Abstract This paper provides an overview of the distributed ledger technology (DLT) options available to central banks for issuing central bank digital currency (CBDC). We discuss the main requirements that a DLT solution must fulfill and analyze the various structures for implementation offered by DLT — public, permissioned and private — and the implications that each has for the central bank and the existing financial system. While a CBDC built on an open, permissionless system would provide the full functionality offered by DLT, it is also far more disruptive to the existing financial system and consequently requires more new infrastructure on the part of the central bank.
Hamra Afzaal, Nazir Ahmad Zafar, Aqsa Tehseen, Shaheen Kousar · 5 authors
In recent years, Beacon Chain known as the core of Ethereum 2.0, has gained considerable attention since its launch. Many validators have staked billions of Ether in the Proof of Stake (PoS) network. It is a mission critical system and its security and stability rely on the justification and finalization of checkpoints. These are essential elements of the Casper FFG consensus algorithm utilized by the Beacon Chain. This process is critical for establishing a trustworthy foundation and finalizing proposed blocks by confirming agreed upon checkpoints. Hence, ensuring the correctness of checkpoints in the Beacon Chain has significant importance because any bug in it can cause serious implications. To address this challenge, we employ formal methods, a popular mathematical approach used for verifying the correctness of such critical systems. In this work, we have done formal verification of the processes of Beacon Chain state initialization, justification and finalization of checkpoints using the Process Analysis Toolkit (PAT) model checker. The adoption of model checking through the PAT model checker presents a novel contribution of our work, as this approach is not previously utilized in the formal verification of Beacon Chain. The presented work is specified through the Communicating Sequential Programs, formal specification language, and the properties are described through Linear Temporal Logic. The PAT model checker takes the specified formal model and properties as input to assess whether the properties are satisfied. The properties are analyzed with respect to the verification time, visited states, total transitions, and memory used. Through this research, we aim to increase confidence in the correctness and reliability of the Beacon Chain.
As blockchains shift from energy-hungry Proof-of-Work to capital-intensive Proof-of-Stake, they trade electricity costs for a new vulnerability: the risk of a capital run that can destabilize consensus and security. We model investors who choose between staking their coin to earn rewards or exiting to cash out, potentially triggering mass withdrawals. These "staking runs" are more likely when protocols are weak, when failure would hit coin prices hard, or when staking rewards are low. Leverage worsens things: margin calls accelerate exits and amplify run dynamics. Longer lock-up periods slow the run but may not prevent it. Previous research shows that low rewards are good for protocol security. We show they also raise the risk of a run. A run on a major Proof-of-Stake chain---like Ethereum---could destabilize the entire crypto ecosystem, threatening DeFi platforms that depend on it.
Ethereum is undergoing significant changes to its architecture as it evolves. These changes include its switch to PoS consensus and the introduction of significant infrastructural changes that do not require a change to the core protocol, but that fundamentally affect the way users interact with the network. These changes represent an evolution toward a more modular architecture, in which there exists new exogenous vectors for centralization. This paper builds on previous studies of decentralization of Ethereum to reflect these recent significant changes, and Ethereum's new modular paradigm.
Decentralized finance revolutionizes traditional financial systems by leveraging blockchain technology to reduce trust. However, some vulnerabilities persist, notably front-running by malicious actors who exploit transaction information to gain financial advantage. Consensus with a fair order aims at preventing such attacks, and in particular, the differential order fairness property addresses this problem and connects fair ordering to the validity of consensus. The notion is implemented by the Quick Order-Fair Atomic Broadcast (QOF) protocol (Cachin et al., FC ‘22). This paper revisits the QOF protocol and describes a modular implementation that uses a generic consensus component. Moreover, an empirical evaluation is performed to compare the performance of QOF to a consensus protocol without fairness. Measurements show that the increased complexity comes at a cost, throughput decreases by at most 5%, and latency increases by roughly 50 ms, using an emulated ideal network. This paper contributes to a comprehensive understanding of practical aspects regarding differential order fairness with the QOF protocol and also connects this with similar fairness-imposing protocols like Themis and Pompē.
Ethereum has emerged as a leading platform for decentralized applications (dApps) due to its robust smart contract capabilities. One of the critical issues in the Ethereum ecosystem is Maximal Extractable Value (MEV), a concept that has gained significant attention in the blockchain community. However, MEV has remained a major challenge with significant implications for the platform's operation and integrity. This paper introduces the FairFlow protocol, a novel framework designed to mitigate the effects of MEV within Ethereum's existing infrastructure. The protocol aims to provide a more equitable environment, preventing exploitation by miners or validators, and protecting user data. The combined approach of auction-based block space allocation and randomized transaction ordering significantly reduces the potential for MEV exploitation.
