Rabib Jahin Ibn Momin, Ahmed Mahir Sultan Rumi, Rezwana Reaz
Academic examination systems worldwide continue to rely on centralised, opaque record-keeping that is often vulnerable to credential forgery, result tampering, examiner bias, and the absence of transparent re-evaluation pathways. Existing blockchain-based approaches in education focus predominantly on post-hoc certificate storage or online-only examination portals, leaving the complete onsite examination lifecycle, from conducting exams through scrutiny, largely unaddressed. This paper proposes ParikkhaChain, a blockchain-based framework that covers the entire examination lifecycle of an onsite examination system with three distinguishing contributions: (i) anonymous script evaluation through cryptographic hashing of answer scripts before examiner access, thereby eliminating identity-based bias; (ii) a transparent evaluation and scrutiny workflow backed by an immutable on-chain audit trail that records every mark submission and grade revision; and (iii) inclusion of privacy-preserving verification using zero-knowledge proofs and off-chain storage mechanisms. The system is architected around four Solidity smart contracts deployed on the Ethereum blockchain. The proposed architecture is the first initiative to our knowledge to support physical examination process, anonymous marking, and re-evaluation transparency. We successfully simulate full exam cycles of an onsite exam to grade-sheet generation using a working prototype on a large scale of 100 courses and hundreds of teachers and students. The experimental results show that the system can manage online examinations of hundreds of courses, students and faculties efficiently with great throughput, low storage, and transaction cost. Our codebase is available in open source form at https://github.com/AhmedRumi/CSE6608-ParikkhaChain
We present DSKAG-IT-SIG, a family of post-quantum transaction signature schemes that achieve computational existential unforgeability under adaptive chosen-message attack, built on the DSKAG deterministic key-derivation layer. The construction derives per-transaction MAC keys through DSKAG, a deterministic symmetric key agreement protocol requiring no key transmission, no handshake, and no public key infrastructure. We prove (Theorem 1) that for an adversary making q adaptive chosen-message queries, existential forgery advantage in standard mode is at most q * 2^{-128} plus the PRF distinguishing advantage of HMAC-SHA256, reducing to the pseudorandomness of DSKAG-derived keys and the PRF security of HMAC-SHA256 under a uniform key; the ideal-cipher-model analysis gives the same q * 2^{-128} bound in idealized form. We prove (Theorem 2) that cross-domain forgery advantage is at most 2^{-128} + epsilon_iso, reducing to the key-separation properties of DSKAG across policy domains. The construction is computationally secure and is not unconditionally secure. DSKAG key derivation is built on HKDF-SHA512 (RFC 5869) over HMAC and SHA-512, and the shared base is established once via FIPS 203 ML-KEM, so security reduces throughout to standard FIPS-based symmetric and hash primitives. The scheme's post-quantum security rests on symmetric and hash hardness for authentication and on lattice hardness for the one-time base alone: the construction presents no integer-factorization or discrete-logarithm structure, so Shor's algorithm has no target and does not apply, and the operative quantum attack is Grover search, which yields at most a quadratic speedup against the 256-bit HMAC-SHA256, SHA-2, and SHA-3 primitives and preserves a 128-bit quantum security level. Because buffer uniqueness derives from tx_seq monotonicity rather than hash collision resistance, the security argument does not depend on the collision property, the hash property most weakened by quantum search. Standard-mode signatures are 30 bytes, a 97.8% reduction versus Falcon-512 (666 bytes) and compatible with ISO 20022 SWIFT message fields without re-engineering. The NexusKey composite policy digest binds asset class, jurisdiction, KYC level, and chain identity into the key derivation path; policy bypass is cryptographically equivalent to key forgery. A four-layer UltraHonk zero-knowledge proof system (143,802 gates, no trusted setup, 16 KB proof) verifies policy compliance wherever policy is enforced, off-chain in governance, cloud, and payment-processing deployments, and, where permissionless public auditability is required, on-chain; the on-chain Solidity verifier is deployed on Ethereum Sepolia and Arbitrum Sepolia. Version 2.3. 18 pages, 8 tables. Changes from v2.2: concrete finite bounds replacing generic negl(lambda) in Properties 1 and 2; buffer uniqueness derived from tx_seq monotonicity (no SHA3 collision resistance dependency); explicit ideal cipher model and standard model dual framing for HMAC analysis; formal separation of empirical and theoretical claims.
