The contemporary education landscape is often marred by escalating costs and centralized pedagogical structures, which collectively create significant barriers to entry for millions of potential learners worldwide. This paper presents \textbf{Skill Link}, a sophisticated decentralized platform designed to democratize skill acquisition through a specialized credit-based barter system. Unlike conventional e-learning platforms that rely on traditional currency transactions, Skill Link enables a frictionless exchange of knowledge by utilizing a virtual credit economy where participants earn and spend "learning credits." To address the critical issue of credential fraud in decentralized environments, the platform integrates Ethereum-based blockchain technology to ensure the absolute immutability and verifiable authenticity of all earned certificates. Key innovations include a multi-tiered course classification system, an automated mock assessment framework with negative marking capabilities, an intelligent context-aware AI assistant powered by advanced language models, and a rigorous verification mechanism for professional social links (LinkedIn, GitHub, Indeed). Developed using the robust Django framework, Python-based Web3 utilities, and a secure PostgreSQL/SQLite back-end, Skill Link provides a highly secure, transparent, and scalable ecosystem for peer-to-peer knowledge sharing, ultimately fostering a global community of experts and lifelong learners. The system's architecture emphasizes data integrity through atomic transactions and cryptographic verification, ensuring a trustless environment for global skill exchange.
Diana Moses, Mannem Sirivalli, Mohammed Zaid, Afeefa Aref
Abstract Crowdfunding is a proven way to support startups and social projects; nevertheless, conventional crowdfunding platforms are based on centralized architecture, which brings problems like poor transparency, excessive transaction costs, and low level of control over the usage of money. In this paper, a decentralized crowdfunding solution that will solve the described problems will be presented. Blockchain technology is applied to implement the platform through the usage of Ethereum smart contracts, thus providing safe and transparent transactions. The users will be able to launch a campaign, make payments, and control their transactions via MetaMask extension. Milestone-based funding will be used as well to monitor the spending of money properly. Frontend of the project will be designed using React.js and Web3.js. Experimental results show significant advantages of the proposed solution such as improved transparency, reduced dependence on third parties, and increased trust between people. Keywords:Blockchain,Crowdfunding, Ethereum, Smart Contracts, Web3.js, React,js
Automated matching engines execute millions of orders per session, yet systematic asymmetries in latency, order size, and market access compound into persistent execution disparities that erode participant trust. We formulate provably fair order matching as a Constrained Markov Decision Process and propose CPO-FOAM (Constrained Policy Optimization with Feedback-Optimized Adaptive Margins). An inner loop computes an analytic trust-region step on the Fisher information manifold; a PID-controlled outer loop dynamically tightens safety margins, suppressing the sawtooth oscillations endemic to Lagrangian methods under non-stationary dynamics. Group fairness (demographic parity, equalized odds) enters the CMDP cost vector while individual Lipschitz fairness is enforced deterministically via spectral normalization. We prove BIBO stability and that the integral term drives steady-state violations to zero. On LOBSTER NASDAQ data across six market regimes, CPO-FOAM recovers 95.9% of unconstrained throughput at 2.5% constraint violation frequency; on crypto-asset LOB data under MEV injection it captures 98.4% of the reward envelope at 3.2% CVF. The method scales sub-linearly to M=8 constraints, settles on-chain within one Ethereum block, and yields a 2.1X reward improvement on Safety-Gymnasium, confirming domain-agnostic generalization.