The core of a blockchain network is its consensus algorithm. Starting with the Proof-of-Work, there have been various versions of consensus algorithms, such as Proof-of-Stake (PoS), Proof-of-Authority (PoA), and Practical Byzantine Fault Tolerance (PBFT). Each of these algorithms focuses on different aspects to ensure efficient and reliable processing of transactions. Blockchain operates in a decentralized manner where there is no central authority and the network is composed of diverse users. This openness creates the potential for malicious nodes to disrupt the network in various ways. Therefore, it is crucial to embed a mechanism within the blockchain network to constantly monitor, identify, and eliminate these malicious nodes. However, there is no one-size-fits-all mechanism to identify all malicious nodes. Hence, the dynamic adaptability of the blockchain network is important to maintain security and reliability at all times. This paper introduces MRL-PoS, a Proof-of-Stake consensus algorithm based on multi-agent reinforcement learning. MRL-PoS employs reinforcement learning for dynamically adjusting to the behavior of all users. It incorporates a system of rewards and penalties to eliminate malicious nodes and incentivize honest ones. Additionally, MRL-PoS has the capability to learn and respond to new malicious tactics by continually training its agents.
Since the introduction of the first cryptocurrency, Bitcoin, in 2008, the gain in popularity of distributed ledger technologies (DLTs) has led to an increasing demand and, consequently, a larger number of network participants in general. Scaling blockchain-based solutions to cope with several thousand transactions per second or with a growing number of nodes has always been a desirable goal for most developers. Enabling these performance metrics can lead to further acceptance of DLTs and even faster systems in general. With the introduction of directed acyclic graphs (DAGs) as the underlying data structure to store the transactions within the distributed ledger, major performance gains have been achieved. In this article, we review the most prominent directed acyclic graph platforms and evaluate their key performance indicators in terms of transaction throughput and network latency. The evaluation aims to show whether the theoretically improved scalability of DAGs also applies in practice. For this, we set up multiple test networks for each DAG and blockchain framework and conducted broad performance measurements to have a mutual basis for comparison between the different solutions. Using the transactions per second numbers of each technology, we created a side-by-side evaluation that allows for a direct scalability estimation of the systems. Our findings support the fact that, due to their internal, more parallelly oriented data structure, DAG-based solutions offer significantly higher transaction throughput in comparison to blockchain-based platforms. Although, due to their relatively early maturity state, fully DAG-based platforms need to further evolve in their feature set to reach the same level of programmability and spread as modern blockchain platforms. With our findings at hand, developers of modern digital storage systems are able to reasonably determine whether to use a DAG-based distributed ledger technology solution in their production environment, i.e., replacing a database system with a DAG platform. Furthermore, we provide two real-world application scenarios, one being smart grid communication and the other originating from trusted supply chain management, that benefit from the introduction of DAG-based technologies.
Operators of low-Earth-orbit (LEO) non-geostationary satellite networks, also known as mega-constellations, are required by current regulations to share all available satellite spectrum. This paper proposes a consensus mechanism to facilitate spectrum sharing with accountability by multiple operators, a subset of which may even be adversarial. A distributed ledger is used to securely record and track the state of consensus on spectrum usage, including interference incidents and the corresponding responsible parties. A key challenge is that operators generally do not have initial agreement due to noise in their analog measurements. To address this, two categories of spectrum-sharing solutions are studied in detail. The first category employs an exact Byzantine fault tolerant (BFT) agreement model; the second category utilizes an approximate BFT agreement model. Practical considerations were taken into account regarding the BFT agreements, substantiated by numerical findings on the feasibility of the proposed solutions within the context of non-geostationary orbit satellite networks (NGSO).
A system of zero-knowledge proofs on graph signatures has been proposed, where a graph can be signed, and the owner of the graph signature can prove a graph relation such as the connectivity and isolation of any two vertexes on the graph without disclosing all information about the graph. The correctness of the graph information is guaranteed by the signature. One of the applications is a virtualized infrastructure, where an infrastructure provider manages a distributed system, and each tenant is allocated a specific portion of this infrastructure for use. Tenants need to check with the provider that their resources are properly connected (connectivity) and that their resources are properly separated from the resources of other tenants (isolation). On the other hand, the provider cannot simply disclose the entire infrastructure topology to each tenant. Using the zero-knowledge proof system on graph signatures, both requirements can be addressed. Previously, an efficient zero-knowledge proof system on graph signatures using a bilinear-map accumulator has been proposed, where the verification time and the size of the proof data do not depend on the number of graph vertexes and edges. However, this system has two problems. First, since the proof does not include labels, it is not possible to prove the connectivity considering network bandwidth and cost. Second, since it assumes undirected graphs, it cannot handle applications on directed graphs such as network flows. In this paper, we extend the previous system and propose a zero-knowledge proof system of the connectivity for directed graphs where each edge has labels. We implemented our system on a PC using a pairing library and evaluate it by measuring the processing times. Compared to the conference version of this paper, we show the formal definitions and the security proofs of our proposed system, and add implementation-based evaluations reflecting the application to the virtualized infrastructure.