Open access
2 source records
Cryptography and Data Security
Cryptographic Implementations and Security
Physical Unclonable Functions (PUFs) and Hardware Security
A central question of the Ethereum ecosystem is where Maximal Extractable Value (MEV)revenue originates and to what extent it stems from harming unsuspecting users. It is acceptable if MEV arises from arbitrages between centralised and decentralised exchanges (CEX-DEX). Yet theoretical models have significantly underestimated the scale of these arbitrages, while empirical studies have highlighted their importance - though these remain conservative estimates, constrained by numerous debatable heuristic assumptions. Revisiting the theoretical model, we found that CEX-DEX arbitrages require trading volumes on the order of the total activity of major liquidity pools and yield profits comparable to MEV. Most prior AMM models utilised the Black-Scholes (BS) stochastic differential equation (SDE) - i.e., geometric Brownian motion - and assumed continuous price trajectories where asset prices move in small increments only.We argue that BS underestimates arbitrage profits by ignoring price jumps, which are precisely the points at which arbitrage opportunities tend to arise. To address this gap, we present an extended discrete-time AMM model in which the price process is the sum of a diffusive component and stochastic jumps that can have arbitrary noise distributions. Although mathematically more involved this framework allows us to employ a general discrete-time SDE and compute the stationary probability distribution via function iteration with geometric convergence. We further prove that the resulting mispricing process is an ergodic Markov chain. We implement our model in C++, collect spot prices and AMM exchange data from the Ethereum blockchain and fit the model parameters to the observed prices. The estimates derived from our model closely match empirical observations and provide a natural theoretical explanation for several fundamental questions in the blockchain ecosystem.
O estudo investiga barreiras de usabilidade em aplicações de Finanças Descentralizadas (DeFi) executadas em redes compatíveis com a Ethereum Virtual Machine (EVM), mostrando que problemas de fluxo, terminologia e feedback comprometem a adoção, especialmente entre iniciantes. Para enfrentar essas limitações, o trabalho propõe uma interface de usuário aprimorada e a compara a uma versão não otimizada usando métricas de desempenho, número de cliques e o questionário NASA-TLX. Os resultados indicam que a interface melhorada elevou a taxa de conclusão de tarefas de 76% para 89%, reduziu os cliques excedentes de 221 para 186 e diminuiu a carga cognitiva global aferida pelo NASA-TLX em todas as seis dimensões avaliadas, com destaque para demanda mental e frustração, inclusive entre usuários experientes, que relataram maior fluidez e previsibilidade. O artigo conclui que refinamentos de usabilidade voltados para aplicações financeiras descentralizadas são determinantes para elevar confiança e adoção, recomendando a padronização de processos, mensagens menos técnicas e a redução de etapas críticas para mitigar a fadiga de operações e ampliar o alcance da Web3.
Products of MDS codes are of major practical importance; for a recent example, they are used in Data Availability Sampling (DAS) in blockchain networks such as Celestia and as part of the Ethereum roadmap. This motivates us to consider subcodes of such codes with the goal of obtaining a larger minimum distance. In this paper, we present explicit constructions of subcodes of Reed--Solomon product codes, along with bounds on their minimum distance. In particular, they achieve an optimal or near-optimal dimension--distance tradeoff. For component codes of dimension $r$, our construction requires a field whose size is bounded linearly by the overall product code length, and attains the maximum possible minimum distance for subcode dimensions $r^2-1$, $r^2-2$, and all dimensions at most $2r-1$. Furthermore, we establish a new upper bound on the minimum distance of subcodes of the product of two codes with identical parameters.
Massimo Bartoletti, Angelo Ferrando, E. Lipparini, Vadim Malvone
Smart contracts deployed on blockchains such as Ethereum routinely manage large amounts of assets, making their security critical. Empirical studies show that real-world attacks often exploit flaws in the business logic of contracts that unfold across multiple transactions, such as liquidity or front-running attacks. Detecting these attacks requires reasoning about expressive temporal properties beyond the capabilities of existing analysis tools. In this paper, we present an automated approach to the formal verification of smart contracts, enabling the specification and verification of complex temporal properties. Our approach provides a fully automated encoding into Lustre -- the specification language supported by the Kind 2 model checker -- of an expressive subset of Solidity contracts and temporal specifications based on first-order Hennessy-Milner Logic. This encoding allows us to leverage Kind 2 to determine whether the contract respects the specification or not. We implement our approach in a toolchain that integrates the translation and verification steps, and we evaluate its effectiveness and performance on a benchmark of smart contracts and temporal properties capturing complex attack scenarios. Our results show that the proposed approach can effectively verify non-trivial temporal properties of smart contracts and detect violations that are beyond the reach of existing analysis tools.