Abstract - The healthcare supply chain faces challenges such as inefficient procurement, lack of transparency, counterfeit medicines, and poor tracking mechanisms. This paper proposes a blockchain-based solution integrating smart contracts and decentralized storage systems to enhance traceability, security, and efficiency. The system connects stakeholders including manufacturers, distributors, retailers, and healthcare providers through the Ethereum blockchain. Smart contracts automate transactions, while IPFS and Hyperledger Fabric ensure secure and decentralized storage. The proposed framework improves transparency, reduces fraud, and enhances communication across the supply chain. Experimental results demonstrate improved security, cost efficiency, and system reliability. Key Words: Blockchain Technology, Healthcare Supply Chain, Smart Contracts, Ethereum, Decentralized Storage, IPFS (InterPlanetary File System), Hyperledger Fabric, Supply Chain Management, Data Security, Traceability, Transparency, Counterfeit Drug Prevention, Distributed Ledger Technology
The agricultural sector is essential for global food security but continues to face challenges in supply chain management, including lack of transparency, traceability, and data integrity. This study proposes AgroChain, a blockchain-based framework designed to enhance governance and trust in the Agricultural Supply Chain (ASC). The system is built on the Quorum blockchain platform, an enterprise version of Ethereum, which integrates Zero-Knowledge Proof (ZKP) protocols to ensure data privacy while maintaining secure and transparent transactions. AgroChain introduces a scalable process model that separates the registry of agricultural records from the actual data, enabling efficient data handling. Smart contracts are used to automate key supply chain operations such as record creation, validation, transfer, and deletion, allowing end-to-end traceability from farm to consumer. The framework also incorporates rolebased access control for stakeholders including farmers, distributors, retailers, and consumers. Experimental results indicate that AgroChain improves transparency, accountability, and interoperability, demonstrating the potential of blockchain technology to transform agricultural supply chain governance.
We present DSKAG-IT-SIG, a family of information-theoretic transaction signature schemes that achieve unconditional existential unforgeability under adaptive chosen-message attack by computationally unbounded adversaries. 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 the forgery advantage of any unbounded adversary making q queries is at most q * 2^{-128} in standard mode, reducing to the statistical uniformity of DSKAG-derived keys and the pairwise independence of HMAC-SHA256 under a uniform key. We prove (Theorem 2) that cross-domain forgery advantage is at most 2^{-128} + negl(lambda), reducing to the statistical key isolation of DSKAG across policy domains. Both bounds are unconditional and independent of any computational hardness assumption. 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) enables permissionless on-chain compliance verification, deployed on Ethereum Sepolia and Arbitrum Sepolia. Version 2.2. 17 pages, 7 tables. Three independent academic institutions validated the construction: no structural attacks found.
Este artigo analisa estratégias de otimização de gas em Ethereum a partir de duas dimensões principais: o custo dos opcodes da EVM e as escolhas de estruturas de dados em Solidity. A tabela de opcodes da EVM e a evolução do gas schedule mostram que operações de armazenamento e acesso externo, como SSTORE, SLOAD, CALL, BALANCE e EXT*, estão entre as mais caras, especialmente após EIPs como a 2929, que aumentaram o custo de acessos “frios” a contas e slots de storage para refletir melhor seu impacto na execução e na camada de armazenamento. Estudos recentes sobre custos de armazenamento evidenciam que uma escrita em SSTORE pode custar cerca de 22.100 gas para 32 bytes (aprox. 690 gas/byte), enquanto leituras via SLOAD também são significativamente caras, motivando pesquisas sobre técnicas como SSTORE2 e mecanismos para corrigir “overcharge” em leitura/escrita de storage, com ganhos médios de até 30–32% em fees para certos padrões de uso. Boas práticas de otimização de gas em Solidity incluem reduzir o número de acessos a storage movendo valores frequentemente lidos para variáveis em memória, empacotar variáveis em slots de 32 bytes (storage packing), preferir tipos fixos a dinâmicos quando possível, evitar cópias desnecessárias de arrays de storage para memória e desenhar estruturas de dados que minimizem gravações em storage. A literatura e guias de otimização indicam que a escolha entre arrays, mappings, structs e padrões de layout impacta diretamente o custo de execução, especialmente em loops que interagem com storage ou estruturas dinâmicas. Conclui‑se que a otimização de gas em Ethereum é um problema tanto de engenharia de baixo nível, ligado ao custo de opcodes e ao modelo warm/cold de acessos, quanto de design de dados e algoritmos, com implicações econômicas diretas para usuários, protocolos DeFi e estratégias de design de L2s.<br>
Набір даних містить матеріали для відтворення емпіричного аналізу, опублікованого у статті «Крипторинок як асиметрична дуополія: комплементарність і конкуренція між Bitcoin і Ethereum». Він включає аналітичний скрипт R, похідні табличні результати та рисунки, що відтворюють усі таблиці й графіки, представлені у статті. Аналіз охоплює щоденні ціни закриття та обсяги торгів для біткоїна (BTC-USD) та ефіріуму (ETH-USD), отримані з Yahoo Finance, за період з 1 січня 2017 року до 20 березня 2026 року. Емпірична модель перевіряє наслідки моделей цінової конкуренції Бертрана та кількісної конкуренції Курно, а також оцінює три гіпотези: цінове лідерство біткоїна (H1), кількісну рівновагу Курно (H2) та часткову комплементарність активів (H3).
