration based on a smart contract with an on-chain Groth16 zk-SNARK proof-of-possession verification, which makes for an efficient and authenticated public key registration that is replay-resistant, protects against key-substitution attacks, and establishes a safe session under a well-established adversarial model.To improve traceability, resolvability, and auditability, the suggested protocol separately identifies cryptographic assumptions, block chain consensus assumptions, smart contract validity semantics, and more.To allow for independent verification of the framework's operation, the complete message flows, contract-level validation rules, and on-chain/off-chain boundaries for interactive protocols are all clearly specified.The experiment was conducted on a private Ethereum Proof-of-Stake test network with 50 validators, a gas block limit of 60,000,000, and a block interval of 12 seconds.A set of tests, each consisting of 30 independent runs, was conducted to produce a total of 30,000 registration transactions for the same workload circumstances.The average end-to-end delay is 24.73 seconds, and the registration process includes an average of 275,555 gas.The actual interval of batch-finalization, which is the period between the first batch submitting a transaction and the last batch's finality confirmation in each round of experiment, was used to determine throughput.The throughput that results from running the experiment within the constraints of the blockchain restrictions is comparable to the theoretical, gas-limited processing speed of around 18. 1 tps.Additionally, the lightweight authenticated key exchange phase, which on the tested network settings, carried out about 41 complete bilateral exchange cycles every second, was also accomplished.The outcomes demonstrate that the post-quantum authenticated key establishment can be realistically incorporated into the blockchain-assisted infrastructure with the reproducible system-level behaviors, while maintaining provable proof-of-possession and preserving structured validation semantics.
Open access
Blockchain Technology Applications and Security
Cryptography and Data Security
Physical Unclonable Functions (PUFs) and Hardware Security
Kanan Huseynov, Ali Shahzaib, IstvÃĄn AndrÃĄs Seres, JÃĄnos Tapolcai
From a user's perspective, perhaps the most significant difference between traditional banking services and widely used blockchain-based financial systems is that, in the latter, transactions and, either directly or indirectly, account balances and transaction histories are publicly observable. Therefore, a growing number of cryptographic solutions have been proposed to add a privacy layer to such systems. However, the privacy that users actually obtain does not depend solely on the security of the underlying cryptographic protocol: user behavior, transaction amount patterns, and timing decisions can substantially reduce anonymity. In this work, we study behavioral leakage in cryptocurrency mixers, focusing on Railgun on Ethereum. We aim to heuristically estimate the probability that a given deposit and withdrawal transaction belong to the same user. We consider five sources of leakage: characteristic timing patterns, address reuse, proximity in the transaction graph induced by prior public transactions, amount fingerprints that preserve distinctive digit patterns across transaction values, and knapsack type matches in which groups of transaction amounts add up in revealing ways. Our results show that even cryptographically strong privacy systems may suffer substantial anonymity loss due to user behavior and transaction patterns. Our five heuristics are able to uniquely link 17.65% of Railgun withdraw transactions to deposit transactions. We also applied a knapsack solver algorithm that was able to produce a 3.42 bit median anonymity loss for withdraw transactions. This work contributes to a better understanding of the practical privacy limits of mixers and anonymity pools, and points toward safer usage practices and design principles.
As autonomous AI agents increasingly transact across organizational boundaries, a fundamental trust challenge emerges: how can an agent assess whether an unknown counterpart is trustworthy? The ERC-8004 protocol addresses this challenge with the first permissionless trust layer for AI agent economies, built around three on-chain registries for Identity, Reputation, and Validation. Despite its rapid adoption, the protocol has not been studied empirically, leaving it unclear whether the information it records provides a trustworthy basis for decision-making. To address this gap, we present the first empirical study of ERC-8004 across three chains: Ethereum, BNB Smart Chain (BSC), and Base, covering the period from protocol deployment through May 13, 2026. We crawl on-chain Identity and Reputation events, off-chain files, and x402 payment transactions. On the identity side, we find that most registrations are placeholders rather than active agents, with only a small fraction (3%, 4%, and 15% across Ethereum, BSC, and Base) exposing a valid ERC-8004 registration file with at least one live service endpoint. On the reputation side, we show that the Registry, as currently deployed, cannot function as a trust signal: values are not commensurable, feedback records are rarely grounded in verifiable interactions, and reputation can be manipulated at minimal cost. Consistent with these design weaknesses, we find that a substantial fraction of reviewers (73.5%, 59.2%, and 90.6% across Ethereum, BSC, and Base) exhibit coordinated Sybil behavior. After removing Sybil-flagged feedback, 15.8%, 77.9%, and 86.8% of rated agents, respectively, are left with no valid feedback. We then turn these findings into concrete recommendations for future revisions of ERC-8004. Our study yields actionable protocol-design implications and establishes an empirical baseline for research on AI agent markets.