The frozen SUPT-CA phase-coherence probe (α = 0.01, zero free parameters) was applied to live blockchain data from Bitcoin, Ethereum, Solana, Cardano, and Polkadot. Consensus mechanism design directly determines geometric regime: deterministic hardware clocking (Solana, Polkadot) produces deep-lock distributions; regulated proof-of-stake with fee targeting (Ethereum, Cardano) produces coherence-zone distributions; probabilistic proof-of-work (Bitcoin) produces clutch-band timing with sub-floor transaction variability. A validated congestion oracle signal is identified for Ethereum: transaction count d_ij crossing 1.0 in a rolling 150-block window marks network congestion onset, confirmed against the May 2024 memecoin congestion event. All data from live public RPC endpoints, April 15, 2026. No parameters adjusted.
Alaa Alqaryuti, Haya Aljaghoub, Khaled Salah, Ahmad Mayyas
The growing adoption of Proton Exchange Membrane (PEM) fuel cell electric vehicles (FCEVS) has increased the need for secure, transparent, and verifiable certification and lifecycle tracking of hydrogen-related components. Current practices rely on fragmented documentation and centralized record-keeping, which creates risks of data manipulation, incomplete maintenance histories, and limited visibility for regulators and service providers. This paper introduces a blockchain-based framework that integrates decentralized storage, oracle-driven automation, and three interoperable smart contracts to manage stakeholder registration, component certification, vehicle assembly validation, and maintenance tracking. Implemented and evaluated in an EVM-compatible environment, the system enforces strict role-based access control, generates immutable audit trails, and automates both failure-based and mileage-based maintenance triggers using real-time inputs. A gas-cost analysis demonstrates that all contract functions operate at minimal cost under current Ethereum conditions, supporting the feasibility of real-world deployment. Overall, the proposed framework improves traceability, regulatory compliance, and operational accountability by enabling near real-time verification of certification records and reducing manual audit processing steps compared to traditional document-based certification workflows. • Blockchain ensures secure, tamper-proof FCEV component traceability. • Smart contracts automate certification, assembly, and maintenance. • Oracle triggers enable real-time, failure-, and scheduled service. • Framework improves compliance, transparency, and lifecycle oversight.
Open access
Blockchain Technology Applications and Security
Electric Vehicles and Infrastructure
Physical Unclonable Functions (PUFs) and Hardware Security
SHAIK SANA SHAIK SANA, N. SOUJANYA N. SOUJANYA, MOHAMMED MAJEED MOHAMMED MAJEED, BUCHI PAVITHRA BUCHI PAVITHRA · 6 authors
In the current digital era, social media platforms have become pivotal for individuals to express their opinions, political views, and product reviews. However, the centralized nature of traditional social media systems poses significant risks related to data breaches, server crashes, and single points of failure. To address these challenges, this paper proposes a novel approach to migrate from centralized to decentralized social media platforms by leveraging Blockchain technology. Blockchain ensures data immutability, decentralized storage, and enhanced security by distributing data across multiple nodes. Any tampering with data is immediately detectable due to the cryptographic linkage of data blocks through unique SHA-256 hash codes. The proposed system, named dTweets, enables users to post and view tweets securely using smart contracts written in Solidity and deployed on the Ethereum network. This decentralization prevents fraudulent users from spreading misinformation or unauthorized advertisements. Experimental results demonstrate that the proposed system achieves strong data integrity, tamper resistance, and transparent operation while maintaining acceptable transaction latency. This implementation provides a robust foundation for a secure and tamper-proof social media ecosystem. KEYWORDS : Blockchain, Decentralized Social Media, Data Security, Privacy Protection, Smart Contracts, SHA-256, Proof of Work, Distributed Ledger, Ethereum, Solidity, dTweets, Secure Data Storage, Web3.
