Verifiable Delay Functions (VDFs) introduced by Boneh et al. (CRYPTO'18) are functions that require a prescribed number of sequential steps T to evaluate, yet their output can be verified in time much faster than T. Since their introduction, VDFs have gained a lot of attention due to their applications in blockchain protocols, randomness beacons, timestamping and deniability. This thesis explores the theory and applications of VDFs, focusing on enhancing their soundness, efficiency and practicality. The only practical VDFs known to date are based on repeated squaring in hidden order groups. Consider the function VDF(x,T)=x^(2^T). The iterated squaring assumption states that, for a random group element x, the result of VDF cannot be computed significantly faster than performing T sequential squarings if the group order is unknown. To make the result verifiable a prover can compute a proof of exponentiation (PoE) \pi. Given \pi, the output of VDF can be verified in time much less than T. We first present new constructions of statistically sound proofs of exponentiation, which are an important building block in the construction of SNARKs (Succinct Non-Interactive Argument of Knowledge). Statistical soundness means that the proofs remain secure against computationally unbounded adversaries, in particular, it remains secure even when the group order is known. We thereby address limitations in previous PoE protocols which either required (non-standard) hardness assumptions or a lot of parallel repetitions. Our construction significantly reduces the proof size of statistically sound PoEs that allow for a structured exponent, which leads to better efficiency of SNARKs and other applications. Secondly, we introduce improved batching techniques for PoEs, which allow multiple proofs to be aggregated and verified with minimal overhead. These protocols optimize communication and computation complexity in large-scale blockchain environments and enable scalable remote benchmarking of parallel computation resources. We then construct VDFs with enhanced properties such as zero-knowledge and watermarkability. It was shown by Arun, Bonneau and Clark (ASIACRYPT'22) that these features enable new cryptographic primitives called short-lived proofs and signatures. The validity of such proofs and signatures expires after a predefined amount of time T, i.e., they are deniable after time T. Our constructions improve upon the constructions by Arun, Bonneau and Clark in several dimensions (faster forging times, arguably weaker assumptions). Finally, we apply PoEs in the realm of primality testing, providing cryptographically sound proofs of non-primality for large Proth numbers. This work gives a surprising application of VDFs in the area of computational number theory. Together, our contributions advance both the theoretical foundations and the real-world usability of VDFs in general and in particular of PoEs, making them more adaptable and secure for current and emerging cryptographic applications.
The increasing number of blockchain projects introduced annually has led to a pressing need for secure and efficient interoperability solutions. Currently, the lack of such solutions forces end-users to rely on centralized intermediaries, contradicting the core principle of decentralization and trust minimization in blockchain technology. We propose a decentralized and efficient interoperability solution (aka Bridge Protocol) that operates without additional trust assumptions, relying solely on the Byzantine Fault Tolerance (BFT) properties of the two chains being connected. In particular, relayers (actors that exchange messages between networks) are permissionless and decentralized, hence eliminating any single point of failure. We introduce Random Sampling, a novel technique for on-chain light clients to efficiently follow the history of PoS blockchains by reducing the signature verifications required. Here, the randomness is drawn on-chain, for example, using Ethereum’s RANDAO. We analyze the security of the bridge from a crypto- economic perspective and provide a framework to derive the security parameters. This includes handling subtle concurrency issues and randomness bias in strawman designs. While the protocol is applicable to various PoS chains, we demonstrate the protocol’s practical feasibility by showcasing an instantiated bridge between Polkadot and Ethereum (currently deployed), and discuss some practical security challenges. Furthermore, we evaluate the efficiency of our on-chain light client verifier (implemented as an Ethereum smart contract) against SNARK-based approaches, demonstrating significantly lower gas costs for signature verification - even for validator sets up to 10⁶.
