Blockchain Papers

Smity Agarwal

No abstract is available for this record.

Jitao Wang, Changhao Wu, Yakun Chen, Weili Han

No abstract is available for this record.

Yujiu Xiong, Amit Kumar Jaiswal, Tao Tang, QianZhou Zuo · 6 authors

No abstract is available for this record.

Brugeres, Maxence, Languille, Victor, Kuznetsov, Petr, Zarfaoui, Hamza

We propose a decentralized asset-transfer system that enjoys full privacy: no party can learn the details of a transaction, except for its issuer and its recipient. Furthermore, the recipient is not aware of the sender’s identity. Our system does not rely on consensus or synchrony assumptions, and therefore, it is responsive, since it runs at the actual network speed. Under the hood, every transaction creates a consumable coin equipped with a non-interactive zero-knowledge proof (NIZK) that confirms that the issuer has sufficient funds without revealing any information about her identity, the recipient’s identity, or the payment amount. Moreover, we equip our system with a regulatory enforcement mechanism that can be used to regulate transfer limits or restrict specific addresses from sending or receiving funds, while preserving the system’s privacy guarantees. Finally, we report on PaxPay, our implementation of Fully Private Asset Transfer (FPAT) that uses the Gnark library for the NIZKs. In our benchmark, PaxPay exhibits better performance than earlier proposals that either ensure only partial privacy, require some kind of network synchrony or do not implement regulation features. Our system thus reconciles privacy, responsiveness, regulation enforcement and performance.

Marco Benedetti, Francesco De Sclavis, Marco Favorito, Giuseppe Galano · 7 authors

No abstract is available for this record.

Pavloff, Ulysse, Amoussou-Guenou, Yackolley, Tucci-Piergiovanni, Sara

This paper investigates whether following the fork-choice rule in the Ethereum PoS consensus protocol constitutes a Nash equilibrium - i.e., whether the protocol that maintains the canonical chain in Ethereum is incentive-compatible. Specifically, we explore whether selfish participants may attempt to manipulate the fork-choice rule by forking out previous blocks and capturing the rewards associated with those blocks. Our analysis considers two strategies for participants: the obedient strategy, which adheres to the prescribed protocol, and the cunning strategy, which attempts to manipulate the fork-choice rule to gain more rewards. We evaluate the conditions under which selfish participants might deviate from the obedient strategy. We found that, in a synchronous system, following the prescribed fork-choice rule is incentive-compatible. However, in an eventually synchronous system, the protocol is eventually incentive-compatible - that is, only a limited number of proposers will find it profitable to fork the chain during the synchronous period. After this sequence of cunning proposers, subsequent proposers will find it more profitable to follow the protocol.

Nathaniel G. Gordon, Gregory Falco

Modern space vehicles capture a wealth of sensor data that is in high-demand by a wide range of commercial and nation-state beneficiaries. This data can be used to monitor our planet, monitor space traffic and manage collision avoidance, among other use cases. While there is ongoing investment into cross-linking satellite constellations and building an ‘on-orbit internet’, it remains unclear how the integral requesting and delivery of this data will be facilitated. We propose a distributed marketplace for space domain awareness that engages smart contracts and a distributed ledger to manage the engagement of satellites across an untrusted ecosystem. Furthermore, this work implements a simulated on-orbit marketplace consisting of independent nodes able to efficiently and securely exchange data and services under a series of representative scenarios. The marketplace software payload was designed to conform to the power and compute constraints of a modern space vehicle while implementing secure smart contracting and format-preserving validation techniques, demonstrating the practical viability of the on-orbit marketplace as a concept.