DeFree is a unified Web3-enabled platform designed to integrate freelancing, event management, and real-time community communication into a single decentralised ecosystem. Traditional platforms often suffer from high commission fees, a lack of transparency, and centralised control over transactions. DeFree addresses these limitations by leveraging Ethereum-based smart contracts for trustless escrow payments, ERC-721 NFTs for secure event ticketing, and Socket.IO for real-time communication. The platform is built using React, TypeScript, Node.js, Express, MongoDB, and Solidity-based smart contracts deployed on the Ethereum Sepolia testnet. Experimental evaluation demonstrates efficient system performance with API response times under 250 ms and real-time messaging latency below 200 ms. The proposed system enhances transparency, reduces dependency on intermediaries, and provides a scalable solution for decentralised collaboration.
Gregorio Dalia, Tat Luat Nguyen, Andrea Di Sorbo, Corrado Aaron Visaggio · 5 authors
Ethereum smart contracts manage billions in digital assets, and vulnerability detection is critical given the immutability of deployed code and the irreversible nature of transactions. However, existing tools such as Slither rely on rigid, rule-based analysis, and general-purpose language models like ChatGPT often miss rare or context-dependent bugs. To address these limitations, this paper presents BreachT5, an ensemble of two fine-tuned CodeT5+ models designed for multi-label vulnerability detection in Solidity contracts. We first fine-tune a 220M parameter model on over 67,000 real contracts labeled with the Smart Contract Weakness Classification (SWC), revealing intrinsic detection differences across vulnerability types. We then explore the performance of a 770M variant, which improves accuracy on frequent classes but underperforms on rare ones. To balance this trade-off, BreachT5 combines both models via soft voting with per-class thresholds. Our results on the BCCC-SCsVuls2024 dataset show that BreachT5 achieves 0.556 Macro-F1 and 0.612 Micro-F1, outperforming the two standalone models, Slither, and GPT-5 in multi-label vulnerability detection.
Mohamad Kassab, Rabeya Zahan Mily, Valdemar Vicente Graciano Neto
We report a five-year, construct-preserving longitudinal replication of a 2020 empirical study of blockchain-engineer job advertisements, extended to a global 2025 cohort. Using mixed text-mining and expert-validated coding grounded in established competency taxonomies, we analyze 235 postings from 31 countries to examine how blockchain-specific, general technical, and soft-skill demands have evolved under an aligned measurement protocol. The findings indicate professional maturation from single-platform prototyping toward multi-chain, production-grade engineering that integrates back-end development, deployment operations, and security. Ethereum remains the most frequently cited platform, while Solana and other ecosystems increase platform diversity. Smart-contract development becomes a baseline expectation, with Solidity remaining central and Rust and Move becoming mainstream. Operational tooling such as cloud and containerization, alongside security-oriented practices including audits and zero-knowledge proofs, appears as recurring demand signals. Soft-skill mentions rise substantially, while formal degree requirements decline in favor of experience-based qualification. We contribute an updated 2025 competency atlas and empirically grounded implications for software engineering research, hiring, and curriculum design, while acknowledging comparability limits inherent to global sampling and cross-period labor-market conditions.
J. Rekha J. Rekha, N. Soujanya N. Soujanya, R. Sai Deepthi R. Sai Deepthi, S. Praveen Kumar S. Praveen Kumar · 6 authors
Cloud computing has revolutionized the way organizations and individuals store, process, and manage data by offering scalable and cost-effective solutions over the internet. However, despite its widespread adoption, cloud computing faces critical challenges related to data security, privacy, trust, and centralized control. Centralized cloud architectures are highly susceptible to cyber-attacks, unauthorized access, and data breaches, which can compromise sensitive information. To address these issues, this project proposes a blockchain-integrated cloud system called Cloud Chain, which leverages Ethereum blockchain technology to enhance security and trust in cloud environments.The proposed system utilizes smart contracts to automate access control and ensure secure data transactions. Blockchain provides an immutable and decentralized ledger, making it nearly impossible to alter stored data without detection. This system enables secure file storage, transparent data access, and efficient verification mechanisms. By integrating blockchain with cloud computing, the project enhances data integrity, reduces dependency on centralized authorities, and improves overall system reliability. The experimental results demonstrate that the proposed system provides a more secure and scalable solution compared to traditional cloud systems.