This thesis presents novel techniques to improve the efficiency, scalability, and security of Data Confidence Fabrics (DCFs), a framework that ensures data authenticity and integrity in large scale, heterogeneous distributed systems by generating metadata at each point of data formation, processing, and transmission. Despite their strengths, DCFs face significant challenges, including excessive annotation and transactional overhead, which reduce scalability and efficiency, and metadata privacy risks, which compromise sensitive network information. To address these challenges, this research proposes methods that improve system scalability, enable efficient annotation retrieval, and protect sensitive network information, with a focus on the Alvarium Data Confidence Fabric, though the solutions are broadly applicable to other DCFs. A primary contribution of this work is addressing the efficiency and scalability challenges by reducing annotation overhead through compact annotation techniques, particularly annotation batching. By aggregating multiple annotations into a single ledger transaction, this approach minimizes redundancy, storage costs and ledger interactions. However, batching introduces complexity in retrieving individual annotations. To overcome this, two retrieval methods are proposed: Batch Keys, which use mapping tables to quickly locate individual annotations based on a Batch key, and Bloom Filters, which provide a low-overhead approach for efficiently verifying the presence of annotations. Another major focus of this work is mitigating metadata privacy risks, where adversaries could analyze annotations to infer network structures. To obscure network patterns, two privacy-preserving schemes, Hostname Mapping and Hostname Encryption, are introduced, with Hostname Encryption offering a more efficient and secure alternative. Additionally, the research highlights how timestamp metadata can be exploited to reconstruct network structures through clustering techniques. To mitigate this vulnerability, a timestamp obfuscation solution is proposed, introducing controlled randomness to disrupt predictable timing patterns and protect network confidentiality. In summary, the thesis introduces and evaluates methods that significantly enhance the efficiency, scalability, and security of DCFs. These contributions strengthen the practical deployment of DCFs in cloud-edge environments and provide a foundation for future research in secure and trustworthy data management across distributed systems.
The development of smart contracts in blockchain networks has enabled the creation of sophisticated decentralized finance (DeFi) protocols, encompassing decentralized exchanges, lending platforms, and algorithmic crypto-assets. Despite decentralization and transparency, blockchain networks do not guarantee a predictable transaction execution order, leading to the emergence of the phenomenon known as Maximal Extractable Value (MEV) – an additional profit extracted by certain network participants who influence transaction ordering. This study focuses on the empirical analysis of MEV extraction across various DeFi protocols to identify critical factors influencing the frequency and extent of MEV attacks. The research introduces a comparative methodology for evaluating MEV extraction based on a modified version of the MEV Inspect Py software suite, enhanced by newly developed components: a Price Resolver for collecting and correcting cryptocurrency price data, and a Jupyter Notebook module for detailed data analysis, comparison and visualization. An evaluation of the total volume of sandwich and arbitrage-type MEV attacks was also developed, and a method for correcting cryptocurrency price data was implemented, which improved the quality of the obtained results. The obtained results demonstrate that Uniswap V2 and Uniswap V3 are the primary targets for MEV extraction; however, their operational mechanisms create distinct conditions for attacks. A clear correlation was identified between concentrated liquidity, pricing algorithms, and the scale of MEV exploitation. Furthermore, the findings confirm that the architectural features of DeFi protocols significantly affect their vulnerability to MEV. These results can be employed to enhance the resilience of decentralized exchange algorithms against MEV extraction and to develop mechanisms that minimize its negative impacts on both protocol efficiency and user fairness. Moreover, the insights from this research provide valuable guidance to DeFi protocol users seeking to reduce their exposure to MEV- related risks and make more informed decisions. Future research directions include extending the analysis to MEV exploitation in blockchain networks other than Ethereum and evaluating the effectiveness of existing and emerging protective strategies.
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.
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.
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.
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.
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.
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
Blockchain networks face escalating security challenges, including quantum computing threats, Sybil attacks, and scalability bottlenecks. Existing consensus mechanisms like Proof-of-Work (PoW) and Proof-of-Stake (PoS) lack adaptive security features and quantum resistance. This paper introduces the Quantum-Resistant Hierarchical Consensus Protocol (QRHCP), a novel hybrid framework combining Hierarchical Byzantine Fault Tolerance (HBFT), lattice-based post-quantum signatures, dynamic sharding, and a deception-based Sybil resistance mechanism. QRHCP organizes nodes in a multi-layered validation hierarchy, where root validators finalize blocks while edge validators process lightweight transactions. To counter quantum threats, we integrate CRYSTALS-Dilithium signatures in a dual-signature scheme, ensuring backward compatibility while transitioning to quantum-safe cryptography. Additionally, Adaptive Dynamic Sharding (ADS) optimizes network performance by dynamically splitting or merging shards based on real-time threat analysis. We evaluate QRHCP against Byzantine attack resistance, quantum vulnerability, and transaction throughput using a custom blockchain simulator. Results show 40% faster consensus latency compared to PBFT, 99.9% Sybil attack detection via the Decoy Chain Mechanism (DCM), and scalability up to 10,000 TPS under adaptive sharding. Our work provides a provably secure, quantum-resistant, and highly scalable consensus model for next-generation blockchain applications.
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.
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>