The rapid proliferation of cloud storage services necessitates robust mechanisms for verifying data integrity without requiring complete data retrieval. Traditional Provable Data Possession schemes face significant challenges in achieving simultaneous decentralization, privacy preservation, and efficient dynamic data handling. We present a novel framework that integrates blockchain technology with zero-knowledge cryptography to comprehensively address these limitations. Our approach employs Ethereum smart contracts for decentralized verification orchestration, Groth16 zk-SNARKs for privacy-preserving proof generation, and IPFS for distributed metadata management. The system architecture features a hierarchical Merkle tree authentication structure combined with BLS signature aggregation, achieving logarithmic verification complexity that is independent of the dataset size. By leveraging blockchain's immutable ledger properties, we eliminate single points of failure inherent in centralized third-party auditor models while ensuring complete audit trail transparency. The protocol supports dynamic data operations, including insertions, deletions, and modifications, through efficient cryptographic re-authentication mechanisms. We implement homomorphic encryption to enable verification on encrypted data, ensuring cloud providers never access plain-text information. Experimental evaluation on realistic datasets demonstrates a 43% reduction in computational overhead, a 67% decrease in communication costs, and 99.9% verification accuracy compared to existing approaches. When processing 10,000 data blocks totalling 1 GB, our system achieves a 2.3 -second average verification time with only 1.2% storage overhead. Formal security analysis proves correctness, soundness under computational hardness assumptions, and zero-knowledge privacy guarantees.
Efficient pricing mechanisms are critical for optimizing water consumption, managing demand, and promoting equitable resource distribution. This paper presents a Time-of-Use (TOU) dynamic pricing model integrated with Blockchain Technology (BT) to address these challenges. The proposed model categorizes time into Peak, Off-Peak, and Shoulder hours, applying distinct pricing tiers responsive to demand fluctuations, further refined through seasonal adjustments and demand constraints to support sustainability and regulatory compliance. Implemented on the Polygon blockchain - chosen for its low transaction cost, high scalability, and ethereum compatibility - the framework leverages Smart Contracts (SC) for secure, transparent and automated real-time pricing adjustments. Full on-chain data storage eliminates off-chain dependencies, ensuring data integrity and traceability throughout the water supply chain. Pseudonymous blockchain identities maintain user privacy while providing full auditability via immutable on-chain records. Security vulnerabilities such as input manipulation, arithmetic overflows, and unauthorized access receive proactive mitigation through secure coding practices, role-based access control, and logic constraints. Performance evaluation using the k6 load testing tool under simulated real-world conditions shows robust system behavior: response times ranged from 2.14s to 5.64s, with the 90th and 95th percentiles at 3.5s and 4.26s, respectively. Latency ranged from 5.96ms (median) to 49.54ms (95th percentile), validating the system’s responsiveness, scalability, and reliability under concurrent user requests. The test results further highlight the system’s ability to handle concurrent user requests efficiently, demonstrating reliable performance under simulated varying workloads.