Traditional philanthropic frameworks often struggle with financial opacity and a relianceon centralized intermediaries, which frequently leads to an erosion of donor trust andsystemic mismanagement. This paper proposes a Decentralized Charity Fund ManagementSystem that mitigates these risks by encoding the complete donation lifecycle withinEthereum smart contracts, ensuring transparency and accountability by design. Utilizing agovernance model inspired by Decentralized Autonomous Organizations (DAOs), thesystem grants donors proportional voting rights based on their contributions, empoweringthem to collectively oversee fund disbursement. Capital is released to campaign organizersonly after a majority of donors approve specific withdrawal proposals, which must besupported by cryptographic expenditure proofs hosted on the InterPlanetary File System(IPFS). Additionally, the system features an autonomous refund mechanism that activatesif a campaign fails to reach its financial target by a set deadline, allowing for the directreclamation of funds without central intervention. Implementation via a React-baseddecentralized application (DApp) and validation through Hardhat-based testing confirmthat this frameowrk enforces all governance rules deterministically, effectively eliminatingthe need for centralized authority in the charitable ecosystem.
Hongxu Su, Mingzhe Liu, Jie Xu, Xiaohua Jia · 5 authors
ERC-4337, the Ethereum account abstraction standard, simplifies account management and transaction fee payment in decentralized applications by introducing programmable smart contract wallets and gas sponsorship via paymasters. However, its heavy reliance on on-chain validation and frequent state updates incurs substantial gas overhead, leading to performance bottlenecks and limiting scalability in large-scale deployments. To mitigate these issues, we propose GasLiteAA, a framework that optimize ERC-4337 by offloading paymaster logic to Trusted Execution Environments (TEE). GasLiteAA delegates the secure execution of stateful gas sponsorship logic and user quota management to TEE, enforcing validation rules off-chain while anchoring their integrity on-chain via lightweight cryptographic attestations. This verifiable offloading architecture significantly reduces on-chain computation and storage costs without sacrificing verifiability or decentralization. Experimental results demonstrate that GasLiteAA substantially lowers transaction fees, while remaining fully compatible with Ethereum Layer 1. By balancing security, efficiency, and deployability, GasLiteAA provides a practical and scalable approach to gas sponsorship for account-abstraction-based decentralized applications.
Internet of Vehicles (IoV) and IoT environment require decentralized platforms that can support a high number of transactions and provide high security and privacy assurance. This study suggests a reputation-aware, zero-knowledge proof (ZKP) based, dynamically sharded smart contract system that is able to process scalable and privacy-preserving transactions. The suggested architecture highly incorporates dynamic sharding, ZKP-based verification, decentralized smart contracts and reputation-based selection of leaders to jump over the scalability, trusting and performance limitations of traditional blockchain systems. There are also extensive experimental assessments that occur within 100-1000 transactions per second (tps) and batch sizes of 10, 30, 50, and 100. Findings indicate that the given framework demonstrates the ability to scale throughput linearly to about 1000 tps, and Enhanced Fabric and Ethereum reach throughput saturation at 140-150 and 15-20 tps, respectively. The proposed system has an average latency of less than 500 ms at an arrival rate of 1000 tps whereas at the same rate, baseline approaches have a latency of over 8000 ms with larger batch sizes. The success rate of the transaction is always above 97, which is due to the isolation of reputation and adaptive scheduling of shards. Moreover, the framework decreases 40-50% and 45-50% the computation overhead and the cost of communication respectively, over heavyweight baseline schemes. These results show that the synergistic implementation of ZKP, dynamic sharding, decentralized smart contracts, and reputation-aware control are a scalable solution with high throughput IoT and IoV applications that is efficient and secure.
Cheri Venkata Sai, Gurijela Pavan, Pittala Abhirameshwar, S. Suma
These come hand in hand with unprecedented levels of complexity in copyrighting and mon- etizing creations. In general, this protects the copyrights under the existing framework, which are cen- tralized, expensive, and beyond the reach of any independent creator. This paper presents an innovative blockchain-based framework for image copyrighting and social crypto monetization by using blockchain technologies such as Ethereum smart contracts and the InterPlanetary File System (IPFS). The proposed framework enables creators to publish digital images, calculate cryptographic proofs of image ownership with the SHA-256 hashing algorithm, store images in IPFS, and record metadata into the blockchain with unchanged timestamps. In addition, the platform supports “Like to Earn”, where public engagement for viewing is translated directly into rewarding creators with cryptocurrencies via smart contracts. The proposed framework adopts Web3 technologies to enable secure signing of all transactions with fraud prevention using the Elliptic Curve Digital Signature Algorithm (ECDSA) technique through MetaMask wallet authentication. Experimental evaluation of the proposed framework confirms that it can remove duplicate uploads, promptly verify image ownership, and enable social monetization of cryptocurrencies in a secured way.