Non Fungible Token (NFT) Industry has been witnessing 16 million dollar trade in recent times.The following is the development of the decentralized NFT marketplace divided into three principal phases: smart contract development on the Ethereum blockchain using Solidity, creation of the frontend using React.js,Next.js,Node.js,HTML, CSS, and JavaScript, and backend development using Express.jsand MongoDB.The aim of this project is to offer a transparent and safe digital marketplace to mint, buy, and trade NFTs.The project employs ERC-721 standards for the uniqueness of tokens, Web3.js for interaction with smart contracts, and off-chain metadata storage with the help of REST APIs and MongoDB.Results indicate that the marketplace functions securely and efficiently, with seamless user interaction and successful on-chain transaction execution.Challenges related to deployment cost, metadata storage, and smart contract gas optimization were addressed during development.The final product demonstrates a fully functional, scalable, and decentralized NFT marketplace platform.
The growing popularity of smart contracts on blockchain platforms in recent years has made the development of reliable verification techniques that ensure code is both logically correct and secure an urgent priority. One of the most effective methods adopted by existing tools is formal verification. This thesis addresses the problem of smart contract verification, particularly focusing on those developed for the Ethereum platform. It concentrates on using Constrained Horn Clauses (CHCs) as an intermediate formalism for representing and analysing program properties. Various verification tools were analysed and compared during the course of the work, particularly those based on CHCs, to identify practical limitations, methodological gaps, and opportunities for improvement. Based on this analysis, new tools and optimisations were designed and developed. On the one hand, we implemented CHCViz, a visualisation system that assists auditors and developers in inspecting and understanding CHCs generated by existing tools, such as SolCMC. On the other hand, a verifier for Yul code was built from scratch to extend the applicability of formal verification via CHCs to the recently released intermediate code from the Ethereum foundation.
Smart contracts deployed on blockchain platforms are immutable once deployed, making correctness and security critical concerns that have led to substantial financial losses due to vulnerabilities. A significant proportion of these vulnerabilities stem from human-written code rather than blockchain infrastructure or cryptographic primitives. This observation motivates a paradigm shift from manual code development to model-driven approaches that generate semantically correct smart contracts from formal specifications. This thesis presents EDAM (Enhanced Data-Aware Machines), a behavioural model for specifying smart contracts that balances expressiveness with tractability. The framework extends traditional data-aware finite state machines [3] with essential features for a wide range of smart contract applications: dynamic role-based access control enabling runtime role assignment and revocation, participant management supporting unbounded and varying participants, and explicit modelling of inter-contract interactions through call tries with success and failure handling. The formal semantics of EDAM are grounded in established techniques from behavioural type theory, process calculi, and finite state machine theory, enabling rigorous reasoning about contract behaviour. The thesis contributes a comprehensive toolchain that integrates modelling, code genera- tion, test generation, and validation in a unified methodology. We develop a code generation engine that automatically produces Solidity smart contracts from EDAM specifications. The generated code faithfully implements the formal model, ensuring that the behaviour established at the model level is preserved in the executable code. The code generation process uses an intermediate JavaScript Object Notation (JSON) representation, which enables platform-agnostic code generation with ongoing extensions to support additional blockchain platforms such as Aptos. We present an automated test generation methodology that produces executable test suites from EDAM specifications. The approach combines symbolic trace generation using the formal semantics implemented in OCaml with randomized exploration of the Finite State Machine (FSM) network, enabling concrete trace derivation through random value assignment and Satisfiability Modulo Theories (SMT) constraint solving. This methodology systematically explores the state space to generate traces that