Davide Frey, Lucie Guillou, Michel Raynal, François Taı̈ani
This paper explores the territory that lies between best-effort Byzantine-Fault-Tolerant Conflict-free Replicated Data Types (BFT CRDTs) and totally ordered distributed ledgers, such as those implemented by Blockchains. It formally characterizes a novel class of distributed objects that only requires a First In First Out (FIFO) order on the object operations from each process (taken individually). The formalization leverages Mazurkiewicz traces to define legal sequences of operations and ensure both Strong Eventual Consistency (SEC) and Pipleline Consistency (PC). The paper presents a generic algorithm that implements this novel class of distributed objects both in a crash- and Byzantine setting. It also illustrates the practical interest of the proposed approach using four instances of this class of objects, namely money transfer, Petri nets, multi-sets, and concurrent work stealing dequeues.
Blockchains add transactions to a distributed shared ledger by arriving at consensus on sets of transactions contained in blocks. This provides a total ordering on a set of global transactions. However, total ordering is not enough to satisfy application semantics under the Byzantine fault model. This is due to the fact that malicious miners and clients can collaborate to add their own transactions ahead of correct clients' transactions in order to gain application level and financial advantages. These attacks fall under the umbrella of front-running attacks. Therefore, total ordering is not strong enough to preserve application semantics. In this paper, we propose causality preserving total order as a solution to this problem. The resulting Blockchains will be stronger than traditional consensus based blockchains and will provide enhanced security ensuring correct application semantics in a Byzantine setting.
The Algorand consensus protocol is interesting both in theory and in practice. On the theoretical side, to achieve adaptive security, it introduces the novel idea of player replaceability, where each step of the protocol is executed by a different randomly selected committee whose members remain secret until they send their first and only message. The protocol provides consistency under arbitrary network conditions and liveness under intermittent network partitions. On the practical side, the protocol is used to secure the Algorand cryptocurrency, whose total value is approximately 850M at the time of writing.
Resilience is vital to blockchain systems and helps them automatically adapt and continue providing their service when adverse situations occur, e.g., node crashing and data discarding. However, due to the vulnerabilities in their implementation, blockchain systems may fail to recover from the error situations, resulting in permanent service disruptions. Such vulnerabilities are called resilience issues.
We study the problem of committee selection in the context of proof-of-stake consensus mechanisms or distributed ledgers. These settings determine a family of participating parties---each of which has been assigned a non-negative ''stake''---and are subject to an adversary that may corrupt a subset of the parties. The challenge is to select a committee of participants that accurately reflects the proportion of corrupt and honest parties, as measured by stake, in the full population. The trade-off between committee size and the probability of selecting a committee that over-represents the corrupt parties is a fundamental factor in both security and efficiency of proof-of-stake consensus, as well as committee-run layer-two protocols.
Miguel Oliveira, Sumit Chauhan, Filipe Pereira, Carlos Felgueiras · 5 authors
"Industry 5.0" is the latest industrial revolution. A variety of cutting-edge technologies, including artificial intelligence, the Internet of Things (IoT), and others, come together to form it. Billions of devices are connected for high-speed data transfer, especially in a 5G-enabled industrial environment for information collection and processing. Most of the issues, such as access control mechanism, time to fetch the data from different devices, and protocols used, may not be applicable in the future as these protocols are based upon a centralized mechanism. This centralized mechanism may have a single point of failure along with the computational overhead. Thus, there is a need for an efficient decentralized access control mechanism for device-to-device (D2D) communication in various industrial sectors, for example, sensors in different regions may collect and process the data for making intelligent decisions. In such an environment, reliability, security, and privacy are major concerns as most of the solutions are based upon a centralized control mechanism. To mitigate the aforementioned issues, this paper provides the opportunities for and highlights some of the most impressive initiatives that help to curve the future. This new era will bring about significant changes in the way businesses operate, allowing them to become more cost-effective, more efficient, and produce higher-quality goods and services. As sensors are getting more accurate, cheaper, and have lower time responses, 5G networks are being integrated, and more industrial equipment and machinery are becoming available; hence, various sectors, including the manufacturing sector, are going through a significant period of transition right now. Additionally, the emergence of the cloud enables modern production models that use the cloud (both internal and external services), networks, and systems to leverage the cloud's low cost, scalability, increased computational power, real-time communication, and data transfer capabilities to create much smarter and more autonomous systems. We discuss the ways in which decentralized networks that make use of protocols help to achieve decentralization and how network meshes can grow to make things more secure, reliable, and cohere with these technologies, which are not going away anytime soon. We emphasize the significance of new design in regard to cybersecurity, data integrity, and storage by using straightforward examples that have the potential to lead to the excellence of distributed systems. This groundbreaking paper delves deep into the world of industrial automation and explores the possibilities to adopt blockchain for developing solutions for smart cities, smart homes, healthcare, smart agriculture, autonomous vehicles, and supply chain management within Industry 5.0. With an in-depth examination of various consensus mechanisms, readers gain a comprehensive understanding of the latest developments in this field. The paper also explores the current issues and challenges associated with blockchain adaptation for industrial automation and provides a thorough comparison of the available consensus, enabling end customers to select the most suitable one based on its unique advantages. Case studies highlight how to enable the adoption of blockchain in Industry 5.0 solutions effectively and efficiently, offering valuable insights into the potential challenges that lie ahead, particularly for smart industrial applications.