Open access
2 source records
Blockchain Technology Applications and Security
Advanced Steganography and Watermarking Techniques
Type of the article: Research ArticleAbstractCryptocurrency markets are highly volatile, making price prediction a complex yet essential task for investors, financial engineers, and institutions. The purpose of this study is to evaluate whether Bayesian optimization of technical indicator parameters significantly improves the forecasting performance of Long Short-Term Memory (LSTM) models compared to baseline configurations. The study used daily Bitcoin and Ethereum price data from January 2016 to September 2025. Six technical indicators representing trend, momentum, volatility, and volume-based technical indicators are constructed and dynamically optimized through Bayesian optimization. The optimized indicators are then used as inputs to an LSTM forecasting framework. The study found that the baseline LSTM model achieved moderate predictive accuracy, where Ethereum outperformed Bitcoin. After optimization, both models exhibited improved performance, reducing the forecasting error for Bitcoin by 36.4% and for Ethereum by 12.2%. LSTM model with Bayesian optimized indicators showed a higher forecasting accuracy as compared to the baseline model, with 32% and 18.6% improvements for Bitcoin and Ethereum, respectively. These findings suggest that combining optimized technical indicators with LSTM models enhances predictive power in cryptocurrency markets. The approach offers a robust forecasting framework for traders, analysts, and algorithmic systems in high-volatility environments.Acknowledgment“This work was funded by the Deanship of Scientific Research, Vice Presidency for Graduate Studies and Scientific Research, King Faisal University, Saudi Arabia [Project No. KFU261690].”
P. Subramanya Sai, Bhukya Niranjan, Akula Tejaswini, A Varshitha · 5 authors
The exponential increase in digital data exchange and online communication has intensified the need for secure, transparent, and dependable file-sharing systems. Critical information such as financial records, healthcare data, confidential documents, and research outputs is frequently transmitted across distributed networks, where conventional centralized storage models introduce significant vulnerabilities. These traditional systems rely on single-point control, making them prone to data breaches, unauthorized access, service disruptions, and integrity violations. Furthermore, they lack transparency and robust audit mechanisms, raising concerns about data reliability and trustworthiness during storage and transmission. To overcome these limitations, this work proposes a decentralized and secure file-sharing framework that integrates blockchain technology, the Inter-Planetary File System (IPFS), and cryptographic techniques. The system ensures data confidentiality by encrypting files using the Elliptic Curve Integrated Encryption Scheme (ECIES) before storing them in the distributed IPFS network. Instead of placing the actual data on-chain, only essential metadata including file hash, ownership details, timestamps, and access permissions is maintained within a smart contract on the Ethereum blockchain. This design guarantees immutability, traceability, and protection against tampering, while enabling fine-grained access control. In addition to secure storage, the framework incorporates ChaCha20-based symmetric encryption to evaluate and compare computational performance with asymmetric methods. The combination of decentralized storage, cryptographic security, and immutable ledger technology eliminates reliance on centralized authorities, thereby reducing single points of failure and enhancing system resilience. The proposed approach ensures that only authorized entities can access and decrypt shared content while maintaining transparency of file transactions.
Peer-to-peer (P2P) payments facilitate rapid direct transactions but are frequently compromised by trust asymmetry, leading to substantial risks of non-delivery or non-payment. This study addresses these vulnerabilities by introducing a lightweight, deterministic escrow mechanism based on Ethereum smart contracts, specifically designed to bridge the regulatory gap in consumer protection. Unlike conventional escrow systems that rely on costly human intermediaries or complex decentralized autonomous organization (DAO) structures, the proposed "FairPay" model advances the state-of-the-art by offering a streamlined five-state lifecycle architecture comprising Created, Funded, WorkSubmitted, Released, and Refunded stages. The research prioritizes an analytical problem-solution flow, focusing on a state-machine design that enforces automated role-based restrictions. Methodological evaluation conducted on the Ethereum Sepolia testnet demonstrates a 100% functional success rate across all unit test scenarios. Furthermore, gas cost analysis reveals that the system is economically viable for granular transactions, with core operational functions maintaining a low execution overhead. Beyond operational success, the primary scholarly contribution lies in the design insight of balancing high cryptographic security with granular transaction accessibility, providing a scalable framework for the modern digital economy. However, the system currently assumes binary participant decisions for work verification, representing a transparency-oriented limitation in handling highly subjective service deliverables. Ultimately, this study demonstrates that algorithmic trust, mediated through a simplified state-machine, offers a more efficient and transparent alternative to existing high-complexity blockchain models, effectively resolving the tension between decentralized security and practical usability in P2P digital interactions.