exercise transitions, guards, and role constraints, producing executable test suites for standard testing frameworks such as Hardhat. The process is fully automated and can be integrated into the development workflow. Our evaluation demonstrates the expressiveness and practicality of the approach through a diverse benchmark of smart contracts, including contracts from the Azure repository [148], standard token contracts (Ethereum Request for Comments 20 (Token Standard) (ERC20)), Decentralized Finance (DeFi) protocols (Automated Market Makers (AMMs)), and multi- coordinator systems. The evaluation demonstrates expressiveness through the modelling of essential features, showing that the approach is able to model a wide range of smart contract features. The validation methodology employs a multi-faceted approach that combines code coverage analysis, mutation testing to validate the correctness of the generated code and the effectiveness of the test suites, and cross-validation by applying the generated tests to other established implementations. This cross-validation approach shows that our generated test suites are applicable to validate existing smart contract implementations, providing evidence of the quality and correctness of both the generated code and the testing methodology. The results empirically indicate that our model-driven approach produces contracts and test suites that preserve the structure and semantics of the formal model and can be applied to validate existing smart contract implementations. Unlike existing approaches that address isolated phases of the development lifecycle, EDAM provides an integrated toolchain that ensures consistency between specifications, vii generated code, and test suites. The framework shows that behavioural types provide a solid foundation for smart contract modelling and verification, enabling the development of unified frameworks that integrate modelling, code generation, test generation, and val- idation. Although our implementation targets blockchain platforms, the methodology is platform-agnostic and may generalise to other service-oriented and distributed architectures. The results show that model-driven approaches can produce high-quality smart contracts and comprehensive test suites, contributing to the advancement of secure smart contract development practices.
This paper investigates Ethereum-based smart contracts as a decentralized cybersecurity governance layer for Electronic Medical Records (EMRs). It addresses challenge of fragmented healthcare data silos and strict compliance requirements for electronic protected health information (ePHI), such as HIPAA and GDPR by analyzing how blockchain technology enables explicit, patient-centric access control. Current legacy systems often centralize authorization, creating vulnerablilities. Through topic analysis and a Solidity-based Proof of Concept (PoC), the study demonstrates a hybrid architecture that uses on-chain execution for permission management while storing sensitive clinical data off-chain. The PoC shows how immutable ledger entries enforce least-privilege principles, block unauthorized queries, and provide tamper-evident auditability. The architectureâs trade-offs between enhanced accountability, patient sovereignty, and practical limitations in scalability, governance, and costs are assessed. It concludes that while blockchain offers a robust trust layer, integration with off-chain interoperability standards remains essential for clinical adoption.
This paper underscores the vital role of blockchain technology in Industry 4.0, aiming to inspire researchers and industry professionals to recognize its transformative potential in creating decentralized, automated, and data-driven industrial settings. It explains core concepts, components, and varieties of blockchain systems, and assesses their uses across various sectors. The research delves into security and privacy issues, particularly relating to Ethereum platforms and smart contracts. It meticulously details common vulnerabilities of smart contracts and their implications for industrial systems. A critical comparison of existing vulnerability-detection techniques reveals current limitations. The paper also investigates the potential of artificial intelligence to enhance security analysis in blockchain contexts, systematically reviewing machine learning and deep learning strategies for identifying smart contract issues. A novel detection framework is introduced and tested against real-world datasets, showing improved accuracy and robustness compared to traditional methods. Ultimately, the paper aims to foster the development of secure and trustworthy blockchain infrastructure for applications in Industry 4.0.
