Blockchain technology has fueled exponential growth across various industries, including finance, supply chain management, and healthcare, enabling greater transparency in transaction management and supporting decentralized implementations. This paper presents a comprehensive performance analysis of permissioned and permissionless blockchain platforms, specifically Hyperledger Fabric and Ethereum. The study evaluates these platforms with varying transaction workloads (100 to 1000 transactions) with a consistent network. Our objective is to measure key performance metrics such as send rate, throughput, latency, resource utilization, and transaction success rate using established benchmarking tools and methodologies. The findings offer valuable insights into the comparative strengths, limitations, and optimal use cases of these blockchain platforms across different performance parameters. The results indicate that Hyperledger Fabric achieves, on average, 3.5–4.5 times higher throughput and 10–12 times lower latency than Ethereum, while consuming 2.5–3 times less memory across tested workloads. In contrast, Ethereum demonstrates a higher send rate and lower CPU demand in some operations. Overall, the study suggests that Hyperledger Fabric is better suited for enterprise applications that demand high scalability and performance.
The Byzantine Generals Problem, introduced by Lamport, Shostak, and Pease, fundamentally addresses how a distributed system can achieve consensus even when some of its components are unreliable or malicious. This paper delves into the mathematical bounds that govern the solvability and efficiency of Byzantine Agreement (BA) protocols, specifically exploring the role of network topology in these limits. We examine classical impossibility results, such as the n $>$ 3f requirement for unauthenticated synchronous systems and the Fischer-Lynch-Paterson impossibility for deterministic asynchronous systems. Furthermore, we introduce "treasonous topologies" as a conceptual framework to systematically analyze how graph-theoretic properties like connectivity and diameter influence the minimum number of honest nodes required, message complexity, and time complexity. Special attention is paid to authenticated protocols which can relax certain bounds by employing digital signatures. This study elucidates the intricate relationship between adversarial capabilities, network structure, and the inherent mathematical constraints on achieving robust agreement in the presence of malicious nodes. We also touch upon modern applications in blockchain and distributed ledger technologies, where these theoretical bounds translate into practical considerations for security, scalability, and decentralization. A core contribution of this work is the synthesis of these established bounds with a detailed examination of how varying network structures fundamentally dictate protocol design and performance, offering a clearer lens through which to understand the vulnerabilities and strengths of real-world distributed systems.
Blockchain technologies underpin an expanding ecosystem of decentralized applications, financial systems, and infrastructure. However, the fundamental networking layer that sustains these systems, the peer-to-peer (P2P) layer, of all but the top few ecosystems remains largely opaque. In this paper, we present the first longitudinal, cross-network measurement study of 36 public blockchain networks. Over 9 months (since late 2024), we deployed 15 active crawlers, sourced data from two additional community crawlers, and conducted hourly connectivity probes (e.g., pings and protocol-level handshakes) to observe the evolving state of these networks. Furthermore, by leveraging Ethereum's discovery protocols, we inferred metadata for an additional 19 auxiliary networks that utilize the Ethereum peer discovery protocol. We also explored Internet-wide scans, which only require probing each protocol's default ports with a simple, network-specific payload. This approach allows us to rapidly identify responsive peers across the entire address space without having to implement custom discovery and handshake logic for every blockchain. We validated this method on Bitcoin and similar networks with known ground truth, then applied it to Cardano, which we could not crawl directly. Our study uncovers dramatic variation in network size from under 10 to more than 10,000 active nodes. We quantify trends in IPv4 versus IPv6 usage, analyze autonomous systems and geographic concentration, and characterize churn, diurnal behavior, and the coverage and redundancy of discovery protocols. These findings expose critical differences in network resilience, decentralization, and observability. Beyond characterizing each network, our methodology demonstrates a general framework for measuring decentralized networks at scale. This opens the door for continued monitoring, benchmarking, and more transparent assessments of blockchain infrastructure across diverse ecosystems.
The inherent complexity of cryptographic addresses in Web3 ecosystems poses significant usability problems. Decentralized Domain Services attempt to solve this challenge yet, in the meantime, jeopardize users’ pseudo-anonymity. This paper investigates the design and implementation of a decentralized naming system leveraging IOTA’s Move smart contract framework. We analyze the system architecture and provide a comparative evaluation against established domain name services such as ENS, SuiNS, SolanaNS, and Avvy, highlighting the unique advantages and limitations of our proposed solution. Moreover, we introduce a novel committee-bridge architecture managing off-chain hashed name storage, enabling selective disclosure of domain information while maintaining low computational overhead. We also present results from an evaluation that assesses the functioning and the performance of the system, which confirm the viability of the proposal.