Buti Sello

This thesis investigates the security challenges of blockchain consensus mechanisms, arguing that sub-stratal to these challenges is the widely adopted mindset of probabilistic finality, which in itself is an inherent and significant vulnerability. Core to this problem is the inability or probabilistic protocols such a Proof of Work and Proof of Stake to provide the necessary deterministic and irreversible transaction settlement that high-integrity systems require. This is primarily due to their use of a “longest chain” rule. This deficiency is immensely amplified on new blockchains, as they do not possess the accumulated economic and computational security of mature networks. New blockchains face a serious “bootstrap security problem” which makes them highly prone to catastrophic 51% attacks. The research methodology follows a multi-stage, systematic approach, beginning with a comprehensive literature review to classify and analyse the existing threat landscape across major consensus protocols. Then a targeted theoretical critique of probabilistic finality is presented next, as is a systematic evidence-based assessment of some of the economic and architectural vulnerabilities of nascent networks. The findings of this analytical work confirm that the security of a blockchain is not static but evolves, and that the initial phase of a network's lifecycle is its most insecure. The main contribution of this thesis is the design and proposal of a novel consensus algorithm called “Erdos” that aims to address these issues directly. Erdos offers a deterministic process for block finalization that involves multiple rounds of vetting and a fair, resource-independent node selection. The design provides a strong fork resistance that stops the risk of 51% attacks and double spending right from the inception and launch of a network. Moreover, it reduces the centralisation pressure that proves to be a problem for nascent protocols. The primary implication of this research is that the future of secure, decentralised systems, particularly for new and emerging applications, necessitates an architectural shift away from probabilistic models towards deterministic, fair, and resilient consensus protocols as exemplified by the Erdos algorithm.

Ciampi, Michele, Lu, Yun, Ostrovsky, Rafail, Zikas, Vassilis

Common blockchain protocols are monolithic, i.e., their security relies on a single assumption, e.g., honest majority of hashing power (Bitcoin) or stake (Cardano, Algorand, Ethereum). In contrast, so-called optimistic approaches (Thunderella, Meshcash) rely on a combination of assumptions to achieve faster transaction liveness. We revisit, redesign, and augment the optimistic paradigm to a tiered approach. Our design assumes a primary (Tier 1) and a secondary (Tier 2, also referred to as fallback) blockchain, and achieves full security also in a tiered fashion: If the assumption underpinning the primary chain holds, then we guarantee safety, liveness and censorship resistance, irrespectively of the status of the fallback chain. And even if the primary assumption fails, all security properties are still satisfied (albeit with a temporary slow down) provided the fallback assumption holds. To our knowledge, no existing optimistic or tiered approach preserves both safety and liveness when any one of its underlying blockchain (assumptions) fails. The above is achieved by a new detection-and-recovery mechanism that links the two blockchains, so that any violation of safety, liveness, or censorship resistance on the (faster) primary blockchain is temporary - it is swiftly detected and recovered on the secondary chain - and thus cannot result in a persistent fork or halt of the blockchain ledger. We instantiate the above paradigm using a primary chain based on proof of reputation (PoR) and a fallback chain based on proof of stake (PoS). Our construction uses the PoR and PoS blockchains in a mostly black-box manner - where rather than assuming a concrete construction we distil abstract properties on the two blockchains that are sufficient for applying our tiered methodology. In fact, choosing reputation as the resource of the primary chain opens the door to an incentive mechanism - which we devise and analyze - that tokenizes reputation in order to deter cheating and boost participation (on both the primary/PoR and the fallback/PoS blockchain). As we demonstrate, such tokenization in combination with interpreting reputation as a built-in system-wide credit score, allows for embedding in our two-tiered methodology a novel mechanism which provides collateral-free, multi-use payment-channel-like functionality where payments can be instantly confirmed.

Dr. N. R. Ananthanarayanan, Mr. Suresh Subbu

Abstract: Blockchain technology is a transformative distributed ledger paradigm that enables secure, transparent, and tamper-resistant data management without centralized authorities. At its core lies the consensus mechanism-the protocol through which distributed nodes agree on a single canonical transaction history. This paper presents a structured review of major blockchain consensus schemes including Proof-of-Work (PoW), Proof-of-Stake (PoS), and Practical Byzantine Fault Tolerance (PBFT), as well as emerging hybrid models such as Avalanche and Polkadot. The analysis evaluates sustainability, scalability, security, and decentralization characteristics, offering a comprehensive comparison across these mechanisms. The findings highlight inherent trade-offs related to energy consumption, throughput, finality, validator governance, and fault tolerance. The study concludes by identifying open research challenges important for designing next-generation blockchain systems capable of supporting large-scale, mission-critical applications. Keywords: Avalanche, Blockchain, Consensus Mechanisms, PBFT, PoS, PoW, Scalability, Security, Sustainability. Title: Study and Comparative Analysis of Blockchain Consensus Mechanisms Author: Dr. N. R. Ananthanarayanan, Mr. Suresh Subbu International Journal of Recent Research in Mathematics Computer Science and Information Technology ISSN 2350-1022 Vol. 12, Issue 2, October 2025 - March 2026 Page No: 1-15 Paper Publications Website: www.paperpublications.org Published Date: 25-November-2025 DOI: https://doi.org/10.5281/zenodo.17711245 Paper Download Link (Source) https://www.paperpublications.org/upload/book/Study%20and%20Comparative%20Analysis%20of%20Blockchain-25112025-2.pdf