Blockchains are distributed ledgers that let mutually distrustful parties agree on an append-only transaction history without relying on a central authority. By combining cryptographic hashing, digital signatures, and consensus mechanisms, blockchains provide tamper evidence, auditability, and agreement among nodes. Modern blockchain systems significantly vary in consensus design (e.g., Proof of Work, Proof of Stake, Proof of Author- ity, and Byzantine Fault Tolerance mechanisms), access model (open vs. permissioned), and execution layers (from simple asset transfers to expressive smart-contract virtual machines). The related architectural choices shape decentralization, fault tolerance, and the attainable latency-throughput envelope. As blockchain deployments expand to payments, tokenization, decentralized finance, supply chain traceability, and digital identities, comparing these systems has become an urgent necessity. Unfortunately, rigorous blockchain evaluation remains difficult. On the one hand, measurements are confounded by fluctuating network conditions, heterogeneous infrastructures, and rapidly evolving software. On the other hand, results are too often collapsed to a single number (such as transactions per second) without dispersion or methodological details; economic assessments of crypto-assets lack a unified and interpretable index that captures the balance of core economic parameters and their trade-offs (usage, liquidity, stability, and security) rather than market price sentiment; and experimental studies rarely address the dimensions of experimental repeatability (same setup, same results) and performance predictability (stable expectation). The consequence is an evidence gap: how to assess and compare the efficiency of blockchains â spanning performance, energy, economics, and result stability â in different scenarios? This dissertation aims at reducing this gap with a coherent yet modular approach that combines topology-controlled benchmarking with an orthogonal, entropy-based economic analysis, delivering four contributions. First, it introduces Lilith, a system-agnostic benchmarking framework that couples workload generation with network emulation to run controlled, repeatable experiments under explicit overlay topologies (i.e., the logical peer- to-peer connectivity graphs) and link properties such as latency, bandwidth, and packet loss. Lilith orchestrates deterministic deployments (pinned artifacts, controlled boot order, and CPU core pinning and memory binding), integrates power probes, and provides a uniform client interface; this underpins a comparison based on typical performance metrics. Second, Lilith is employed to quantify blockchain energy consumption under realistic conditions. Third, Lilith is adopted for a network-controlled, multi-run measurement campaign to produce a public dataset. By combining dispersion metrics (e.g., worst-case deviation) with analysis of variance and intraclass correlation, we quantify run-to-run variability and performance predictability across blockchains, topologies, workloads, and node-set sizes. Fourth, in addition to Lilith, the dissertation introduces the Entropy Balance index (EB-index), which aggregates heterogeneous on-chain indicators into a single, interpretable score of economic efficiency. ii As for the first three contributions, we set up the experimental baseline by considering five network topologies (fat-tree, full mesh, hypercube, scale-free, torus) and five industry- grade blockchains (Algorand, Diem, Ethereum Clique, Quorum IBFT, Solana), exercised with transfer transactions and smart-contract workloads (DDoS, FIFA, GAFAM, gaming, PayPal, VISA) across two node-set sizes (10 and 40). In the performance study, the network topology emerges as the primary factor de- termining throughput and latency. Full mesh, hypercube, and torus deliver higher performance under heavy load. The performance of Algorand and Diem is stable with respect to topology changes, while Ethereum is less sensitive but remains slower. In the energy study, fat-tree and full mesh turn out to be the most energy-efficient topologies, especially at high load. Algorand and Diem exhibit the lowest energy per transaction, Ethereum Clique the highest across topologies; Quorum IBFT and Solana become costlier as workload intensity and network size increase. The experimental repeatability and performance predictability study shows low per- formance variance (transactions per second, block latency, energy consumption) for Algorand and Diem and pronounced sensitivity for Solana and Quorum IBFT, especially as workloads, node-set size, and geo-latency conditions vary. The released dataset and the accompanying analysis templates, which are based on clusters instead of public-cloud testing, enable thorough checks that go beyond point estimates by quantifying dispersion and confidence in comparative results. Finally, in the economic study, the EB-index aggregates heterogeneous on-chain indicators â such as user activity (transactions, active addresses), token distribution (balance concentration), and supply turnover/velocity â by using the normalized Shannon entropy and its weighted BelisĖ§-GuiasĖ§u variant. When applied to the capitalization-based leading crypto-assets Bitcoin, Ethereum, Ripple, USD Coin, Dogecoin, and Cardano, the EB-index separates volume-driven bursts from structurally balanced ecosystems and reveals differences that price, total value locked, or raw activity may blur. Overall, this dissertation delivers a topology-aware blockchain benchmarking frame- work, empirical evidence that network structure materially affects performance and energy, a public multi-run dataset together with analysis templates that promote experimental repeatability and performance predictability, and an entropy-based index for assessing economic efficiency.