As the blockchain ecosystem continues to diversify, the lack of interoperability among heterogeneous blockchain systems has become a critical bottleneck, leading to fragmented data silos and limited collaboration. Although numerous cross-chain protocols—such as atomic swaps, sidechains, and relay-based mechanisms—have been introduced to address this issue, they often face significant challenges related to privacy, security, and decentralization. In this paper, we propose a novel cross-chain protocol that enhances traditional hash-locking mechanisms by integrating zero-knowledge proofs and chameleon hash functions. Our approach ensures strong path confidentiality, such that reconstructing the payment path is computationally infeasible under the discrete logarithm assumption, even in partially compromised networks. Additionally, we introduce a multi-path atomic swap framework that supports concurrent routing and preserves transactional autonomy, enabling users to flexibly select preferred payment paths. We evaluate the performance through theoretical analysis and simulation. Comparative results demonstrate that our solution achieves secure atomicity with minimal trust assumptions and improved latency compared to existing methods.
To address the limitations of blockchain data storage capacity and uneven dis-tribution, this paper proposes a Chord dual-ring distributed storage method based on virtual nodes. Building upon the original Chord protocol, this approach introduces virtual rings to construct a “storage ring-virtual ring” dual-ring structure. Target virtual nodes are located through routing table lookups, and data is distributed across the storage ring via a name mapping mechanism. Sim-ulation experiments validate the proposed scheme's effectiveness by evalu-ating load balancing and query success rate across varying sharding granulari-ties. Results demonstrate that this approach not only efficiently achieves shard-ed storage for blockchain data but also ensures balanced distribution of block data.
With the growing adoption of blockchain interoperability, cross-chain token transfers have become a critical aspect of decentralized finance and blockchain ecosystems. Polkadot, a blockchain network designed to facilitate interoperability, employs a unique cross-chain message passing (XCMP) protocol to enable token transfers among the relay chain and parachains. However, token transfer time within this system, particularly the relationship between its average and standard deviation and underlying factors, has not been extensively investigated. In this paper, we conduct an empirical analysis of token transfer times in Polkadot and Kusama mainnets using ParaSpell to measure XCMP delays across various cross-chain messaging mechanisms, including Downward and Upward Message Passings and Horizontal Relay-routed Message Passing. Our findings reveal a significant correlation between the mean and standard deviation of token transfer times, suggesting the presence of fundamental systemic delays. Furthermore, we propose a theoretical model based on validator-to-validator broadcast time, which appears to be the dominant factor influencing transfer latency. Index Terms-Cross-chain message passing, Polkadot, Token transfer time, Experiment, Theoretical analysis
This paper presents EMDns, a domain name system based on Ethereum and MongoDB, addressing the centralization, security weaknesses, and privacy issues of the Domain Name System (DNS). EMDns enables automated and decentralized domain management to eliminate SPOF and authority dependence, while resolution is performed via local look-ups with hash comparison to protect privacy against deanonymization attacks. Experimental results show that EMDns maintains resolution efficiency while significantly enhancing security and privacy.
This study tackles the computational challenges of solving Markov Decision Processes (MDPs) for a restricted class of problems. It is motivated by the Last Revealer Attack (LRA), which undermines fairness in some Proof-of-Stake (PoS) blockchains such as Ethereum (\$400B market capitalization). We introduce pseudo-MDPs (pMDPs) a framework that naturally models such problems and propose two distinct problem reductions to standard MDPs. One problem reduction provides a novel, counter-intuitive perspective, and combining the two problem reductions enables significant improvements in dynamic programming algorithms such as value iteration. In the case of the LRA which size is parameterized by $κ$ (in Ethereum's case $κ$= 325), we reduce the computational complexity from $O(2^κκ^{2^{κ+2}})$ to $O(κ^4)$ (per iteration). This solution also provide the usual benefits from Dynamic Programming solutions: exponentially fast convergence toward the optimal solution is guaranteed. The dual perspective also simplifies policy extraction, making the approach well-suited for resource-constrained agents who can operate with very limited memory and computation once the problem has been solved. Furthermore, we generalize those results to a broader class of MDPs, enhancing their applicability. The framework is validated through two case studies: a fictional card game and the LRA on the Ethereum random seed consensus protocol. These applications demonstrate the framework's ability to solve large-scale problems effectively while offering actionable insights into optimal strategies. This work advances the study of MDPs and contributes to understanding security vulnerabilities in blockchain systems.