Aggelos Kiayias, Ηλίας Κουτσουπιάς, Evangelos Markakis, Panagiotis Tsamopoulos

We study a game-theoretic model for pool formation in Proof of Stake blockchain protocols. In such systems, stakeholders can form pools as a means of obtaining regular rewards from participation in ledger maintenance, with the power of each pool being dependent on its collective stake. The question we are interested in is the design of mechanisms, i.e., "reward sharing schemes," that suitably split rewards among pool members and achieve favorable properties in the resulting pool configuration. With this in mind, we initiate a non-cooperative game-theoretic analysis of the well known Shapley value scheme from cooperative game theory into the context of blockchains. In particular, we focus on the oceanic model of games, proposed by Milnor and Shapley (1978), which is suitable for populations where a small set of large players coexists with a big mass of rather small, negligible players. This provides an appropriate level of abstraction for pool formation processes that occur among the stakeholders of a blockchain. We provide comparisons between the Shapley mechanism and the more standard proportional scheme, in terms of attained decentralization, via a Price of Stability analysis and in terms of susceptibility to Sybil attacks, i.e., the strategic splitting of a players' stake with the intention of participating in multiple pools for increased profit. Interestingly, while the widely deployed proportional scheme appears to have certain advantages, the Shapley value scheme, which rewards higher the most pivotal players, emerges as a competitive alternative, by being able to bypass some of the downsides of proportional sharing in terms of Sybil attack susceptibility, while also not being far from optimal guarantees w.r.t. decentralization. Finally, we also complement our study with some variations of proportional sharing, where the profit is split in proportion to a superadditive or a subadditive function of the stake, showing that our results for the Shapley value scheme are maintained in comparison to these functions as well.

Fan, Yixuan

Consensus serves as a foundational mechanism in both social coordination and distributed technical systems. While machine consensus research in engineering focuses on fault tolerance and synchronization, social science emphasizes human deliberation, participation, and governance. However, the increasing convergence of human and machine decision making, exemplified by decentralized autonomous organizations (DAOs), intelligent agents, and cyber-physical social systems, demands a more integrated and theoretically robust understanding of consensus. This thesis addresses this interdisciplinary gap by investigating consensus across three interconnected dimensions: probabilistic fault-tolerant consensus systems, human-driven voting mechanisms in DAOs, and a unified conceptual framework bridging human and machine consensus. The first part of the thesis focuses on distributed fault-tolerant consensus in uncertain environments. Traditional approaches often rely on deterministic assumptions about node failures and fixed quorum rules. These assumptions may fail to reflect real-world systems where node behaviour is influenced by heterogeneous reliability and probabilistic failures. To address this limitation, a probabilistic modelling framework is proposed, treating node reliability as a stochastic variable. Within this framework, consensus outcomes are classified into three categories: safe, risky, and compromised. A new concept, referred to as the reliability quorum, is introduced to provide a more flexible threshold for achieving consensus based on targeted reliability levels. This model enables system designers to tailor fault tolerance according to specific reliability requirements, providing both analytical clarity and practical adaptability. The second part investigates consensus in decentralized systems primarily driven by human-oriented agents, using DAO voting as a representative case. In contrast to deterministic coordination among machines, DAO consensus arises from voluntary participation, heterogeneous voting power, and non-uniform approval conditions. To guide the analysis, the thesis introduces the DAO governance triangle alongside the SEED framework, which qualitatively evaluates voting mechanisms across four dimensions: Security, Efficiency, Effectiveness, and Decentralization. Building on this conceptual foundation, the study proceeds to a quantitative investigation of two key SEED dimensions. For decentralization, a stochastic process model is proposed to capture probabilistic participation and power distribution, leading to the formulation of the Consistency Rate and the Decentralization Coefficient as quantitative indicators. For efficiency, the model is further extended to characterize the interactions among participation probability, voting duration, and approval rate, enabling a formal evaluation of voting responsiveness and resource usage. Simulation results support both aspects of the analysis, revealing how power concentration, turnout behaviour, and mechanism design jointly influence decentralization and efficiency in DAO voting. The third part presents a unifying conceptual framework to analyse consensus across human, machine, and human-machine hybrid systems. Despite disciplinary differences, the thesis identifies three core components of any consensus process: participants (the actors of agreement), communication (the medium of exchange), and state (the evolving representation of agreement). Framing consensus as an entropy-reduction process that resolves cognitive or informational divergence, this abstraction enables comparative analysis across diverse systems. The framework also distinguishes among human consensus, machine consensus, and human-machine hybrid consensus, and offers design guidelines aligned with the characteristics and limitations of each. Together, these three threads construct a comprehensive theory of consensus that connects distributed computation, social governance, and emerging hybrid collectives. By integrating modelling, evaluation, and abstraction, this thesis contributes a multi-layered foundation for understanding and designing consensus mechanisms that are robust, scalable, and trustworthy in increasingly decentralized and intelligent environments.