The increasing adoption of decentralised technologies, such as blockchain, is reshaping the way distributed systems are used and, in particular, how digital and physical resources are represented and managed. While tokenisation techniques have enabled the representation of unique and verifiable artefacts on the blockchain, Non-Fungible Tokens (NFTs), the most popular standards used to encode them still provide limited support for those resources that need to change over time. Updates to their content are handled through poorly structured, weakly regulated, and often opaque mechanisms, making it difficult to model assets whose lifecycle requires controlled modifications, and verifiable state transitions. This thesis addresses these limitations and introduces a conceptual and operational framework for the structured, controlled, and traceable man- agement of asset mutability within blockchain-based ecosystems running on Ethereum-compatible platforms. The proposed approach formalises the mu- tability of asset attributes, defines an explicit model for updates, and inte- grates on-chain authorisation mechanisms to ensure that every modification, every transfer and every minting operation is performed in accordance with predefined policies and in a permanently verifiable manner. The thesis defines update-control rules, more fine-grained metadata rep- resentations, and coordination schemes that enable creators, owners, and authorised actors to collaborate safely on the modification of a resource. The validity of the framework is assessed through the application of real use cases and simulation tools that analyse performance, costs, and behavioural properties, as well as the long-term sustainability in the blockchain across different scenarios. The results show that a more precise and structured treatment of muta- bility significantly enhances the expressiveness, reliability, applicability, and, iii most importantly, the intrinsic value of blockchain-based asset representa- tions. This provides a more realistic and flexible management of the lifecycle of digital resources, while opening new directions towards future develop- ments in areas such as decentralised identity, cross-chain interoperability, and distributed collaborative systems.
Mohammed Benseddik, Benjamin Kraner, Claudio J. Tessone
Ethereum's beacon chain hosts over 920,000 active validators, a number inflated by the legacy 32 ETH stake cap. The Pectra upgrade (May 2025) addresses this by introducing 0x02 compounding validators, raising the maximum stake per validator from 32 to 2,048 ETH and enabling automatic reward reinvestment. This paper examines how compounding affects consensus-layer rewards, whether higher balances provide execution-layer advantages, and whether the APR uplift justifies migration for different staker types. We analyse adoption patterns across solo stakers and staking providers, investigate the role of consolidation (merging multiple 32 ETH validators into one) in early migration, and identify barriers slowing the transition. Through simulation, we find that compounding provides roughly +5% relative consensus-layer APR uplift for small balances, diminishing to under 1% for large staking providers. Empirical analysis of all active beacon chain validators shows 0x02 validators achieving modestly higher median CL APR. Solo stakers show higher relative adoption but face operational barriers, whilst providers cite infrastructure costs and protocol constraints. The results suggest that without improved reward accessibility and stronger economic incentives, 0x02 migration will remain gradual despite its network efficiency benefits.
Valerio Mandarino, Giuseppe Pappalardo, Emiliano Tramontana
Authentication is essential to hold users accountable across online services. Conventional authentication systems rely on centralized architectures or third-party identity providers, which, however, introduce single points of failure, privacy concerns, and limited user autonomy. Conversely, fully decentralized authentication frameworks often struggle to provide reliable identity attestation mechanisms. This makes them vulnerable to Sybil attacks and self-asserted claims, while limiting their interoperability with trust-based systems. This paper presents dAuth, a hybrid blockchain-based authentication architecture based on Ethereum smart contracts to provide cryptographic tokens that enable authentication to services. These tokens, anchored to the smart contract, are derived by users from institutionally certified base credentials issued by an accredited verifying authority and enable authentication to services without further involvement of the authority. Each token is cryptographically bound to a specific service, constrained in scope and duration, and verifiable off-chain through data and cryptographic commitments provided by the user. No plaintext personal information is published on-chain: identity attributes are committed as cryptographic digests, which anchor certified identity data on-chain while keeping the underlying personal information private and auditable. This design removes the verifying authority from the authentication process, as all authentication steps are assisted by the user-controlled smart contract. The verifying authorityâs role is limited to initial identity certification and exceptional update procedures. The result is a privacy-preserving and verifiable hybrid authentication framework that leverages the cryptographic security properties of the underlying blockchain infrastructure and inherits its scalability characteristics. The proposed design has been implemented and experimentally evaluated on the Ethereum platform, addressing public blockchain-specific challenges such as scalability constraints and transaction costs to ensure practical deployment.
