In blockchain networks, so-called "full nodes" serve data to and relay transactions from clients through an RPC interface. This serving layer enables integration of "Web3" data, stored on blockchains, with "Web2" mobile or web applications that cannot directly participate as peers in a blockchain network. In practice, the serving layer is dominated by a small number of centralized services ("node providers") that offer permissioned access to RPC endpoints. Clients register with these providers because they offer reliable and convenient access to blockchain data: operating a full node themselves requires significant computational and storage resources, and public (permissionless) RPC nodes lack financial incentives to serve large numbers of clients with consistent performance. Permissioned access to an otherwise permissionless blockchain network raises concerns regarding the privacy, integrity, and availability of data access. To address this, we propose a Permissionless Accountable RPC Protocol (PARP). It enables clients and full nodes to interact pseudonymously while keeping both parties accountable. PARP leverages "light client" schemes for essential data integrity checks, combined with fraud proofs, to keep full nodes honest and accountable. It integrates payment channels to facilitate micro-payments, holding clients accountable for the resources they consume and providing an economic incentive for full nodes to serve. Our prototype implementation for Ethereum demonstrates the feasibility of PARP, and we quantify its overhead compared to the base RPC protocol.
Can you imagine, blockchain transactions can talk! In this paper, we study how they talk and what they talk about. We focus on the input data field of Ethereum transactions, which is designed to allow external callers to interact with smart contracts. In practice, this field also enables users to embed natural language messages into transactions. Users can leverage these Input Data Messages (IDMs) for peer-to-peer communication. This means that, beyond Ethereum's well-known role as a financial infrastructure, it also serves as a decentralized communication medium. We present the first large-scale analysis of Ethereum IDMs from the genesis block to February 2024 (3134 days). We filter IDMs to extract 867,140 transactions with informative IDMs and use LLMs for language detection. We find that English (95.4%) and Chinese (4.4%) dominate the use of natural languages in IDMs. Interestingly, English IDMs center on security and scam warnings (24%) with predominantly negative emotions, while Chinese IDMs emphasize emotional expression and social connection (44%) with a more positive tone. We also observe that longer English IDMs often transfer high ETH values for protocol-level purposes, while longer Chinese IDMs tend to involve symbolic transfer amounts for emotional intent. Moreover, we find that the IDM participants tend to form small, loosely connected communities (59.99%). Our findings highlight culturally and functionally divergent use cases of the IDM channel across user communities. We further examine the security relevance of IDMs in on-chain attacks. Many victims use them to appeal to attackers for fund recovery. IDMs containing negotiations or reward offers are linked to higher reply rates. We also analyze IDMs' regulatory implications. Their misuse for abuse, threats, and sexual solicitation reveals the urgent need for content moderation and regulation in decentralized systems.
S rozvojem kryptoměn v poslední dekádě získal blockchain pozornost akademické obce, průmyslu i veřejnosti. Některé blockchainy podporují Turingovsky úplné programy známé jako chytré kontrakty, které umožňují vývojářům vytvářet komplexní decentralizované aplikace pomocí vyšších programovacích jazyků. Tato práce se zabývá studiem zranitelností chytrých kontraktů, jejich prevencí a mitigací. Jsou studovány a shrnuty časté zranitelnosti v jazyce Solidity a na Ethereum blockchainu. Je vytvořen podrobný přehled těchto zranitelností, včetně konkrétních příkladů, strategií prevence a metod detekce. Praktická část práce se zaměřuje na implementaci série praktických vzdělávacích cvičení pro studenty, umožňujících jim experimentovat s těmito zranitelnostmi v kontrolovaném prostředí. V rámci této práce byla implementována série devíti praktických cvičení, která dohromady obsahují 23 úloh, v nichž mohou studenti experimentovat s reentrancy útoky, s útoky s využitím flash loans, s manipulací cenových orákulů, se slabinami v řízení přístupu, s útoky typu odepření služby, s problémy náhodnosti, s aritmetickými chybami, s frontrunningem a sandwich útoky, s unit testy a fuzzingem a dalšími koncepty.