Hora, Harneesh Singh, Sahani, Rahul, Suthar, Aryan, Rizwan Khan, Sahil

<i>We present a decentralized NFT (Non-Fungible Token) marketplace built on the Ethereum blockchain. The platform allows users to mint, buy, and sell unique digital assets (e.g., art, collectibles) using Solidity smart contracts and a Web3-enabled frontend. All ownership records are stored on-chain for transparency and immutability, while large media data (images, metadata) are stored off-chain using IPFS. Users connect their wallets (e.g., MetaMask) via a React interface using Ethers.js, enabling peer-to-peer transactions without intermediaries. Key features include real-time transaction updates via blockchain event listeners and gas-optimized contract design. Security is enforced through standard libraries and audit practices to prevent common exploits (e.g., reentrancy, overflow). Performance evaluations show reasonable gas costs per transaction, demonstrating feasibility on Ethereum’s current throughput. Future work includes expanding cross-chain support and enhanced scalability.</i>

Ashwin Kumar Karnad

Ensuring the reproducibility of scientific simulations is a persistent challenge, despite current best practices like version control and containerization. Factors such as floating-point arithmetic variations, hardware differences, and concurrency issues often prevent bit-for-bit replication of results. This paper investigates the techniques that distributed ledger technologies employ to achieve deterministic computations and application of these techniques to enhance the reproducibility, trustworthiness and verifiability of scientific simulations. We explore two primary approaches: executing simulations directly “on-chain” for complete transparency and deterministic replay, and performing computations “off-chain” while anchoring their integrity to a blockchain via cryptographic proofs, such as Zero-Knowledge Proofs (ZKPs) and Merkle trees.

Nicolò Romandini

In today's data-driven world, vast amounts of information power Machine Learning (ML) models for a wide range of applications. However, this data flow raises significant privacy concerns, as individuals are often reluctant to share personal information, especially given increasing regulations on data protection. Federated Learning (FL) offers a solution by training ML models directly on users' devices and sending only model updates to a central server. This distributed approach enables collaboration without sharing personal data, but challenges remain. Centralization may lead to server bottlenecks, reduced resilience, and fairness concerns if updates from certain devices are prioritized. Additionally, the lack of transparency and accountability can erode trust, while security risks, such as data poisoning and model inversion attacks, further complicate FL. Deployment can be costly and time-consuming, and participants may also lack incentives. Regulatory compliance, such as ensuring the right to be forgotten, adds complexity, as removing data from FL models without full retraining is challenging. This dissertation proposes integrating Distributed Ledger Technologies (DLTs) with FL to address these challenges. DLT decentralizes the aggregation process, enhancing security, transparency, and fairness through immutable record-keeping and traceability. Two DLT-based architectures are presented: one blockchain-based and the other using a Directed Acyclic Graph (DAG) for scalability. These approaches utilize Decentralized Identifiers (DIDs) and Verifiable Credentials (VCs) to track contributions and verify participants. Furthermore, a DLT-based FL as a Service (FLaaS) is introduced to simplify deployment, incorporating model validation to mitigate poisoning attacks and token-based incentives to encourage participation. Additionally, this dissertation outlines design guidelines for Federated Unlearning (FU), covering key evaluation metrics, existing techniques, and future research. Finally, a new unlearning algorithm is proposed to address adversarial settings and protect model integrity. These contributions pave the way for more secure, transparent, and resilient FL systems that can meet the needs of next-generation data-driven applications.