N. V. Ravindhar, A. Manju, S. Murugesan, T. K. S. Rathish Babu
Electric Vehicle-to-Grid (V2G) arrangements stand at the center of bidirectional energy exchange in modern smart grids and are, however, challenged by real-time decision-making, load balancing, and the security of transaction validation. This paper has proposed an energy-efficient optimization framework based on a Bio-Inspired Deep Learning Controller using a Monarch Butterfly Optimization (MBO) algorithm with Gated Recurrent Unit (GRU) network for optimizing charging and discharging schedules across EV fleets. GRU networks forecast short-term grid demand and EV battery availability while MBO tunes the controller weights dynamically to adapt to scheduling under varying conditions. Furthermore, in order to maintain the trust over the transaction in a tamper-resistant fashion, a blockchain layer is embedded with the use of smart contracts to keep a track of authentication, pricing, and energy transfer log records for V2G. The proposed system shows charging cost reduction of 19.6%, peak load shaving efficiency of 23.2%, and forecast accuracy of 96.4%, in all mobility scenarios evaluated. The architecture also contributes to improving grid regulation response time by 28% and reducing EV queuing delay by 31%. Simulated by using MATLAB/Simulink, TensorFlow, and Ethereum-based blockchain, the architecture renders a scalable and secure framework for V2G coordination. It is noted that the findings are based on simulation, and co-simulation experiments, and the actual conditions of deployment like latency in communications, non-idealities of the hardware and regulatory factors are not factored into the analysis. Furthermore, the model facilitates real-time adaptation, strengthens grid resilience, and guides EV operation according to concurrent market conditions for energy.
Carlos Melo, Glauber Gon§Alves, Francisco A. Silva, André Soares · 7 authors
Leading blockchain platforms like Ethereum face significant scalability challenges while striving to balance high transaction throughput, security, and decentralization. Layer-2 solutions, especially Zero-Knowledge (ZK) Rollups, tackle this issue by processing transactions off-chain and submitting concise validity proofs to the main network. This approach preserves security while improving throughput. Despite these technical advantages, optimizing the underlying infrastructure remains a complex task for node operators. This paper presents a formal modeling approach using Stochastic Petri Nets (SPNs) to assess the operational behavior of ZK-Rollups, particularly addressing deployment challenges in public cloud environments. The proposed model is calibrated using empirical parameters from the zkSync Era protocol to ensure realistic performance representation. Using a Design of Experiments (DoE) methodology, we analyze key infrastructure metrics systematically, including resource utilization, transaction wait times, and daily operational costs under various system configurations. Case studies demonstrate that increasing Layer-2 transaction volume can reduce service providers’ daily operational costs by up to $\mathbf{2 5 \%}$ through more efficient batch usage. However, results indicate a significant tradeoff between cost efficiency and responsiveness, as larger batch sizes may double user waiting times. Additionally, we analyze the relationship between server utilization and capacity, demonstrating that typical deployments are frequently overprovisioned and compromise system stability.
Decentralized Finance (DeFi) lending protocols have demonstrated the viability of peer-to-pool lending without traditional intermediaries. However, the dominant Ethereum-based platforms such as Aave and Compound impose transaction costs of $5–$50 per operation, rendering micro-loans below $1,000 economically unviable for the 1.4 billion unbanked individuals globally. This paper presents Solaris Protocol, a decentralized micro-lending protocol built natively on the Solana blockchain, designed specifically for financial inclusion through micro-lending. Solaris Protocol leverages Solana’s sub-second finality, parallel transaction processing via Sealevel, and transaction costs averaging $0.00025 to achieve a 99.98% cost reduction compared to Ethereum-based alternatives. We present a complete system architecture utilizing Program Derived Addresses (PDAs) for deterministic state management, Cross-Program Invocations (CPIs) for atomic fund transfers, and Rust’s ownership model for memory-safe smart contract execution. Our implementation comprises five core instructions (initialize, deposit, borrow, repay, withdraw) validated through 13 comprehensive test cases covering both success paths and adversarial scenarios. Comparative analysis demonstrates that a $10 micro-loan lifecycle on Solaris Protocol costs $0.00125 in total fees versus $25–$150 on Ethereum-based protocols, establishing the technical feasibility of blockchain-based micro-lending for underserved populations.