Carlos Melo, José Miqueias, Glauber Dias Gonçalves, Francisco Airton Silva · 6 authors
Embora a transição da plataforma Ethereum para Proof-of-Stake e o surgimento de sidechains ofereçam soluções parciais para os problemas de escalabilidade, essas abordagens apresentam trade-offs entre segurança e complexidade de implementação. Para mitigar esses desafios, os ZK-Rollups surgiram como soluções de escalabilidade de Layer-2, combinando computação off-chain com verificação on-chain, garantindo segurança e descentralização na plataforma Ethereum. Este artigo propõe uma abordagem baseada em Redes de Petri Estocásticas para avaliar a viabilidade dos ZK-Rollups, considerando os principais fatores que impactam métricas de desempenho essenciais, como vazão e latência. Também analisamos a relação entre custo e benefício, incluindo o custo médio por transação e como este é impactado pelas métricas de desempenho. Os resultados mostram que uma maior adoção de transações na Layer-2 pode aumentar a vazão do sistema em até 20%, passando de 85 tps em um ambiente sem Layer-2 para 105 tps quando 90% das transações seguem por esse caminho. Por outro lado, a latência pode sofrer um aumento superior a 100% com a utilização de batches maiores na Layer-2.
Flaviene Scheidt de Cristo, Jorge Augusto Meira, Jean-Philippe Eisenbarth, Radu State
Several distributed systems based on unstructured p2p networks, such as blockchains, rely on underlying protocols to disseminate messages in a fast and reliable way. As the state-of-the-art for message dissemination in blockchains, GossipSub guarantees delivery and resilience against attacks and byzantine faults by scaling pubsub dissemination without exceeding bandwidth or overloading peers. Although GossipSub relies heavily on the way its mesh is constructed, there is little insight into how different configuration parameters impact the overall performance of the system. This study analyzes the relationships between the configuration and the performance of GossipSub from a causal point of view using the concrete case of the XRPL. By employing graphical causal methods to investigate the strength of those connections, this study goes towards the direction of finding the best configuration for GossipSub for different domains, without the need for excessive empirical tests.
Praveen Kumar Myakala, Anil Kumar Jonnalagadda, Sooraj George Thomas
This study introduces a novel intent-driven framework designed to advance privacy, scalability, and autonomous coordination in decentralized systems. Unlike traditional transaction-centric models, the proposed architecture allows users to express the desired outcomes through signed intents, enabling flexible and dynamic counterparty discovery without predefined execution paths. Solver-based optimization, leveraging constraint satisfaction techniques, matches, and composes these intents into valid transactions, facilitating complex workflows across heterogeneous trust and consensus environments. Composable privacy is achieved through integrated mechanisms, such as zero-knowledge proofs, homomorphic encryption, and programmable confidentiality, offering fine-grained control over data exposure and state transitions. The framework further supports multi-chain atomic settlement, dynamic rollup instantiation, and cross-domain interoperability, enabling applications across de-centralized finance, supply chain orchestration, and confidential governance. By unifying intent-centric interaction with modular security models, this architecture provides a scalable, privacy-preserving foundation for the next generation of decentralized analytics and autonomous decision-making systems.
Parwat Singh Anjana, Srivatsan Ravi, Herlihy, Maurice
This paper presents a comprehensive analysis of historical data across two popular blockchain networks: Ethereum and Solana. Our study focuses on two key aspects: transaction conflicts and the maximum theoretical parallelism within historical blocks. We aim to quantify the degree of transaction parallelism and assess how effectively it can be exploited by systematically examining block-level characteristics, both within individual blocks and across different historical periods. In particular, this study is the first of its kind to leverage historical transactional workloads to evaluate conflict patterns. By offering a structured approach to analyzing these conflicts, our research provides valuable insights and an empirical basis for developing more efficient parallel execution techniques for smart contracts in the Ethereum and Solana. Our empirical analysis reveals that historical Ethereum blocks frequently achieve high independence, with over 50\% independent transactions in more than 50\% of blocks, while, on average, Solana blocks contain longer conflict chains $\sim$58\%, compared to $\sim$18\% in Ethereum, reflecting fundamentally different parallel execution dynamics.
Ningbin Yang, Chunming Tang, Zhihong Deng, Debiao He
Blockchain systems have evolved over decades, addressing the inefficiencies and high costs associated with centralized architectures. Among various consensus mechanisms, committee-based hybrid Byzantine Fault Tolerant (BFT) protocols are a fundamental approach to blockchain consensus. However, designing a hybrid BFT consensus protocol that ensures fairness, responsiveness, and formal security remains challenging. In this paper, we propose GRBFT: a Gaussian reputation-based hybrid BFT blockchain consensus protocol with a formal security framework. Our proposed protocol integrates a multilateral Gaussian reputation evaluation to incentivize trusted nodes' participation in the consensus. We use threshold signatures and verifiable random functions (VRFs) to randomly select committee members and leaders, ensuring fair reconfiguration and unbiased sortition. A formal security framework is utilized to design and analyze the blockchain consensus system. Additionally, we design a speculative GRBFT (S-GRBFT) protocol to circumvent the traditional$\mathcal {O}(n^{2})$leader sortition complexity and reduce the communication to$\mathcal {O}(n)$within a single round. Moreover, we present a secure candidate committee reconfiguration method that efficiently updates members based on their reputation and a Proof-of-Stake (PoS) mechanism. The proposed GRBFT protocol is proven to achieve consistency and liveness under the corruption and liveness parameters.