Hajer Rejeb, Alexandre Reiffers-Masson

No abstract is available for this record.

Abeer S. Al-Humaimeedy

No abstract is available for this record.

Syed Badruddoja, Sasi Kanduri, Ram Dantu

No abstract is available for this record.

Orestis Melkonian, Wouter Swierstra, James Chapman, Sub Software Technology · 6 authors

Distributed ledgers nowadays manage substantial monetary funds in the form of cryptocurrencies such as Bitcoin, Ethereum, and Cardano. For such ledgers to be safe, operations that add new entries must be cryptographically sound - but it is less clear how to reason effectively about such ever-growing linear data structures. This paper demonstrates how distributed ledgers may be viewed as computer programs, that, when executed, transfer funds between various parties. As a result, familiar program logics, such as Hoare logic, are applied in a novel setting. Borrowing ideas from concurrent separation logic, this enables modular reasoning principles over arbitrary fragments of any ledger. All of our results have been mechanised in the Agda proof assistant.

Xiaojie Feng

Proof of Stake (PoS), as an important consensus algorithm in blockchain technology, has received widespread attention and research in recent years. PoS aims to solve the problems of high energy consumption and low efficiency in Proof of Work (PoW) algorithms. By allowing validators to participate in the consensus process based on their economic interests, it achieves low energy consumption and high efficiency in block verification. This article examines the latest developments in five consensus algorithms for proof of stake, with the aim of identifying errors, omissions, and shortcomings in the original proof of stake. This article finds that although proof of stake has been widely used in the market, PoS algorithm still faces challenges such as how to further improve consensus efficiency, enhance system security, and effectively respond to malicious attacks. In order to address these challenges, this article presents some of its own opinions and proposes some summarized solutions and areas for improvement. This article aims to promote the continuous development of PoS algorithm through these perspectives, in order to adapt to more complex and diverse blockchain application scenarios.

Frederic von Normann, Mansur Aliyu, Niclas Kannengießer, Lan Bao Quang Le · 6 authors

Proof-of-stake-based (PoS-based) blockchain systems exhibit a trade-off between degree of decentralization (DoD) and scalability: equitable participation of validating nodes can raise latency and degrade throughput, while scaling can reduce equitable participation. To meet application requirements, software architects must balance these dimensions using comparable metrics. We curated a compact metric set for DoD (block-proposal randomness [Shannon entropy], token concentration [HHI], wealth distribution [Gini]) and for scalability (transaction throughput, first-inclusion latency) and applied it to Tezos Hangzhou 2 (Octez v12.3). Across 1,573 controlled configurations with varying validating-node count n, block interval, and block size limit, we normalized DoD by n to enable cross-configuration comparison. Under this normalization, DoDscalability associations were weaker and not uniformly negative. Scalability was primarily influenced by validating-node count. Our main contributions are a benchmarking approach with curated metrics, an empirical mapping of configuration levers to both dimensions, evidence for the dominant role of n, and guidance for configuring PoS-based blockchain systems.

Beth Probert, Ruaridh Clark, Erik Blasch, Malcolm Macdonald

As the density of objects in Low Earth Orbit continues to increase, greater levels of coordination among satellites are needed to ensure the continued operation and sustainability of the space environment. Existing centralised space governance frameworks suffer from delays, ambiguity, and vulnerability to manipulation, introducing further complexity and risk into satellite operations, and hindering the development of new space-based services. This review examines the feasibility of leveraging Distributed Ledger Technologies to facilitate secure, decentralised, and autonomous coordination among satellites, conceptualised as an extension of Internet of Things networks. By examining analogous applications in swarms of Uncrewed Aerial Systems, and the Internet of Things, key system requirements for decentralised satellite coordination are defined. It is found that traditional Blockchain systems using Proof of Work-based consensus mechanisms are impractical for use in space-based systems, whilst Directed Acyclic Graph architectures, Sharded Blockchain architectures, and non-deterministic Proof of Stake consensus mechanisms are the most suitable. Critical gaps preventing the implementation of Distributed Ledger Technologies in the space environment are identified. These include wider regulatory considerations, and technical obstacles relating to the storage of transactional data and reaching consensus in time-varying, asynchronous networks.