Anirban Dalui, Ritik Kumar Patra, Jatin Tiwary, Jeeva S
The voluntary carbon market is vital for getting private money to projects – worldwide – which cut emissions or take carbon from the air. However, current markets suffer from fragmentation, lack of transparency, manual verification, and risks of double-counting or fraudulent credits. These issues severely erode buyer trust and market efficiency. This study shows a blockchain system built to deal with these faults: verified carbon credits are made into ERC-20 tokens on the Ethereum blockchain. The system lets people trade without needing to trust each other, using Balancer Automated Market Maker – AMM – pools that have DAI stablecoins with them; and it ensures credits are removed from the market for good with a ‘buy-and-burn’ method, ending with ERC-721 Non-Fungible Tokens – NFTs – being given out as proof the emissions were offset. By including data linked to Inter-Planetary File System (IPFS), and signs from cryptographically checked people who confirmed things, the system stops double-counting, makes it easier to find where credits came from, and helps the market to trade more easily. Using what we’ve learned from carbon platforms which have used tokens, from 2020 to 2025, we use a fixed-effects Difference-in-Differences – DiD – test to find what effect the system has on how well prices work and how many trades there are. What we found is that using blockchain makes prices more steady when there’s a reasonable amount of trading, but doesn’t change trading volume much in the short run. These results show how blockchain can make carbon markets stronger, lower costs of trading, and help the Sustainable Development Goals – SDGs. What this study gives is useful to people who make policy, control things, and invest, who want to make digital carbon systems that can last, work well and grow.
Dr. Tejaswini S, Bhashitha Jain P L, Neil Chris Dsouza, Vibha Bhat
I. INTRODUCTION Cryptocurrency has rapidly transformed from a niche technological curiosity to a mainstream financial asset with millions of participants across the globe, and India is no exception to this trend. By 2022, India was estimated to have one of the largest populations of cryptocurrency holders in the world, with figures ranging from 10 to 20 crore users according to various industry reports. This explosive growth brought an urgent question to the forefront of Indian tax policy: how should gains and income arising from such digital assets be taxed, and how should compliance be ensured in a space that has historically operated in a regulatory grey zone? The term cryptocurrency, or more broadly Virtual Digital Asset (VDA), refers to any information, code, number, or token - other than Indian currency or foreign currency — generated through cryptographic means, providing a digital representation of value exchanged with or without consideration. Bitcoin, Ethereum, and a wide spectrum of altcoins and non-fungible tokens (NFTs) fall under this definition as formally adopted in India's Finance Act 2022. The Finance Act 2022 was a watershed moment in India's regulatory journey with digital assets. It introduced Section 115BBH into the Income Tax Act, 1961, which imposed a flat 30% tax on income arising from the transfer of VDAs, irrespective of the holding period or the taxpayer's income slab. Simultaneously, Section 194S mandated Tax Deducted at Source (TDS) at 1% on payments related to VDA transfers, placing the obligation on crypto exchanges and certain buyers to withhold tax at the point of transaction. These twin provisions created a definitive, if controversial, legal framework for cryptocurrency taxation in India.
Sreekanth Vp, Ronny Sebastian Roy, Surya Gopalakrishnan, Thanmaya S Krishna
The proliferation of cyber threats and the increasing digital vulnerability of students necessitate innovative educational approaches to cybersecurity awareness. Traditional methods of teaching cybersecurity often fail to engage learners effectively, resulting in poor knowledge retention and limited practical skills. This paper introduces Zyberix, an interactive educational game that leverages Web3 technologies to teach cybersecurity concepts through immersive gameplay and blockchain-based incentives. By integrating Unity game engine with Ethereum smart contracts, IPFS decentralized storage, and NFT rewards, Zyberix creates an engaging learning environment that simulates realistic cyber threats including phishing, malware, and social engineering attacks. The system rewards successful challenge completion with verifiable Non-Fungible Tokens (NFTs), providing both motivation and an introduction to blockchain technology. This research demonstrates how gamified experiential learning combined with Web3 technologies can significantly enhance cybersecurity education, addressing the critical gap between theoretical knowledge and practical application while fostering digital literacy among students.
