In this paper, we explored the Transaction Network on Ethereum from August 7, 2015 to November 22, 2024 with the perspective of complex network science. We aim to identify key network characteristics, such as disassortativity and core nodes stability. Our analysis reveals that high-degree nodes, typically mining pools and exchanges, preferentially connect with lowdegree nodes and rarely connected with each other. Additionally, we find that the ETN core structure remains robust over time. These findings contribute to blockchain network regulation and offer insights for future research into cryptocurrency transaction dynamics.
After successfully transitioning from proof-of-work to proof-of-stake, the Ethereum blockchain’s developer community has set an ambitious goal of achieving rapid block finalization, ideally completing it before the next block proposal, a concept known as single slot finality. Currently, block finalization on the ETH beacon chain takes ∼ 15 minutes to collect the attestation from the majority of the validators. The current protocol has several drawbacks, including slow finalization, high bandwidth usage and a rigid aggregation structure that is prone to failures. The challenge is collecting cryptographic signatures from close to a million validators distributed worldwide, connected to the network in 12 seconds without requiring high bandwidth internet connections from the peers in the network. This study presents an alternative scheme that has the potential to realize single-slot finality. Ours is a fully decentralized approach in which no node has a specific role, rendering it more robust than the current one. We simulate our heuristics on the Ethereum network topology and demonstrate that it can efficiently collect a million attestations from almost ten thousand physical nodes.
Luigi Vigneri, Darcy Camargo, Olivia Saa, Andrew Cullen
The rapid advancements in distributed ledger technology (DLT) have produced novel systems combining high throughput, low latency and smart contract programmability. However, designing robust incentives schemes for such advanced protocols remains a critical challenge. Weaknesses in existing incentives schemes, particularly in reward distribution and incentive alignment, can hinder protocol adoption and long-term sustainability. In this paper, we propose a unified framework for comprehensive analysis of a wide range of DLTs. Our framework extends existing methodologies for studying transaction fee mechanisms by incorporating reward distribution among multiple actors involved in the consensus process, addressing critical gaps in the literature. We introduce a categorisation of incentive mechanisms and apply the above framework to the modern consensus protocols of Sui and IOTA, offering comparisons with more ‘traditional’ systems including Ethereum and Bitcoin.
B S Rajeshwari, Shamanth K Murthy, S M, S P Shashank
Cross-Chain interoperability is one of the critical challenges in Blockchain technology, which enables seamless communication and asset transfers between different chains. Existing interoperability solutions such as atomic swaps, relay chains, notary schemes and blockchain bridges, often face security vulnerabilities, scalability limitations, and trust assumptions that hinder their efficiency. Zero-Knowledge Proofs (ZKPs) offer a promising approach to enhancing the security and privacy of interoperability mechanisms by enabling verification of computations without revealing the transaction details. This research paper explores existing Cross-Chain interoperability solutions, including the problem they address, such as atomicity, privacy, and decentralization, their implementation or methodology used and their drawbacks that need to be further optimized. Furthermore, the paper explores the integration of ZKPs in interoperability protocols, evaluating their potential to achieve trustless and privacy-preserving crosschain communication and conclude with the outline of future research directions to improve and optimize the current limitations and develop better solutions.
Current decentralized architectures, while powerful, operate in silos.Intent-centric protocols solve for user expression but create trust assumptions for off-chain solvers. 1 Verifiable computation markets address this trust but lack a native framework for complex, goal-oriented coordination. 2Formal verification methods provide security for individual components but struggle with the emergent complexity of their composition. 3 This paper introduces Chimera, a novel protocol architecture that unifies these disparate paradigms.Chimera integrates generalized intent-centricity, a decentralized market for verifiable AI agents (zk-Agents), and autonomic governance inspired by closed-loop control theory, all within a framework of provable composability.We argue that by treating all network actions-from swaps to governance-as intents fulfilled by verifiable AI agents, and by governing the system with an autonomic management layer that monitors and adapts its own parameters, Chimera enables a new class of self-organizing, intelligent, and provably secure decentralized applications.We present the full architectural design and demonstrate its power through case studies in verifiable AI-driven finance and autonomic public goods funding.