IOTA 2.0 addresses the dual challenge of dynamic availability and definite finality in distributed ledgers. By combining voting-based and proof-based consensus models, it allows users to strike a balance between these objectives. This innovative approach represents a significant advancement in the field, offering both dynamic availability and definite finality, all within the evolving landscape of distributed ledger technologies.
Huizhong Li, Yujie Chen, Shi Xiang, Xingqiang Bai · 9 authors
Enterprise-grade permissioned blockchain systems provide a promising infrastructure for data sharing and cooperation between different companies. However, performance bottlenecks seriously hinder the adoption of these systems in many industrial applications that process complex business logic and huge transaction volumes. Our research identifies two key factors that limit the system performance: 1) At the block level, the serial dependency of inter-block processing severely limits the system throughput. A new block must wait for the completion of all previous blocks. 2) At the transaction level, the lack of efficient intra-block transactions concurrency makes it difficult to achieve high performance, especially when dealing with multiple CPU-heavy contracts which are commonly used in industrial scenarios.
Abstract Distributed ledgers, including blockchain and other decentralized databases, are designed to store information online where all trusted network members can update the data with transparency. The dynamics of a ledger’s development can be mathematically represented by a directed acyclic graph (DAG). In this paper, we study a DAG model that considers batch arrivals and random delay of attachment. We analyze the asymptotic behavior of this model by letting the arrival rate go to infinity and the inter-arrival time go to zero. We establish that the number of leaves in the DAG, as well as various random variables characterizing the vertices in the DAG, can be approximated by its fluid limit, represented as the solution to a set of delayed partial differential equations. Furthermore, we establish the stable state of this fluid limit and validate our findings through simulations.
Conor Flynn, Kristin P. Bennett, John Erickson, Aaron Green · 5 authors
With the agile development process of most academic and corporate entities, designing a robust computational back-end system that can support their ever-changing data needs is a constantly evolving challenge. We propose the implementation of a data and language-agnostic system design that handles different data schemes and sources while subsequently providing researchers and developers a way to connect to it that is supported by a vast majority of programming languages. To validate the efficacy of a system with this proposed architecture, we integrate various data sources throughout the decentralized finance (DeFi) space, specifically from DeFi lending protocols, retrieving tens of millions of data points to perform analytics through this system. We then access and process the retrieved data through several different programming languages (R-Lang, Python, and Java). Finally, we analyze the performance of the proposed architecture in relation to other high-performance systems and explore how this system performs under a high computational load.
Engin Zeydan, Luis Blanco, Josep Mangues, Şuayb S. Arslan · 5 authors
Self-Sovereign Identity (SSI) has recently emerged as an identity and access management framework based on Distributed Ledger Technology (DLT) that enables users or organizations to control their own data. The Open RAN (O-RAN), on the other hand, provides a framework for sharing infrastructure-related data between users and mobile network operators (MNOs). By leveraging SSI, O-RAN can benefit from decentralized and secure identity management that enables a more transparent, efficient, and user-centric network ecosystem. This paper examines identity, inventory and configuration management, and authentication of users or MNOs for a resource sharing scenario in an O-RAN architecture. At the end of the paper, we explain the potential limitations and possible solutions for applying SSI to improve security, privacy, trust, and interoperability in O-RANs.
In the rapidly evolving domain of distributed ledger technology, scalability and interoperability have become paramount challenges for both academic and industry sectors. In this paper, we introduce a comprehensive formal model to address atomic composability across multiple rollups on Ethereum. The proposed model incorporates mechanisms like buffering, dependency management, concurrency control, and the groundbreaking zero-knowledge proofs. Moreover, we evaluate its practical repercussions, strengths, and weaknesses, ensuring resilience against manipulative or erroneous actions. The application of the proposed model to shared sequencers and other existing solutions accentuates its versatility and universality.