Chung, Siu Kei, Francisco Carpio, Andrei Navoichyk, Siarhei Valasovich · 11 authors
The internet faces a sovereignty crisis due to power concentration and data growth among a few hyperscalers, leading to centralization and loss of user control. This consolidation risks censorship and creates single points of failure. While Web3 offers decentralized solutions, they often sacrifice either scalability, decentralization, or security, which are key elements in the blockchain trilemma. These solutions also struggle with limited access to enterprise-grade hardware and frequently rely on centralized infrastructure. The Impossible Cloud Network (ICN) addresses these issues by creating a multi-tiered, decentralized infrastructure layer. ICN offers a composable service layer, an enterprise-grade hardware resource layer, and a transparent, permissionless HyperNode network for performance enforcement. By strategically decoupling and decentralizing each layer, ICN aims to provide an open, extensively scalable infrastructure that ensures digital sovereignty, eliminates single points of trust, enables service programmability, and offers a decoupled architecture for limitless possibilities in the future internet.
Ivan Homoliak, Martin Perešíni, Marek Tamaškovič, Timotej Ponek · 6 authors
Proof-of-Stake (PoS) consensus protocols often face a trade-off between performance and security. Protocols that preelect leaders for subsequent rounds are vulnerable to Denial-of-Service (DoS) attacks, which can disrupt the network and compromise liveness. In this work, we present PoS-CoPOR, a single-chain PoS consensus protocol that mitigates this vulnerability by integrating a native onion routing mechanism into the consensus protocol itself. PoS-CoPOR combines stake-weighted probabilistic leader election with an anonymization layer that conceals the network identity of the next block proposer. This approach prevents targeted DoS attacks on leaders before they produce a block, thus enhancing network resilience. We implemented and evaluated PoS-CoPOR, demonstrating its ability to achieve a throughput of up to $110 \mathrm{tx} / \mathrm{s}$ with 6 nodes, even with the overhead of the anonymization layer. The results show that native anonymization can provide robust DoS resistance with only a modest impact on performance, offering a solution to build secure and scalable PoS blockchains.
The emergence of Web 3.0, built upon blockchain technology, signals a paradigm shift toward decentralized applications and token economies. Digital-native millennials and Gen Z consumers demand hyper-personalization, convenience, and sustainability from brands, influencing a transition toward innovative approaches to customer engagement within the Web 3.0 landscape. Web 3.0 wallets play a crucial role in digital asset management, offering enhanced control and security to users. Many enterprises are expected to embrace Web 3.0, blending centralized services with decentralized applications to meet diverse business needs shortly. This transition is driven by Web 3.0’s unique capabilities, benefiting consumers and enterprises alike. However, the academic literature has limited awareness and scientific clarity regarding Web 3.0 and cryptocurrency integration. This chapter critically reviews cryptocurrency integration in the Web 3.0 ecosystem, delving into real-world case studies of successful projects and exploring opportunities, challenges, and future directions. In the Web 3.0 ecosystem, transactions are predominantly conducted using cryptocurrencies on decentralized blockchains, diverging from traditional fiat currencies issued by governments. The convergence of conventional finance and decentralized finance (DeFi) represents a pivotal moment in the evolution of the blockchain industry, promising to unlock new opportunities for financial inclusion and innovation. The regulatory challenges, scalability issues, and seamless integration of traditional finance and DeFi are poised to reshape the future of finance and foster a more transparent and accessible financial ecosystem.
In this paper, we design, implement, and empirically evaluate a tamper-evident, blockchain-secured solar energy logging system for resource-constrained edge Internet of Things (IoT) devices. Using a Merkle tree batching approach in conjunction with threshold-triggered blockchain anchoring, the system combines high-frequency local logging with energy-efficient, cryptographically verifiable submissions to the Ethereum Sepolia testnet, a public Proof-of-Stake (PoS) blockchain. The logger captured and hashed cryptographic chains on a minute-by-minute basis during a continuous 135 h deployment on a Raspberry Pi equipped with an INA219 sensor. Thanks to effective retrial and daily rollover mechanisms, it committed 130 verified Merkle batches to the blockchain without any data loss or unverifiable records, even during internet outages. The system offers robust end-to-end auditability and tamper resistance with low operational and carbon overhead, which was tested with comparative benchmarking against other blockchain logging models and conventional local and cloud-based loggers. The findings illustrate the technical and sustainability feasibility of digital audit trails based on blockchain technology for distributed solar energy systems. These audit trails facilitate scalable environmental, social, and governance (ESG) reporting, automated renewable energy certification, and transparent carbon accounting.