Bertalan Zoltán Péter, Zsófia Ádám, Zoltán Micskei, Imre Kocsis
Due to their decentralized and trustless nature, blockchain and distributed ledger technologies are increasingly used in several domains, including critical applications. The behavior of such blockchain-integrated systems is typically driven by smart contracts. However, smart contracts are application-specific software and may contain faults with severe system-level impacts. This is especially true in the case of the extensively used Hyperledger Fabric (HLF) platform, where smart contracts are written in general-purpose languages (Java, among others), and applications can go far beyond handling virtual-currency-like assets. In this work, we present a novel formal-verification-based approach to smart contract verification and a high-level empirical model of the HLF platform. Our Smart Contract in the Loop (SCIL) method uses a model checker (Java Pathfinder) to check whether specific error properties hold for a given smart contract, while a predefined combination of platform-level fault modes is active. We facilitate the checking of HLF smart contracts without modification and enable the propagation or non-propagation of platform faults through the smart contracts to the system failure level.
Benjamin Gillen, Rashmi Ranjan Bhuyan, Gourab Mukherjee, Austin Pollok
The Ethereum blockchain plays a central role in the broader cryptocurrency ecosystem, enabling a wide range of financial activity through the use of smart contracts. This paper investigates how individual Ethereum wallets responded to the collapse of FTX, one of the largest centralized cryptocurrency exchanges. Moving beyond price-based event studies, we adopt a bottom-up approach using granular wallet-level data. We construct a representative sample of Ethereum addresses and analyze their transaction behavior before and after the collapse using an explainable artificial intelligence (XAI) framework. Our proposed framework addresses data scarcity in high-resolution wallet-level daily transactions by employing a calibrated zero-inflated generalized linear fixed effects model. Our analysis quantifies distinct shifts in transaction intensity and stablecoin usage, highlighting a flight to safety within the ecosystem. These findings underscore the value of a bottom-up methodology for quantifying the user-level impact of blockchain-based shocks, offering insights beyond traditional price-level analysis through wallet-level data.
In this article, we explore the complexities surrounding token issuance within blockchain networks and their integration with decentralized exchanges (DEXs). With the swift evolution of cryptocurrency and blockchain technologies, token issuance has become a prevalent means of funding initiatives and creating novel digital assets. This journey involves tackling a spectrum of technical and organizational hurdles, ranging from choosing the right token standard to crafting, testing, and deploying smart contracts on the Ethereum blockchain. Further, we explore the integration of issued tokens with decentralized exchanges, highlighting the importance of such platforms in enabling token trading without reliance on centralized intermediaries. The technical solutions required for this integration, along with considerations of the unique aspects of exchange protocols, are critically analyzed. We pay special attention to the ERC-20 standard for token creation, detailing the process of smart contract development and deployment on the Ethereum network. Additionally, the advantages and limitations of integrating tokens with DEXs are examined, providing a comprehensive understanding of both the opportunities and challenges within the rapidly evolving digital asset ecosystem. This study extends the current understanding of token dynamics by incorporating an in-depth analysis of scalability challenges, cross-chain interoperability, and the evolving regulatory landscape affecting token issuance and trading. By offering practical recommendations for overcoming identified hurdles, this research guides practitioners and policymakers in navigating the complexities of the decentralized finance (DeFi) space, making a significant contribution to the field of blockchain technology and digital finance.