Ethereum Layer 2 (L2) rollups improve scalability but expose a trade-off between fast sequencer soft finality and slow Layer 1 (L1) settlement finality, limiting latency-sensitive applications that require timely and durable guarantees on transaction ordering. We introduce a Byzantine Fault Tolerant (BFT) finality layer that extends existing rollup architectures without requiring L1 or rollup protocol changes. This layer provides deterministic transaction-level finality ahead of L1 settlement by committing to the sequencer's transaction order, bridging the gap between soft and hard finality. At its core, the layer uses a 1-chain variant of the Jolteon consensus protocol, adapted to the rollup setting where a single sequencer determines transaction ordering. Experiments show sub-second committee finalization latency and stable performance under Byzantine faults.
Ethereum account classification is essential for identifying individuals engaged in illicit transactions and analyzing behavioral patterns across various account types. This process serves as a critical mechanism for monitoring and regulating unlawful activities within transactional markets. However, the Ethereum network exhibits the characteristics of a complex heterophilic graph which poses significant challenges to the effectiveness and performance of conventional graph neural networks (GNNs). To address this challenge, the present study proposes FSGCN(Fourier-Sage GCN), a novel architecture for heterophilic graph neural networks (GNNs) that integrates KolmogorovâArnold Networks (KANs) with GraphSAGE. FSGCN is specifically designed to adapt efficiently to the structural complexity of heterophilic graphs. By leveraging KANs to extract high-order neighborhood information and employing GraphSAGE to capture low-order neighborhood patterns, FSGCN effectively aggregates both homophilic and heterophilic features, thereby improving classification performance. Furthermore, to improve training efficiency and generalization, we propose the MLPInit weight initialization scheme and the DropEdge graph augmentation technique. Experiments on a large-scale Ethereum transaction dataset show that FSGCN achieves an F1-score of 91.8% and a classification accuracy of 91.6%, significantly outperforming traditional homophilic and heterophilic GNN baselines. Additionally, FSGCN demonstrates high training efficiency, completing each epoch in just 2.302 s per epoch and improving overall training speed by 130.4% compared to conventional GraphSAGE.
Gossipsub is the primary peer-to-peer dissemination protocol used by large-scale Web3 systems such as Ethereum, Filecoin, and IPFS. Despite its widespread deployment, the choice of its key parametersâthe eager mesh degree D (number of peers that receive messages eagerly) and the gossip degree Dlazy (number of peers periodically notified via gossip)âhas largely relied on heuristics, with little quantitative guidance. Consequently, production networks lack a principled understanding of the delivery rate, bandwidth cost, and latency tradeoffs induced by these parameters.
Ayei E. Ibor, Denis U. Ashishie, John Adinya Odey, Bassey Ele · 5 authors
ABSTRACT Elliptic curve cryptography ( ECC ) underpins the security of most blockchain systems, yet its practical implementations face numerous vulnerabilities. In this systematic literature review ( SLR ), we catalogue and analyze attacks on ECC in the context of blockchain security, including sideâchannel attacks, nonce/ PRNG failures, cryptanalysis, and implementation flaws, and we survey proposed countermeasures. We follow rigorous SLR methodology with defined inclusion/exclusion criteria, search strategies across databases such as IEEE Xplore, ACM , Scopus, Web of Science, and clear data synthesis, ensuring replicability. Emphasizing empirical case studies and realâworld exploits, we discuss instances where ECC weaknesses led to blockchain breaches including biased elliptic curve digital signature algorithm nonces exposing Bitcoin/Ethereum private keys, smartphone power analysis revealing wallet keys, and Trezor hardwareâwallet key extraction via singleâtrace sideâchannel analysis ( SCA ). We tabulate known attack vectors versus affected systems, and similarly compare countermeasure techniques such as hybrid classical/quantum schemes, threshold signatures, and zeroâknowledge proofs, along with implementation tradeâoffs. We evaluate advances such as Curve25519/ EdDSA and ARM SVE2 to mitigate sideâchannel leakage. Our findings highlight that practical security of blockchain cryptosystems depends on correct ECC implementation and emerging cryptographic upgrades, not merely on the mathematical hardness of the elliptic curve discrete logarithm problem.