Rizqi Akbar Makarim, Desinta Maheswari, Aqila Dina Pramustiwi, Kartika Ayu Rahmawati · 5 authors
The volatility of cryptocurrency markets has increased substantially in recent years, particularly for Ethereum (ETH), which exhibits fat-tailed distributions and persistent volatility clustering that traditional linear models are unable to capture. This study aims to analyze and model the volatility of ETH/USD using high-frequency hourly data to determine the most appropriate volatility model for describing Ethereum’s intraday market dynamics. The dataset consists of 8,760 hourly closing prices from October 31, 2024 to October 31, 2025, obtained through the CryptoCompare API. The methodological framework includes data preprocessing, log-return transformation, stationarity analysis using the Augmented Dickey–Fuller test, detection of heteroskedasticity via the ARCH–LM test, and estimation of several ARCH and GARCH model specifications. The results show that ETH/USD returns are stationary, non-normally distributed, and exhibit clear volatility clustering. Among the ARCH models, only ARCH(1) adequately captures short-term fluctuations, while ARCH(2) provides no additional benefit. In contrast, GARCH models demonstrate superior performance in capturing both short-term shocks and long-term persistence. Based on AIC, BIC, and log-likelihood values, GARCH(1,2) emerges as the best-performing model, offering the highest flexibility in representing Ethereum’s persistent and reactive volatility patterns. These findings confirm that ETH/USD volatility is predictable and can be modeled statistically. Future research may incorporate asymmetric GARCH extensions or external explanatory variables to improve predictive performance.
The rapid advancement of digital technologies in healthcare has increased the need for secure, transparent, and efficient management of medical data. However, most existing systems rely on centralized architectures, where sensitive patient information is controlled by a single authority. This creates vulnerabilities such as data breaches, unauthorized access, and single points of failure, which can compromise data integrity and patient privacy. The core problem addressed in this research is the lack of a decentralized and tamper-resistant mechanism for managing Electronic Health Records (EHR). Current solutions often suffer from limited transparency, inefficient data sharing between patients and doctors, risks of data manipulation, dependency on intermediaries, and scalability issues due to large medical files like reports and prescriptions. To address these challenges, this research proposes a blockchain-based healthcare management system integrated with the Inter-Planetary File System (IPFS). Blockchain technology, implemented using Ethereum and Web3, ensures secure, immutable, and transparent transaction handling through smart contracts. IPFS is used for decentralized storage of medical files, with only cryptographic hashes stored on the blockchain to reduce storage overhead while maintaining data integrity. The system enables patients to book appointments, upload medical reports, and securely share them with doctors. Doctors can access records, provide diagnoses, and generate prescriptions, which are also stored via IPFS and linked to the blockchain. This ensures that data cannot be altered without detection, enhancing trust. The proposed system improves data security, privacy, reliability, and scalability in healthcare data management.
Jiahao Qi, Dian Ding, Jie Li, Jiannong Cao · 7 authors
Account migration in sharded blockchains presents a critical trade-off between optimization effectiveness and system availability. While dynamically reallocating accounts across shards can significantly reduce cross-shard transaction overhead, existing migration mechanisms cause service disruptions that intensify as state data volumes grow. To address this challenge, we propose BIND, a batch-wise account migration protocol that eliminates service interruptions by enabling continuous transaction processing throughout migration. BIND introduces a dual transaction pool architecture that isolates transactions involving migrating accounts while allowing non-migrating accounts to operate uninterrupted. To optimize migration efficiency, we design a reverse greedy heuristic algorithm that partitions accounts into batches based on community cohesion, maximizing intra-batch connectivity to front-load cross-shard communication reduction. We evaluate BIND using real Ethereum transactions, demonstrating superior performance over existing mechanisms. BIND achieves 12% higher overall throughput, reduces migration time to 23.6%-39.3% of the one-shot baseline (across 1-10Gbps bandwidth), and lowers cross-shard transaction rates by 24.1% compared to random batching. These results confirm BIND as a practical solution for large-scale, non-disruptive account migration in production sharded blockchains.