Songyan Ji, Jin Wu, Wei Zhang, Ming Han · 6 authors
This paper centers on open-secret vulnerabilities (OSVs), a kind of smart contract vulnerability that allows attackers to exploit the natural transparency feature of blockchains to gain illegal monetary profits from problematic smart contracts. Attackers can easily launch OSV attacks by leveraging publicly visible information from a smart contract to issue a profitable transaction without violating its business logic. This poses significant challenges in detecting OSVs. Despite the severe impacts of OSVs, there is no prior research work that systematically discusses OSVs (to the best of our knowledge). To fill this knowledge gap, this paper presents a formal definition of OSVs, and OSVHunter, the first-ever tool aiming to detect OSVs in smart contracts. The detection results show that OSVs are prevalent in real-world smart contracts. Some of these vulnerabilities are even concealed within highly popular Ethereum contracts, with individual contract valuations exceeding five hundred thousand U.S. dollars. These vulnerabilities appear in finance, gaming, gambling, etc. We hope this paper can arouse our community’s attention to the significance of OSVs and lay the technical foundation for future research.
Drissia Ennagoura, Kamal El Kehal, Abdelhamid Berdai, Safae Merzouk · 8 authors
Cryptocurrency price prediction is challenging due to strong nonlinearity and high volatility. This paper comparatively evaluates three forecasting models for Ethereum (ETH): SARIMAX with exogenous technical indicators, Long Short-Term Memory (LSTM) networks, and Facebook Prophet. Relative Strength Index (RSI), Moving Average Convergence Divergence (MACD), and Exponential Moving Average (EMA) are incorporated to enhance signal quality. Empirical results reveal clear trade-offs between predictive accuracy, profitability, and risk. SARIMAX achieves the highest directional accuracy (75.00%) with limited profitability, while LSTM yields the highest cumulative profit (23.84%) at the cost of higher drawdown. Prophet provides a balanced compromise between accuracy and risk. The study contributes by jointly evaluating statistical forecasting accuracy and trading-oriented performance metrics, offering practical insights into model suitability for different investor risk profiles.
Traditional consensus mechanisms, such as Proof of Stake (PoS), increasingly reveal an excessive dependency on large liquidity providers. Although the Proof of Liquidity (PoL) mechanism serves as a critical paradigm for incentivizing sustained liquidity provision and ensuring market stability, its transition from asset staking to active liquidity management significantly increases the complexity of underlying smart contract economic models and interaction logic. This renders hidden liquidity logic flaws difficult to detect via traditional methods, seriously threatening the system stability and user asset security of mainstream DeFi and emerging PoL ecosystems. To address this, we propose the LiquiLM framework, which integrates Large Language Models (LLMs) with a Dynamic Co-Attention Network (DCN). By establishing a dynamic interaction between liquidity-critical contracts and flaw descriptions, the framework effectively bridges the semantic gap between underlying code implementations and high-level liquidity intents. We evaluate the performance of LiquiLM on 1,490 validation contracts (covering precision, recall, specificity, and F1-score). The results show that it achieves significant effectiveness in auditing and explaining liquidity flaws: in experiments using Gemini 3 Pro and GPT-4o as backbone models, respectively, the F1-scores both exceed 90%. Furthermore, through an in-depth audit of 1,380 real-world PoL and Ethereum economic contracts, LiquiLM successfully identifies 238 high-risk contracts and assists in discovering 10 vulnerabilities that have received CVE certification.
