Jossekin Beilharz, Bjarne Pfitzner, Robert Schmid, Paul Geppert · 6 authors
Federated learning allows a group of distributed clients to train a common machine learning model on private data. The exchange of model updates is managed either by a central entity or in a decentralized way, e.g. by a blockchain. However, the strong generalization across all clients makes these approaches unsuited for non-independent and identically distributed (non-IID) data. We propose a unified approach to decentralization and personalization in federated learning that is based on a directed acyclic graph (DAG) of model updates. Instead of training a single global model, clients specialize on their local data while using the model updates from other clients dependent on the similarity of their respective data. This specialization implicitly emerges from the DAG-based communication and selection of model updates. Thus, we enable the evolution of specialized models, which focus on a subset of the data and therefore cover non-IID data better than federated learning in a centralized or blockchain-based setup. To the best of our knowledge, the proposed solution is the first to unite personalization and poisoning robustness in fully decentralized federated learning. Our evaluation shows that the specialization of models emerges directly from the DAG-based communication of model updates on three different datasets. Furthermore, we show stable model accuracy and less variance across clients when compared to federated averaging.
Many researchers have proposed replacing the aggregation server in federated learning with a blockchain system to improve privacy, robustness, and scalability. In this approach, clients would upload their updated models to the blockchain ledger and use a smart contract to perform model averaging. However, the significant delay and limited computational capabilities of blockchain systems make it inefficient to support machine learning applications on the blockchain. In this paper, we propose a new public blockchain architecture called DFL, which is specially optimized for distributed federated machine learning. Our architecture inherits the merits of traditional blockchain systems while achieving low latency and low resource consumption by waiving global consensus. To evaluate the performance and robustness of our architecture, we implemented a prototype and tested it on a physical four-node network, and also developed a simulator to simulate larger networks and more complex situations. Our experiments show that the DFL architecture can reach over 90\% accuracy for non-I.I.D. datasets, even in the presence of model poisoning attacks, while ensuring that the blockchain part consumes less than 5\% of hardware resources.
In this paper, we address the digitization of physical assets using blockchain technology focusing on energy and peer-to-peer trading on decentralized energy markets. Because they are forward markets and operate on a day-ahead timeline, the energy transactions are settled only at the movement of energy delivery. Having the option of locking the energy tokens by a third-party escrow becomes a highly desirable feature. Thus, we define a Lockable ERC20 token that provides the option for an owner to lock some of its tokens using smart contracts. A time-lock and an escrow party account or smart contract can be specified allowing the tokens to be unlocked when certain business conditions are met. For validation purposes, we have considered a peer-to-peer energy trading scenario in which the Lockable ERC20 token was used to digitize the surplus of energy of prosumers. In this case, the energy tokens committed in blockchain transactions are successfully locked up until the actual delivery of energy, the settlement considering the monitored data of energy meters.
Data sharing is very important for accelerating scientific research, business innovations, and for informing individuals. Yet, concerns over data privacy, cost, and lack of secure data-sharing solutions have prevented data owners from sharing data. To overcome these issues, several research works have proposed blockchain-based data-sharing solutions for their ability to add transparency and control to the data-sharing process. Yet, while models for decentralized data sharing exist, how to incentivize these structures to enable data sharing at scale remains largely unexplored. In this paper, we propose incentive mechanisms for decentralized data-sharing platforms. We use smart contracts to automate different payment options between data owners and data requesters. We discuss multiple cost pricing scenarios for data owners to monetize their data. Moreover, we simulate the incentive mechanisms on a blockchain-based data-sharing platform. The evaluation of our simulation indicates that a cost compensation model for the data owner can rapidly cover the cost of data sharing and balance the overall incentives for all the actors in the platform.
Zeta Avarikioti, Krzysztof Pietrzak, Iosif Salem, Stefan Schmid · 6 authors
Payment channels effectively move the transaction load off-chain thereby successfully addressing the inherent scalability problem most cryptocurrencies face. A major drawback of payment channels is the need to ``top up'' funds on-chain when a channel is depleted. Rebalancing was proposed to alleviate this issue, where parties with depleting channels move their funds along a cycle to replenish their channels off-chain. Protocols for rebalancing so far either introduce local solutions or compromise privacy. In this work, we present an opt-in rebalancing protocol that is both private and globally optimal, meaning our protocol maximizes the total amount of rebalanced funds. We study rebalancing from the framework of linear programming. To obtain full privacy guarantees, we leverage multi-party computation in solving the linear program, which is executed by selected participants to maintain efficiency. Finally, we efficiently decompose the rebalancing solution into incentive-compatible cycles which conserve user balances when executed atomically. Keywords: Payment Channel Networks, Privacy and Rebalancing.