Blockchain technology introduces a new decentralized paradigm era avoiding the reliance on trusted third parties. It is a transparent and distributed ledger which is designed fundamentally for digital cryptocurrencies but has since been extended to various industries. However, its immutability obligates significant challenges including storing illicit contents, privacy regulations violations, and restricting data management flexibility. Therefore, redactable blockchain has emerged as a leading solution enabling controlled immutable contents amendment. Transaction-level redaction reinforced by fine-grained access control forms the cornerstone of the current redaction mechanisms. This redaction concept essentially depends on modifying mutable transactions governed by predefined access policies specified by the transaction owner. Modifiers equipped with necessary rewriting privileges and who fulfil the associated access policy are enabled to perform modifications. However, the existing redaction mechanisms infrastructures are inefficient. For instance, the chameleon hash ephemeral trapdoor (chet),
This paper explores the dynamics of multibranch forging algorithms within Proof-of-Stake (PoS) systems, focusing on the tails switching effect and its associated risks, such as the Nothing-at-Stake (N@S) attack. The study introduces a series of modifications to the traditional single-branch approach, drawing inspiration from quantum mechanics to enhance system security and efficiency. By analyzing the impact of smooth and direct measure functions on the cumulative measure of blockchain branches, the paper demonstrates that direct measures effectively reduce tails switching and stabilize the network. Additionally, the introduction of single-branch nodes is shown to stabilize the best chain, reducing the likelihood of history rewrites. The results suggest a promising pathway for improving multibranch PoS systems, emphasizing the need for further investigation into delayed propagation, transaction processing, and measure combinations.
Aashish Kumar Jha, Mohammed Nihar N R, J Sankalpa, Chetana Prakash
ABSTRACT: As statistics is the backbone of the digital financial system dependence on centralized cloud storage structures makes users prone to troubles concerning statistics breaches operational price and lack of control this paper examines the deployment of a decentralized cloud storage DCS framework with the use of interplanetary file system IPFS and Ethereum blockchain clever contracts to triumph over those drawbacks the gadget proposed here improves protection and information availability by incorporating aes-256 encryption sharding of records and decentralized metadata control by the introduction of a working prototype based on react.js, Ethereum wallet, ether.js and solidity this mission illustrates the viability of a decentralized statistics garage whilst resolving troubles with latency user adoption and value effectiveness experimental consequences affirm enhancements in safety and availability establishing a strong platform for additional research on decentralized storage architectures
The increasing demand for scalable blockchain has driven research into parallel execution models for smart contracts. Crystality is a novel smart contract programming language designed for parallel Ethereum Virtual Machines (EVMs), enabling fine-grained concurrency through Programmable Contract Scopes and Asynchronous Functional Relay. This paper presents the first formal structural operational semantics for Crystality, providing a rigorous framework to reason about its execution. We mechanize the syntax and semantics of Crystality in the theorem-proving assistant Coq, enabling formal verification of correctness properties. As a case study, we verify a simplified token transfer function, demonstrating the applicability of our semantics in ensuring smart contract correctness. Our work lays the foundation for formally verified parallel smart contracts, contributing to the security and scalability of blockchain systems.
Sharding blockchain networks face significant scalability challenges due to high frequencies of cross-shard transactions and uneven workload distributions among shards. To address these scalability issues, account migration offers a promising solution. However, existing migration solutions struggle with the high computational overhead and insufficient capture of complex transaction patterns. We propose AERO, a deep reinforcement learning framework to facilitate efficient account migration in sharding blockchains. AERO employs a prefix-based grouping strategy to enable group-level migration decisions and capture complex transaction patterns and relationships between accounts. We also implement a sharding blockchain system called AEROChain, which integrates AERO and aligns with the blockchain decentralization principle. Extensive evaluation with real Ethereum transaction data demonstrates that AERO improves the system throughput by 31.77% compared to existing solutions, effectively reducing cross-shard transactions and balancing shard workloads.