Saja Amen

The accelerating pace of adoption of decentralized applications requires the use of efficient, high-performance blockchain infrastructures. These blockchains are supported by consensus algorithms that are critical determinants of scalability, transaction speed, costs, and security. Developers are still unaware of the most useful options because there is a large gap in information regarding the comprehensive evaluation of these algorithms in practice. This study aims to test and compare the performance of the three most popularly used blockchain consensus protocols - Proof of Work (PoW), Proof of Stake (PoS) and Delegated Proof of Stake (DPoS) with the aim to improve the application of decentralized systems. By deploying smart contracts on real blockchain test networks (Callisto for PoW, Sepolia for PoS, and Tron Nile for DPoS), the research explores key performance metrics such as block time, deploy gas fee, block gas limit, and block size. The experiments utilize tools like Remix IDE and Tron-IDE, highlighting the practical implications of consensus algorithms under varying real-world conditions, including network congestion and transaction volatility. Tron Nile excels in speed and capacity but incurs high gas fees, Sepolia balances performance with moderate costs, and Callisto emphasizes cost efficiency at the expense of speed and scalability. Insights derived from this study provide valuable guidelines for developers to choose suitable consensus mechanisms based on the specific requirements of decentralized applications

Xu Liu, Junwu Zhu

Consensus algorithms play a critical role in maintaining the consistency of blockchain data, directly affecting the system's security and stability, and are used to determine the binary consensus of whether proposals are correct. With the development of blockchain-related technologies, social choice issues such as Bitcoin scaling and main chain forks, as well as the proliferation of decentralized autonomous organization (DAO) applications based on blockchain technology, require consensus algorithms to reach consensus on a specific proposal among multiple proposals based on node preferences, thereby addressing the multi-value consensus problem. However, existing consensus algorithms, including Practical Byzantine Fault Tolerance (PBFT), do not support nodes expressing preferences. Instead, the proposal to reach consensus is directly decided by specific nodes, with other nodes merely verifying the proposal's validity, which can easily result in monopolistic or dictatorial outcomes. In response, we proposed the Aggregating Preferences with Practical Byzantine Fault Tolerance (AP-PBFT) consensus algorithm, which allows nodes to express preferences for multiple proposals. AP-PBFT ensures the validity of consensus results through a consensus output protocol, and incentivizes nodes to act honestly during the consensus process by incentive mechanism. First, AP-PBFT leverages Verifiable Random Function to select both consensus nodes and a primary node from the candidates. The primary node gathers proposals, assembles them into a proposal package, and broadcasts it to other consensus nodes. The consensus nodes independently vote to express their preferences for different proposals in the package, execute the consensus output protocol to reach local consensus, and the primary node aggregates these results to form the global consensus. Once the global consensus is finalized, AP-PBFT evaluates node behavior based on the consensus output protocol, penalizes nodes that acted maliciously, and rewards those that adhered to the protocol. Additionally, nodes can interact and adopt different strategies while executing the consensus output protocol, which can influence the consensus outcome. Therefore, we established an evolutionary game model based on hypergraph to analyze these interactions. Theoretical analysis shows that the incentive mechanism in AP-PBFT effectively encourages nodes to honestly follow the consensus output protocol, ensuring that AP-PBFT satisfies the properties of consistency, validity, and termination. Finally, the simulation results demonstrate that the AP-PBFT algorithm possesses good scalability and the capability to handle dynamic changes in nodes, surpassing some mainstream consensus algorithms in terms of transaction throughput and consensus achievement time. Moreover, AP-PBFT can incentivize honest behavior among consensus nodes, thereby enhancing the reliability of consensus and strengthening the security of the network.