Academic research indicates an urgent need for safe, tamper-proof storage of sensitive medical information due to the rapid digitalization of healthcare data. Traditional systems are susceptible to both internal and external assaults because of their dependence on centralized servers. SEC-HEALTH implements a system for the secure storage of electronic health records (EHRs) by combining the immutable, distributed ledger technology of blockchain with the InterPlanetary File System (IPFS).This system use Solidity smart contracts to archive patient data and transaction records on the Ethereum blockchain. Comprehensive EHR files are preserved on IPFS and may be accessed via their blockchain hash addresses. The architecture guarantees data integrity, transparency, and safe access independent of trusted third parties.User modules include appointment scheduling, prescription management, patient and physician authentication, and platform registration. The graphics illustrate a fully operational web interface created in Python, implemented smart contracts, and the integration of blockchain with IPFS. The approach is resilient and decentralized, providing an alternative to traditional centralized health data management systems.
We study the evolution of transaction speed and fees from January 2024 through March 2026, comparing Ethereum Mainnet and its Layer 2 (L2) networks, as well as Solana and Polygon. Ethereum has undergone upgrades that have increased block size and blob count. These upgrades have doubled transactions per second (TPS) on both the Mainnet and the L2 networks. Mainnet median fees have fallen from over \$2 to under \$0.02, and L2 median fees have fallen more than 95% from \$0.05 to \$0.0015. We forecast that Mainnet median fees will converge with Solana in August 2027, but TPS will remain below 100 until 2034. The L1 Strawmap, proposing EIP-7938, a potential exponential increase in the gas limit, brings the Mainnet to only 100 TPS in January 2028. With continued blob expansion, L2s will surpass Solana TPS in March 2029 and have lower median fees by October 2026.
The Global Alliance for Genomics and Health (GA4GH) Beacon protocol lets researchers ask whether a genomic variant has been observed in a participating cohort and receive aggregate variant-level counts. As Beacon networks grow, two privacy risks remain: host institutions can see plaintext queries, and repeated rare-variant queries can support membership-inference attacks. We present bioETH-Beacon, a smart-contract prototype that runs the Beacon "aggregate count" query over encrypted data on a fully homomorphic Ethereum Virtual Machine (fhEVM). Hospitals upload encrypted marker-count entries, authorized researchers submit encrypted marker queries, and the contract returns an encrypted answer that is released, via an off-chain key-management service, only to the requester named in the contract's on-chain ACL. The design is organized as a 3x4 tier-by-query-family grid spanning genotype, sex, age, and phenotype queries, with tiers that trade stronger confidentiality for lower query cost. For genotype paths, the prototype can add bounded on-chain noise to mitigate probing attacks. Experiments on synthetic panels derived from a Polygenic Score (PGS) catalog show the expected scaling behavior and demonstrate that pre-aggregation can substantially reduce query gas when public marker presence is an acceptable trade-off. Overall, bioETH-Beacon provides a research prototype for confidential Beacon-style genomic querying without a trusted compute evaluator.
This study empirically aims to analyze the impact of primary monetary policy stance and transmission mechanisms of the European Central Bank (ECB)âsuch as the total assets of the ECB, long-term interest rate based on the government bond yields, and the EURUSD exchange rateâon major volatile cryptocurrencies like Bitcoin and Ethereum, as well as the leading stablecoin Tether. To this end, the study employs the linear Autoregressive Distributed Lag (ARDL) and the Bootstrap ARDL (BA-ARDL) procedures, robust approaches with limited data in time series analysis. The dataset consists of monthly data over the period from January 2019 to December 2025. We summarize the novel and robust primary empirical results of our study as follows: First, (i) it is revealed that the ECBâs balance sheet expansion has encouraged Bitcoin and Ethereum, yet has also, to a limited extent, suppressed Tether. Secondly, (ii) while the ECBâs long-term interest rate negatively impacts the prices of Bitcoin, Ethereum, and Tether, the negative impact on Tether is relatively weaker. Finally, (iii) the EURUSD exchange rate positively affects Ethereum, while its effect on Bitcoin is not statistically significant. On the other hand, at a 10% significance level, EURUSD has a weak negative effect on Tether. In conclusion, the empirical evidence demonstrates that the primary monetary policy stance and transmission mechanisms of the ECB influence the leading digital assets in distinct ways. Taking our findings into account is crucial for designing the digital euro in terms of financial stability and regulatory framework. Finally, we offer sound policy implications for the ECB based on empirical findings.