This paper introduces the Cartesian Merkle Tree, a deterministic data structure that combines the properties of a Binary Search Tree, a Heap, and a Merkle tree. The Cartesian Merkle Tree supports insertions, updates, and removals of elements in $O(\log n)$ time, requires $n$ space, and enables membership and non-membership proofs via Merkle-based authentication paths. This structure is particularly suitable for zero-knowledge applications, blockchain systems, and other protocols that require efficient and verifiable data structures.
With the rapid growth of the Internet of Things (IoT), maintaining data integrity, confidentiality, and authentication is now an imperative challenge. Most conventional cryptographic solutions cannot satisfy the specific constraints of IoT environments, which include limited computational resources, energy efficiency, and scalability. This study proposes a lightweight hybrid cryptographic framework combining Authenticated Encryption with Associated Data (AEAD) and Verifiable Random Functions (VRF) with Elliptic Curve Digital Signature Algorithm (ECDSA). The hybrid framework is intended to offer robust data integrity, secure authentication, and efficient encryption mechanisms with minimal computational overhead. Our solution makes use of AEAD (AES-GCM or ChaCha20-Poly1305) in order to establish both confidentiality and integrity within a single encryption process and with much less processing time than in traditional approaches such as AES-CTR with HMAC. Use of VRF guarantees that cryptographic algorithms result in verifiable randomness that increases replay attack and unauthorized entry security. ECDSA is utilized for lightweight digital signatures, providing non-repudiation without the computational overhead being higher than RSA-based integrity mechanisms. To ensure the efficacy of our methodology, we performed thorough benchmarking tests comparing AEAD + VRF + ECDSA with conventional cryptographic methods like AES-CTR + HMAC and integrity verification based on RSA. It is revealed by our benchmarks that our hybrid solution considerably cuts down encryption time, minimizes CPU utilization, and maximizes memory usage, thus being very suitable for resource-poor IoT devices. In contrast to AES-CTR + HMAC, which needs independent encryption and authentication phases, AEAD's hybrid approach has the least storage footprint and computational overhead. Furthermore, avoiding a dedicated verification step (necessary in HMAC-based designs) adds to system responsiveness. Our work adds to the literature through a scalable, effective, and secure cryptographic framework optimized for IoT use cases such as secure messaging, sensor data encryption, and access control in distributed systems. Real-world deployment in IoT platforms, post-quantum cryptographic augmentation, and implementing zero-knowledge proofs (ZKPs) for improved privacy-preserving authentication are next steps. By solving major problems in IoT security, our hybrid approach provides an efficient yet reliable alternative to state-of-the-art cryptographic solutions to guarantee end-to-end data confidentiality and integrity within contemporary IoT infrastructures.
Atefeh Zareh Chahoki, Maurice Herlihy, Marco Roveri
Conthereum is a concurrent Ethereum solution for intra-block parallel transaction execution, enabling validators to utilize multi-core infrastructure and transform the sequential execution model of Ethereum into a parallel one. This shift significantly increases throughput and transactions per second (TPS), while ensuring conflict-free execution in both proposer and attestor modes and preserving execution order consistency in the attestor. At the heart of Conthereum is a novel, lightweight, high-performance scheduler inspired by the Flexible Job Shop Scheduling Problem (FJSS). We propose a custom greedy heuristic algorithm, along with its efficient implementation, that solves this formulation effectively and decisively outperforms existing scheduling methods in finding suboptimal solutions that satisfy the constraints, achieve minimal makespan, and maximize speedup in parallel execution. Additionally, Conthereum includes an offline phase that equips its real-time scheduler with a conflict analysis repository obtained through static analysis of smart contracts, identifying potentially conflicting functions using a pessimistic approach. Building on this novel scheduler and extensive conflict data, Conthereum outperforms existing concurrent intra-block solutions. Empirical evaluations show near-linear throughput gains with increasing computational power on standard 8-core machines. Although scalability deviates from linear with higher core counts and increased transaction conflicts, Conthereum still significantly improves upon the current sequential execution model and outperforms existing concurrent solutions under a wide range of conditions.
Duarte Costa, João Ubiratan Moreira dos Santos, Tiago Dias, Miguel Correia
The real estate market, valued at trillions of euros, faces challenges such as illiquidity, inefficiencies, and the reliance on slow and costly processes with unnecessary intermediaries. This paper proposes a real estate marketplace built on Distributed Ledger Technology (DLT) to leverage its inherent decentralized properties. The system aims to accelerate processes with reduced costs, improved transparency, and a reduced level of fraud. The outcome is a secure decentralized finance (DeFi) platform involving transactions of Real-World Asset (RWA) tokens, providing a digital representation of the ownership rights of a real estate property.