O presente artigo analisa a gestão de estado em blockchains públicas, com foco em técnicas de pruning e estratégias de arquivamento eficiente, diante do crescimento contínuo de dados e da necessidade de equilibrar segurança, disponibilidade histórica e custos de infraestrutura. Em redes baseadas em máquinas de estado, como aquelas compatíveis com a Ethereum Virtual Machine, o estado global – composto por contas, contratos e dados de armazenamento – é mantido em estruturas de dados do tipo árvore de Merkle-Patricia (MPT), que crescem monotonicamente à medida que novas transações modificam o estado, levando nós completos e de arquivo a consumirem dezenas de terabytes após alguns anos de operação em produção. Essa dinâmica impõe desafios estruturais a operadores de nós, que precisam escolher entre manter histórico completo, realizar pruning de blocos e estados antigos ou recorrer a nós especializados para consultas históricas, afetando diretamente o grau de descentralização e o custo de participação na rede. A metodologia adotada combina revisão bibliográfica de pesquisas em bancos de dados para blockchains, documentação técnica de clientes de nós – entre os quais Geth, Erigon e equivalentes em outras redes – e estudos recentes sobre statelessness, expiração de estado (state expiry), árvores de Verkle e bancos de dados forkless, discutindo as implicações dessas abordagens para a gestão de estado de longo prazo. Os resultados indicam que estratégias de pruning ao nível de blocos e de estado, combinadas a modelos de nós diferenciados (full, pruned, archive, light) e a técnicas de instantâneos (snapshotting) e arquivamento externo, permitem reduzir significativamente o volume de armazenamento exigido de nós validadores sem sacrificar a capacidade de validação e a segurança da cadeia. Por outro lado, a dependência crescente de archive nodes e de infraestruturas especializadas para consultas históricas levanta questões relevantes acerca de centralização e do custo de reconstrução do estado em cenários adversos, estimulando pesquisa em modelos de clientes sem estado (stateless clients), provas compactas de estado e bancos de dados desenhados especificamente para as cargas de trabalho de blockchains. Conclui-se que a gestão eficiente de estado constitui componente crítico da sustentabilidade de longo prazo da Web3, demandando abordagens integradas que combinem técnicas de pruning, desenho criterioso de estruturas de dados, políticas explícitas de retenção histórica e modelos econômicos que incentivem a operação de nós com diferentes perfis de armazenamento.
O presente artigo examina técnicas de compressão de dados em blocos de blockchain e sua relação com a redução de custos de armazenamento on-chain, considerando tanto o consumo de espaço em disco pelos nós da rede quanto o custo econômico de inclusão de dados em transações. Em plataformas como o Ethereum, parcela significativa do custo de transações – especialmente para rollups e aplicações que utilizam calldata de maneira extensiva – está associada ao armazenamento e à propagação de bytes de dados na camada base, o que tem motivado a adoção de estratégias de compressão de calldata, ajuste de parâmetros de gas e a introdução de novas formas de armazenamento temporário, a exemplo de blobs de dados. A metodologia empregada baseia-se em revisão bibliográfica de trabalhos sobre estratégias de armazenamento on-chain, análise de propostas de melhoria do ecossistema (Ethereum Improvement Proposals – EIPs) voltadas à redução de custos de calldata, exame de relatórios técnicos sobre compressão de dados em soluções de camada 2 e análise recente do impacto de mecanismos como o EIP-4844 (proto-danksharding) sobre a estrutura de custos de rollups. As evidências levantadas indicam que técnicas de compressão aplicadas ao payload de transações podem reduzir da ordem de cinco vezes o tamanho efetivo dos dados enviados, traduzindo-se em economias de aproximadamente 50% no gasto de gas para determinadas operações em redes de segunda camada, sem exigir mudanças disruptivas no protocolo subjacente. Paralelamente, abordagens estruturais – entre as quais a separação de dados de disponibilidade em blobs não permanentes e o emprego de rollups que publicam apenas provas e raízes de estado, em vez de dados completos – contribuem para reduzir a pressão de armazenamento permanente sobre os nós da camada 1. Conclui-se que a compressão de dados em blocos, combinada a ajustes de modelo de dados (blobs, rollups, off-chain storage) e a técnicas de compressão clássicas (run-length, delta, dicionário, entropia), constitui peça central na estratégia de escalabilidade e sustentabilidade econômica da Web3, não obstante levante desafios relevantes quanto à complexidade de implementação, compatibilidade entre clientes e preservação da verificabilidade de longo prazo.