Blockchain technology plays a crucial role for numerous decentralized applications and cryptocurrencies. Still, there are many networks that rely on incompetent and unmanageable consensus mechanisms. This paper proposes an improved Round Robin Proof of Stake consensus protocol as a solution for the restrictions of outdated Proof of Work (PoW) and Proof of Stake (PoS) systems. By using Python simulation, we examine the validator’s behavior, energy efficiency, and fairness in the consensus protocol. Our discoveries reveal that RR-PoS significantly helps in improving the efficiency and encourages unbiased participation of validators, designing it as an innovative solution for blockchain consensus. Python helps in allowing preciseness to the RR-PoS model that helps in integrating important features, i.e., validator rotation, energy modeling of RR-PoS, and incorporating essential features like validator rotation, cooldown periods, and energy-aware block proposals. The comprehensive approach of this enables close monitoring of validator interactions and ensures fair opportunity distribution. Ultimately, RR-PoS emerges as a compelling and sustainable consensus alternative for future blockchain networks.
Patrick Spiesberger, Jan Droll, Hannes Hartenstein
In the Ethereum system, the exclusion of specific transactions is currently feasible with minimal effort due to a power imbalance among entities. This censorship opportunity threatens the dependability of time-sensitive services deployable on Ethereum. In this paper, we look at this threat from an access control perspective and attribute it to a lack of accountability for censorship, a lack of policy definition and enforcement, as well as to the lack of disincentivization of policy violation. We propose an approach to enforceable policies in Ethereum. Furthermore, we demonstrate how a specific policy can address the shortcomings of existing censorship mitigation techniques, particularly Inclusion Lists. Under the assumption that block assemblers are unwilling to incur significant financial penalties as well as that the local view on the network messages is sufficiently consistent, the proposed approach guarantees the inclusion of a transaction in a block within 27 seconds in a non-saturated network. The empirical validation of sufficiently consistent views on outstanding transactions is currently in progress.
Nowadays, checkpoints have been proven to be an effective solution to ensure slashability in proof-of-stake (PoS) consensus, and Tas et al.'s cutting-edge solution in S&P 2023 is a typical example. Unfortunately, despite progress, hour-level transaction delays and annually around 10 K dollar checkpoint costs make existing related solutions still unacceptable in realworld PoS applications. In this paper, we propose SecPoS, a slashable PoS consensus with second-level transaction delays and one-time checkpoint costs. To achieve these design goals, we draw inspiration from Pixel+ signatures and chameleon hash functions to design a novel bilateral blockchain structure, achieving twoblock transaction finalization via only uploading the first block of our chain as checkpoints. Next, considering practical application requirements, we address a series of following challenges, such as bilateral immutability, blockchain forks, determination of the main chain, and malicious attacks from PoS members. In detail, we propose two constructions of SecPoS, i.e., SecPoS – A and SecPoS – B. SecPoS – A and SecPoS – B have a tradeoff between transaction delays and block numbers packed in an epoch. Compatible with most existing one-way blockchains, we implement and outsource a prototype SecPoS to facilitate research11https://github.com/Academic-Paper-Codes/SecPoS-Consensus, and prove the security of SecPoS. Experiments on this prototype show that SecPoS – A and SecPoS – B require around 5s and 100s transaction delays, respectively, and both require 2 dollars one-time checkpoint costs.
As Distributed Ledger Technologies (DLTs) mature, the inherent performance and scalability shortcomings of linearly structured blockchain designs become better understood. Protocols based on Directed Acyclic Graphs (DAGs) have been proposed to address such shortcomings. DAG-based protocols differ from traditional DLTs in the way they build and represent knowledge about transactions and relations between them. While traditional DLTs have straightforward homogeneous semantic attached to blocks and links between blocks, the semantic of vertices and edges in DAG-based protocols is nuanced and varied. In this work, we identify almost a dozen of knowledge-building dimensions in DAG-based DLTs, none of which have been studied before. Knowledge-building is important in DAG-based DLTs because of its significant impact on the size of the DAG, the pace at which new transactions are added, the finality of transactions, and so on. We analyze 40 DAG-based DLTs from this perspective, summarize our results in a taxonomy, and identify a number of research gaps.