Suhyeon Lee, Euisin Gee, Najmeh Soroush, Muhammed Ali Bingol · 5 authors
Simple commit-reveal beacons are vulnerable to last-revealer strategies, and existing descriptions often leave accountability and recovery mechanisms unspecified for practical deployments. We present Commit-Reveal$^2$, a layered design for blockchain deployments that cryptographically randomizes the final reveal order, together with a concrete accountability and fallback mechanism that we implement as smart-contract logic. The protocol is architected as a hybrid system, where routine coordination runs off chain for efficiency and the blockchain acts as the trust anchor for commitments and the final arbiter for disputes. Our implementation covers leader coordination, on-chain verification, slashing for non-cooperation, and an explicit on-chain recovery path that maintains progress when off-chain coordination fails. We formally define two security goals for distributed randomness beacons, unpredictability and bit-wise bias resistance, and we show that Commit-Reveal$^2$ meets these notions under standard hash assumptions in the random-oracle model. In measurements with small to moderate operator sets, the hybrid design reduces on-chain gas by more than 80% compared to a fully on-chain baseline. We release a publicly verifiable prototype and evaluation artifacts to support replication and adoption in blockchain applications.
Distributed Ledger Technologies (DLTs), including Blockchain, have revolutionized financial systems by offering decentralized, transparent, and secure mechanisms for data management and transactions. However, for these systems to maintain integrity and protect sensitive financial data, robust cryptographic techniques are essential. Cryptography ensures data confidentiality, authenticity, integrity, and non-repudiation, which are critical for the security of financial transactions in DLTs. This article examines the role of cryptographic protocols such as hashing, digital signatures, asymmetric encryption, and zero-knowledge proofs in safeguarding distributed ledgers. Furthermore, we explore their applications in securing financial transactions, preventing fraud, ensuring compliance, and enhancing the overall reliability of DLTs in financial systems. The discussion also delves into the challenges of cryptographic security in the face of emerging threats and the potential impact of quantum computing on existing cryptographic protocols.
One of the most emblematic theorems in the theory of distributed databases is Eric Brewer’s CAP theorem. It stresses the tradeoffs between Consistency, Availability, and Partition and states that it is impossible to guarantee all three of them simultaneously. Inspired by this, we introduce the new CAP theorem for autonomous consensus systems, and we demonstrate that, at most, two of the three elementary properties, Consensus achievement (C), Autonomy (A), and entropic Performance (P) can be optimized simultaneously in the generic case. This provides a theoretical limit to Blockchain systems’ decentralization, impacting their scalability, security, and real-world adoption. To formalize and analyze this tradeoff, we utilize the IoT micro-Blockchain as a universal, minimal, consensus-enabling framework. We define a set of quantitative functions relating each of the properties to the number of event witnesses in the system. We identify the existing mutual exclusions, and formally prove for one homogenous system consideration, that (A), (C), and (P) cannot be optimized simultaneously. This suggests that a requirement for concurrent optimization of the three properties cannot be satisfied in the generic case and reveals an intrinsic limitation on the design and the optimization of distributed Blockchain consensus mechanisms. Our findings are formally proved utilizing the IoT micro-Blockchain framework and validated through the empirical data benchmarking of large-scale Blockchain systems, i.e., Bitcoin, Ethereum, and Hyperledger Fabric.
Background: Even while traditional Raft is effective at leader election and log replication, it is not appropriate for sensitive applications like supply chains, financial systems, or healthcare because it lacks built-in privacy safeguards. Materials and Methods: A privacy-preserving Raft consensus method is proposed to solve the privacy issues that occur when private information is transferred between nodes in a distributed system such as a blockchain. Raft itself, by default, does not provide any steps toward ensuring data confidentiality during consensus. By employing privacy-preserving cryptographic techniques like homomorphic encryption and zero-knowledge proofs, nodes can reach consensus while keeping sensitive data private. Results: Traditional Raft performs much better in scenarios where performance matters, while Privacy-Perving Raft works better in a sensitive application to privacy (the average of write throughput is 5% lower than that of traditional Raft) and CPU is 40-60%. Conclusion: Based on the gained privacy by some computational costs, it will be valid to draw the conclusion that this works for privacy-sensitive applications within decentralized systems with these performance and security analyses.