Blockchain technology, also known as Distributed Ledger Technology (DLT), is a decentralized, distributed ledger that chains encrypted blocks of data together. Its inherent properties, such as transparency, data integrity, and security measures, make it a prominent technology for various industries. Consensus protocols, hashing, and smart contracts enhance its security and reliability. However, scalability has proven to be a significant challenge in implementing public blockchains. The rapid growth of network nodes and miners' transaction calculations are the main causes of scalability issues. Efficient data scalability is crucial, as it can result in reduced maintenance costs, improved user experience, and higher agility. In this paper, we explore methods to enhance the consensus algorithm and compare its performance with existing algorithms.
Blockchain sharding is a promising solution for scalability but struggles to reach the expected performance due to the high ratio of cross-shard transactions. Account migration has emerged as a critical approach to optimizing shard performance. However, existing migration solutions suffer from inefficient handling of queued withdrawal transactions from a migrating account and inadequate priority mechanism for migration transaction, resulting in prolonged transaction makespan and reduced system throughput. This paper proposes Caravan, a novel blockchain sharding system for optimizing account migration. First, Caravan proposes a transaction aggregation-based migration scheme to efficiently handle withdrawal congestion post-migration. It incorporates a multi-level Merkle tree and cross-shard synchronization protocol to ensure cross-shard security. Second, Caravan presents an economic incentive-driven priority mechanism that motivates miners to perform transaction aggregation and prioritize migration transactions by increasing the associated revenue. Furthermore, its gas recycling strategy enables users to finance migration costs without awareness or extra expenses. Finally, we develop the Caravan prototype, deploy it on Alibaba Cloud, and experiment with real Ethereum transactions. The results show that compared to the state-of-the-art account migration schemes, Caravan significantly mitigates the transaction surge caused by migration, achieving up to a 3.2× throughput improvement and a 65% reduction in transaction confirmation latency. And users share considerable migration costs without extra expenses, significantly reduce system costs. The code for Caravan is available on GitHub.11Caravan are available athttps://github.com/Caravan-project/Caravan.
The rapid development of the Internet of Things (IoT) has intensified security and privacy challenges across data generation, transmission, and storage. This study introduces a blockchain-based secure edge storage model tailored for IoT environments and presents a lightweight consensus algorithm, Deep Q-Network (DQN)-Raft+, which incorporates deep reinforcement learning. By combining the decentralized features of edge computing and blockchain, the model enables automated data access control through smart contracts. Furthermore, it optimizes leader node selection in the Raft consensus process using a DQN, formulating the consensus as a Markov Decision Process to enhance responsiveness and privacy protection in dynamic network conditions. Experiments were performed in a simulated environment using TensorFlow 2.6 and a MySQL database. The performance of DQN-Raft+ was compared against traditional consensus algorithms, including Proof of Work, Proof of Stake, Practical Byzantine Fault Tolerance, and Delegated Byzantine Fault Tolerance. Results indicate that DQN-Raft+ significantly reduces block generation delay (175.77 ms) and achieves a high privacy protection score (0.95). It also maintains a low data loss rate of 0.01%, demonstrating enhanced robustness and real-time capability. These findings indicate that DQN-Raft+ effectively strengthens data security and privacy in IoT systems, offering a technically sound and efficient mechanism for secure data exchange. The study provides both a theoretical framework and practical direction for future research in secure IoT deployment.
Asst. Prof. Panchami M Hegde, Asst. Prof. Swetha M
Carpooling has emerged as one of the most practical strategies for reducing the growing challenges of traffic congestion, fuel consumption, and environmental pollution, yet conventional carpooling systems that are operated through centralized platforms continue to face numerous issues that restrict their effectiveness and adoption. Existing solutions largely depend on intermediaries to coordinate between drivers and passengers, creating a system that lacks transparency, suffers from high service costs, and exposes user data to privacy risks and security breaches. Moreover, traditional systems are often criticized for inefficient dispute resolution, a reliance on single points of failure such as central servers, and the absence of mechanisms that foster accountability and long-term trust among users. These weaknesses make centralized carpooling platforms vulnerable to manipulation, biased practices, and technical outages, thereby limiting their scope as sustainable mobility solutions. To address these persistent challenges, blockchain technology—specifically the Ethereum ecosystem—offers a transformative alternative. Ethereum supports the development of decentralized applications (dApps) driven by smart contracts, which are self-executing agreements coded directly onto the blockchain. By embedding business logic into these contracts, processes such as ride creation, ride booking, payment settlements, user verification, and rating are automated, ensuring that interactions remain tamper-proof, transparent, and immune to third-party manipulation.