Layer-2 protocols can assist Ethereum's limited throughput, but globally broadcasting layer-2 data limits their scalability. The Danksharding evolution of Ethereum aims to support the selective distribution of layer-2 data, whose availability in the network is verified using randomized data availability sampling (DAS). Integrating DAS into Ethereum's consensus process is challenging, as pieces of layer-2 data must be disseminated and sampled within four seconds of the beginning of each consensus slot. No existing solution can support dissemination and sampling under such strict time bounds. We propose PANDAS, a practical approach to integrate DAS with Ethereum under Danksharding's requirements without modifying its protocols for consensus and node discovery. PANDAS disseminates layer-2 data and samples its availability using lightweight, direct exchanges. Its design accounts for message loss, node failures, and unresponsive participants while anticipating the need to scale out the Ethereum network. Our evaluation of PANDAS's prototype in a 1,000-node cluster and simulations for up to 20,000 peers shows that it allows layer-2 data dissemination and sampling under planetary-scale latencies within the 4-second deadline.
We present the availability and reproducibility report of the ACM SIGMOD 2025 paper titled ''InTime: Towards Performance Predictability In Byzantine Fault Tolerant Proof-of-Stake Consensus''. Following the instructions provided the authors, we evaluated the artifacts hosted on Github. The reviewers confirmed that the codebase is functional and evaluatable. Reproducibility was straightforward as the authors provided automated scripts that simplified the execution of experiments. Experiments on single machine were reproduced while experiments requiring a large cluster of machines are constrained by limited resource capacity and instructions. Hence, the paper's core claims were partially reproduced.
This paper presents a formalised architecture for synthetic agents designed to retain immutable memory, verifiable reasoning, and constrained epistemic growth. Traditional AI systems rely on mutable, opaque statistical models prone to epistemic drift and historical revisionism. In contrast, we introduce the concept of the Merkle Automaton, a cryptographically anchored, deterministic computational framework that integrates formal automata theory with blockchain-based commitments. Each agent transition, memory fragment, and reasoning step is committed within a Merkle structure rooted on-chain, rendering it non-repudiable and auditably permanent. To ensure selective access and confidentiality, we derive symmetric encryption keys from ECDH exchanges contextualised by hierarchical privilege lattices. This enforces cryptographic access control over append-only DAG-structured knowledge graphs. Reasoning is constrained by formal logic systems and verified through deterministic traversal of policy-encoded structures. Updates are non-destructive and historied, preserving epistemic lineage without catastrophic forgetting. Zero-knowledge proofs facilitate verifiable, privacy-preserving inclusion attestations. Collectively, this architecture reframes memory not as a cache but as a ledger - one whose contents are enforced by protocol, bound by cryptography, and constrained by formal logic. The result is not an intelligent agent that mimics thought, but an epistemic entity whose outputs are provably derived, temporally anchored, and impervious to post hoc revision. This design lays foundational groundwork for legal, economic, and high-assurance computational systems that require provable memory, unforgeable provenance, and structural truth.
Dumitrel Loghin, Shuang Liang, S. Liu, Xiong Liu · 6 authors
Zero-knowledge proofs (ZKP) are becoming a gold standard in scaling blockchains and bringing Web3 to life. At the same time, ZKP for transactions running on the Ethereum Virtual Machine require powerful servers with hundreds of CPU cores. The current zkProver implementation from Polygon is optimized for x86-64 CPUs by vectorizing key operations, such as Merkle tree building with Poseidon hashes over the Goldilocks field, with Advanced Vector Extensions (AVX and AVX512). With these optimizations, a ZKP for a batch of transactions is generated in less than two minutes. With the advent of cloud servers with ARM which are at least 10% cheaper than x86-64 servers and the implementation of ARM Scalable Vector Extension (SVE), we wonder if ARM servers can take over their x86-64 counterparts. Unfortunately, our analysis shows that current ARM CPUs are not a match for their x86-64 competitors. Graviton4 from Amazon Web Services (AWS) and Axion from Google Cloud Platform (GCP) are 1.6X and 1.4X slower compared to the latest AMD EPYC and Intel Xeon servers from AWS with AVX and AVX512, respectively, when building a Merkle tree with over four million leaves. This low performance is due to (1) smaller vector size in these ARM CPUs (128 bits versus 512 bits in AVX512) and (2) lower clock frequency. On the other hand, ARM SVE/SVE2 Instruction Set Architecture (ISA) is at least as powerful as AVX/AVX512 but more flexible. Moreover, we estimate that increasing the vector size to 512 bits will enable higher performance in ARM CPUs compared to their x86-64 counterparts while maintaining their price advantage.