Bhutan's GovTech Agency Secretary Jigme Tenzing confirmed that migration of all 800,000 Bhutanese citizens' identity credentials to Ethereum was completed by Q1 2026. King Jigme Khesar Namgyel Wangchuck Prime Minister Tshering Tobgay and Ethereum co-founder Vitalik Buterin attended the launch ceremony. Ethereum protocol governance is conducted by the Ethereum Foundation and decentralised developer community without Bhutanese constitutional participation or veto authority. Bhutan's constitution enshrines Gross National Happiness as a governance mandate. The National AI Strategy 2025 requires AI systems to align with GNH principles. No Bhutanese governance document specifies the constitutional command layer ensuring that Ethereum protocol changes cannot override Bhutanese constitutional governance of national identity infrastructure. When Ethereum upgrades affect how 800,000 citizens' credentials are verified the GovTech Secretary receives advance notice but has no published mechanism to refuse changes incompatible with Bhutanese constitutional requirements. This paper documents the structural gap between Bhutan's GNH constitutional mandate and the sovereign command architecture required to make that mandate technically enforceable over identity infrastructure governed externally.
Gas metering on EVM-compatible blockchains assumes that execution conditions are stable: that the resource mix is constant enough to justify collapsing execution costs into a single scalar with fixed relative prices, and that state drift between submission and execution does not materially alter a transaction's outcome. We measure the extent to which this assumption fails. We present a trace-level measurement study of EVM workloads on Ethereum (L1) and Base (L2) throughout 2025, sampling 3,000 blocks per day per chain. We decompose each transaction into opcode-level execution gas, intrinsic gas, refunds, and persistent state deltas. To measure state sensitivity, we re-execute transactions from September 2025 on older states and record how gas usage and storage access patterns change. We find the resource mix to be far from stable: on Base, storage reads and compute account for 29.2% and 24.3% of execution gas, while Ethereum devotes 34.9% to storage writes. Ethereum's gas limit doubling during 2025 shifted its own profile toward compute-heavier, Base-like patterns. Base also exhibits a higher fraction of cold storage reads (49.7% versus 39.6% on Ethereum). Persistent state growth, a permanent cost priced as a transient one, reaches 456 GB on Base versus 38 GB on Ethereum. Execution outcomes are equally unstable: gas estimates vary across nearby historical states for 46.0% of transactions on Base, compared to 13.9% on Ethereum, with especially high sensitivity for MEV and DeFi activity. Storage access patterns also diverge across states, limiting the effectiveness of access lists and complicating parallel execution. Our work provides an empirical foundation for multi-dimensional gas metering and explicit pricing of state growth. They show that state-sensitive execution behavior complicates workload estimation, directly affecting transaction predictability and user experience.
The digitization of financial markets has produced two classes of platforms that price, in principle, the same state - contingent payoffs: centralized crypto-option exchanges and blockchain-based prediction markets. This paper provides the first option-implied benchmark test of prediction-market pricing for cryptocurrency threshold contracts. For each hour in a matched sample, we compare the Polymarket Yes price with the discounted risk-neutral binary value implied by a listed Binance call option on the same underlying, strike, and maturity, and study the gap between them. In the main September 2023 Bitcoin contract, the mean pricing gap equals 5.6 percentage points across 214 hourly observations (t = 6.46, p < 10^{-9}). Pooling three Binance-compatible Bitcoin threshold markets yields a mean gap of 6.3 percentage points across 287 observations, robust to HAC and block-bootstrap inference. The gap is persistent - with an AR(1) half-life of roughly four hours - yet mean-reverting, consistent with slow information transmission between segmented venues rather than mechanical noise. Cross-sectional regressions reveal that the wedge is largest at low option-implied probabilities and long maturities, a pattern consistent with speculative demand for prediction-market contracts rather than measurement error. A delta-hedged arbitrage proxy remains profitable after conservative transaction costs, though with marginal statistical precision. A Deribit extension on the same three Bitcoin contracts produces a larger pooled gap of 11 percentage points, while a smaller Ethereum exercise yields mixed evidence. The results demonstrate that digital fragmentation of financial markets generates systematic, persistent pricing wedges even for economically identical payoffs.