Byzantine Fault-Tolerant (BFT) protocols enable distributed ledgers to operate without a single trusted party, tolerating up to a threshold of Byzantine faults. While traditional BFT was designed for closed systems with few participants, blockchain applications are open systems with thousands of internet-connected participants. This transition introduces two critical vulnerabilities unaddressed by classical BFT: (1) nodes' susceptibility to internet Denial-of-Service (DoS) attacks, and (2) potential correlated failures when participants use similar configurations, violating the fault independence assumption. This thesis addresses these vulnerabilities through three contributions. First, it introduces the Mobile Crash Adaptive Byzantine (MCAB) adversary model, capturing mobile DoS attacks. Protocols are proven to require either concealment (hiding node identities until after broadcasting) or abundance (having more nodes per role than the adversary can target) to maintain liveness under MCAB. Second, it expands modern Directed Acyclic Graph (DAG) based BFT for system models captured by MCAB. The first constant latency dynamically available DAG-based BFT protocol is proposed. A novel primitive, Graded Common Prefix (GCP), enables nodes to agree on a common DAG subset without standard consensus. Combining these yields a flexible protocol allowing clients to choose between prioritizing liveness or safety while benefiting from modern DAG BFT's high performance. Third, the thesis addresses fault independence through incentive mechanisms encouraging diverse node configurations. Since costs related to various configurationsāfrom software implementation to geo-locationāare hard to quantify, control mechanisms from reinforcement learning and control theory are leveraged, as they function without requiring analytical solutions to the underlying system.
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 āon-chainā for complete transparency and deterministic replay, and performing computations āoff-chainā while anchoring their integrity to a blockchain via cryptographic proofs, such as Zero-Knowledge Proofs (ZKPs) and Merkle trees.
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.
Orestis Melkonian, Wouter Swierstra, James Chapman, Sub Software Technology Ā· 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.
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 KannengieĆer, Lan Bao Quang Le Ā· 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.
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
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.
Christian DelgadoāvonāEitzen, Luis Anido, MarĆa RuizāMolina, Manuel J. FernĆ”ndez Iglesias
ABSTRACT Introduction The popularization of blockchainābased applications made evident a critical challenge, namely the inherent isolation of these decentralized systems, akin to the disconnected and technologically diverse local area networks of the 1970s. This lack of interoperability limits the potential for widespread adoption and innovation in the blockchain space. While various initiatives aim to bridge this gap, many remain nascent. Methods This article addresses this issue by proposing a robust architecture and practical implementation to interconnect two Ethereumābased blockchains, enabling seamless smart contract interactions across these chains, and facilitating the exchange of complex information beyond mere token transfers. Results Our work explores the emerging landscape of interāblockchain communication, highlighting their current maturity and potential, and providing insights on how to overcome the technical hurdles associated with these protocols, particularly in the context of transmitting complex data and executing crossāchain function calls. Additionally, we illustrate with a case study the challenges posed by linking private blockchains with public ones, ensuring secure and efficient data exchange. Conclusion This article aims to inspire blockchain researchers and practitioners, presenting a foundational framework for enhancing blockchain interoperability, including detailed, practical steps for its implementation. By laying the groundwork for more connected blockchain ecosystems, we intend to support the continued evolution and widespread adoption of blockchain technology.
Consensus is one of the key components of Blockchain. Common public blockchains use Proof-Of-Work or Proof-Of-Stake as their consensus protocols. In contrast, private or consortium blockchains often use Raft, which is only crash fault tolerant. It means that strong trust on node holders in private or consortium blockchains is required. To relax the strong trust requirement, we propose by taking raft as foundation and modification on raft and leveraging threshold signature and trusted execution environment to improve security. We have implemented and integrated our proposed consensus algorithm with ConsenSys Quorum. Our experiment shows that our work has slight performance degradation on blockchain compared to original Raft.
Hamra Afzaal, Nazir Ahmad Zafar, Aqsa Tehseen, Shaheen Kousar
Ethereum 2.0 Beacon Chain has adopted the Proof of Stake (PoS) consensus mechanism to significantly advance the security, scalability, and decentralization of blockchain technology. It has played an integral role in organizing validator operations and addressing scalability issues. The Beacon Chainās rewards and penalty system incentivizes honest behavior and penalizes dishonest actors inside the network. Ensuring the correctness of this mechanism is paramount for guaranteeing the systemās integrity. Therefore, this work formally verifies the rewards and penalty mechanism in the Beacon Chain using model checking, a formal methods-based technique. The formal specification of the rewards and penalties processes and several other epoch operations are described using the Communicating Sequential Programs (CSP#) language. The properties for rewards and penalties procedures are specified with Linear Temporal Logic (LTL). The Process Analysis Toolkit (PAT) model checker is utilized for verifying the formal model against the properties. The PAT model checker takes the specified formal model as input and determines whether the properties are satisfied or violated. The properties are examined in terms of verification time, visited states, total transitions, and memory utilization.
In this paper, we provide an overview of a specific, but rather popular type of blockchain scaling solutions, which are usually referred to as Layer 2 blockchains.These solutions depend on the rollup scaling strategy.First, they all create batches of transactions known as rollups.Second, there are two primary approaches to rollup verifications.One approach is referred to as optimistic rollup, where it is assumed that fraudulent transactions rarely occur and should it happen, then some nodes could raise a challenge, which would lead to the resolution of the problem.The interaction between the asserter and the challenger is referred to as interactive fraud proof.The other approach is a conservative approach, where every rollup batch is associated with a validity proof.For all practical purposes, Ethereum is used as the Layer 1 blockchain because it is the first and only large-scale public blockchain that supports Turing-complete smart contracts.These Layer 2 blockchains typically deploy at least two smart contracts on the Layer 1 blockchain, one to receive rollups from the Layer 2 blockchain, and the other to verify the rollup batch.Furthermore, we provide technical details of two Layer 2 blockchains (i.e., Arbitrum and Optimism) that use the optimistic rollup mechanism, and two Layer 2 blockchains (i.e., Polygon and Starknet) that use validity rollup mechanism.Finally, we analyze the Layer 2 blockchain solutions in the framework of the blockchain trilemma theory.We show that all Layer 2 scaling solutions trade decentralization for better scalability.