The European Union's (EU) data strategy aims to create a single market for seamless data flow while ensuring proper governance, privacy, and data protection. In this paper, we present SEDIMARK, an EU project, that builds on this strategy by developing a fully decentralised, secure data marketplace. The goal of SEDIMARK is to build a complete toolbox that enables users to purchase and process data assets. The toolbox includes tools for data cleaning, decentralised machine learning models and secure data exchange. SEDIMARK offers users full control over data assets by enabling them to keep their data locally and thus removing the need for central servers. With customisable pipelines and tools, SEDIMARK supports a wide range of users, from novices to experts, promoting seamless collaboration and fair access to high-quality datasets across Europe. The decentralised connectivity in SEDIMARK is achieved with the use of Distributed Ledger Technology (DLT). Furthermore, SEDIMARK's architecture features a unique Connector component using Self Sovereign Identities (SSI), fostering trust and secure interactions. Transactions in SEDIMARK are stored in a Registry, a decentralised, immutable, non-repudiable and permissionless database. Together the technologies used in SEDIMARK ensure privacy, trust and data quality for secure management, sharing, and monetisation of assets in data spaces.
Software-defined networking (SDN) enhances network management by centralizing control, but its reliance on a single controller introduces vulnerabilities such as distributed denial-of-service (DDoS) attacks and unauthorized access. Traditional SDN architectures lack authentication mechanisms for verifying network compliment, allowing malicious switches to disrupt operations. To mitigate these risks, blockchain technology provided a decentralized and tamper-proof authentication mechanism by recording the registration status of network devices using smart contracts. By integrating blockchain with the SDN controller (RYU) via Web3, switches are authenticated based on their Datapath Identifier (DPID), enabling secure enforcement of OpenFlow policies. This approach ensures that only registered switches can forward traffic, effectively isolating unauthorized devices and reducing the impact of DDoS attacks. The prototype implementation demonstrates improved security and trust in SDN environments. We combined blockchain’s immutability with SDN’s dynamic programmability.
Gang Xu, Shiyuan Xu, Xinyu Fan, Yibo Cao · 7 authors
The Industrial Internet of Things (IIoT) has been widely studied, which dramatically enhanced the manufacturing efficiency and service elasticity. However, how to ensure the data confidentiality and security in the event-driven publish/subscribe communication model becomes a cumbersome problem. To address this concern, ring signatures have been researched deeply. Nevertheless, existing solutions have large computational burdens and neglect to incorporate reporting and tracing features, which makes it impractical for IIoT. In this way, research focus on designing an efficient report and traceable ring signature is still far-reaching. In this article, we propose RAT ring, a novel report and traceable ring signature, which provides publisher authentication, anonymous communication, reporting, and tracing. To achieve this, we adopt the zero knowledge proof to verify the authenticity of publisher data, and the signature of knowledge to trace the signature. Then, we formalize and prove the security of our scheme. Eventually, through comprehensive performance evaluation, our scheme outperforms prior works by approximately up to 51 times in terms of total computational overhead. These results demonstrate that our design is practical and effective for data privacy-preserving in IIoT.