Este artigo analisa o custo‑benefício energético de três mecanismos de consenso centrais no ecossistema de criptoativos: Proof‑of‑Work (PoW), Proof‑of‑Stake (PoS) e Proof‑of‑History (PoH) combinado a PoS, examinando como diferenças de consumo de energia se relacionam a segurança, desempenho e sustentabilidade econômica. A partir de dados recentes sobre consumo energético de redes públicas como Bitcoin, Ethereum antes e depois da transição para PoS e Solana, discute‑se em que medida a evolução dos mecanismos de consenso permite reduzir ordens de grandeza de uso de eletricidade por transação, sem necessariamente comprometer a segurança e a descentralização. A metodologia baseia‑se em revisão bibliográfica de estudos acadêmicos e relatórios técnicos sobre consumo de energia em blockchains, análise de estimativas consolidadas de uso anual de eletricidade e de energia por transação e discussão conceitual de trade‑offs entre eficiência energética, robustez criptográfica, requisitos de hardware e impactos regulatórios. Evidências indicam que o Bitcoin, ancorado em PoW, mantém consumo anual estimado em torno de 120–130 TWh, enquanto o Ethereum, após migrar para PoS em 2022, reduziu seu consumo em mais de 99%, passando a operar com menos de 0,01 TWh por ano. Relatórios de eficiência energética mostram que redes que combinam PoH e PoS, como a Solana, apresentam consumo de energia por transação da ordem de centenas de joules, inferior tanto a redes PoW quanto a muitas redes PoS, embora existam ressalvas metodológicas e discussões sobre centralização de infraestrutura. Conclui‑se que PoS e esquemas híbridos com PoH oferecem vantagens substanciais em termos de eficiência energética, mas a avaliação de custo‑benefício precisa incorporar conjuntamente segurança econômica, distribuição de poder, maturidade de ecossistema e alinhamento com agendas de sustentabilidade e descarbonização que tendem a moldar a evolução da infraestrutura Web3.<br>
We present a formal treatment of provenance trees, directed acyclic graphs of artifact registrations anchored immutably on a public blockchain, and introduce the operator trust problem: when a single privileged operator submits all on-chain registrations on behalf of users, the on-chain record alone cannot distinguish user-initiated registrations from unilateral operator actions. We resolve this through a dual-layer cryptographic commitment scheme in which two commitments derived from a single client-side secret key, binding the key to the tree root and to each unique registration identifier, make false attribution claims strictly dominated strategies. We prove correctness under standard cryptographic assumptions and establish honest behavior as the unique Nash equilibrium without relying on operator trust. We further introduce and analyze the tree poisoning problem: adversarial attacks on users' provenance trees via fraudulent root registration, malicious child attachment, and tree identity spoofing. We characterize the closure properties of each attack variant and prove that a complete provenance tree integrity model requires three distinct mechanisms: cryptographic priority, governance cascade, and contract enforcement, each necessary and none individually sufficient. The construction is deployed on Base (Ethereum L2) as AnchorRegistry, an immutable on-chain provenance registry. We provide gas complexity analysis demonstrating O(1) cost invariant to registry scale, and a trustless reconstruction algorithm recovering the complete registry from public event logs alone.
Prof. S. P. Palaskar, Swaraj Chikhale, Shantanu Chimote, Rakshit Sinha · 6 authors
Abstract— Traditional identity systems rely on centralized authorities, which creates single points of failure and privacy risks. We propose IDentix, a decentralized identity framework leveraging blockchain and cryptography to secure user credentials while preserving privacy. In IDentix, each user owns a self-sovereign identity (SSI) represented by a public/private key pair and a Decentralized Identifier (DID) registered on an Ethereum smart contract. Trusted issuers (e.g. governments, banks) provide verifiable credentials (VCs) to users off-chain, and users present cryptographic proofs (such as zero-knowledge proofs) of specific attributes to verifiers. Verifiers authenticate credentials by checking issuer signatures against public keys on the blockchain and querying an immutable credential registry. Our prototype on the Ethereum Sepolia testnet demonstrates that this design yields tamper-evident identity proofs without exposing personal data. As shown in prior work [1], blockchain-based SSI greatly reduces risks of identity theft while giving users full control over their data. Keywords— Blockchain; decentralized identity; self-sovereign identity; verifiable credentials; decentralized identifiers; identity verification; Ethereum; zero-knowledge proof.