Romaric Duvignau, Michel Raynal, Elad Michael Schiller
One of the most celebrated problems of fault-tolerant distributed computing is the consensus problem. It was shown to abstract a myriad of problems in which processes have to agree on a single value. Consensus applications include fundamental services for the environments of the Cloud or Blockchain. In such challenging environments, malicious behavior is often modeled as adversarial Byzantine faults. At OPODIS 2010, Moste}faoui and Raynal, in short, MR, presented a Byzantine- and intrusion-tolerant solution to consensus in which the decided value cannot be a value proposed only by Byzantine processes. In addition to this validity property, MR has optimal resilience since it can deal with up to t < n/3 Byzantine processes, where n is the number of processes. We note that MR provides this multivalued consensus object (which accepts proposals taken from a set with a finite number of values) assuming the availability of a single Binary consensus object (which accepts proposals taken from the set {0,1}). This work, which focuses on multivalued consensus, aims at the design of an even more robust solution than MR. Our proposal expands MR's fault-model with self-stabilization, a vigorous notion of fault-tolerance. In addition to tolerating Byzantine and communication failures, self-stabilizing systems can automatically recover after the occurrence of arbitrary transient-faults. These faults represent any violation of the assumptions according to which the system was designed to operate (provided that the algorithm code remains intact). To the best of our knowledge, we propose the first self-stabilizing solution for intrusion-tolerant multivalued consensus for asynchronous message-passing systems prone to Byzantine failures.
Andreas Penzkofer, Olivia Saa, Daria Dziubałtowska
In distributed ledger technologies (DLTs) with a directed acyclic graph (DAG) data structure, a message-issuing node can decide where to append that message and, consequently, how to grow the DAG. This DAG data structure can typically be decomposed into two pools of messages: referenced messages and unreferenced messages (tips). The selection of the parent messages to which a node appends the messages it issues, depends on which messages it considers as tips. However, the exact time that a message enters the tip pool of a node depends on the delay of that message. In previous works, it was considered that messages have the same or similar delay; however, this generally may not be the case. We introduce the concept of classes of delays, where messages belonging to a certain class have a specific delay, and where these classes coexist in the DAG. We provide a general model that predicts the tip pool size for any finite number of different classes. This categorisation and model is applied to the first iteration of the IOTA 2.0 protocol (a.k.a. Coordicide), where two distinct classes, namely value and data messages, coexist. We show that the tip pool size depends strongly on the dominating class that is present. Finally, we provide a methodology for controlling the tip pool size by dynamically adjusting the number of references a message creates.
In recent years, blockchain networks have attracted significant attention in many research areas beyond cryptocurrency, one of them being the Edge of Things (EoT) that is enabled by the combination of edge computing and the Internet of Things (IoT). In this context, blockchain networks enabled with unique features, such as decentralization, immutability, and traceability, have the potential to reshape and transform the conventional EoT systems with higher security levels. Particularly, the convergence of blockchain and EoT leads to a new paradigm, calledBEoTthat has been regarded as a promising enabler for future services and applications. In this article, we present a state-of-the-art review of recent developments in the BEoT technology and discover its great opportunities in many application domains. We start our survey by providing an updated introduction to blockchain and EoT along with their recent advances. Subsequently, we discuss the use of BEoT in a wide range of industrial applications, from smart transportation, smart city, smart healthcare to smart home, and smart grid. Security challenges in the BEoT paradigm are also discussed and analyzed, with some key services, such as access authentication, data privacy preservation, attack detection, and trust management. Finally, some key research challenges and future directions are also highlighted to instigate further research in this promising area.
Oct 10, 2021·Proceedings of the ... Annual Hawaii International Conference on System Sciences/Proceedings of the Annual Hawaii International Conference on System Sciences
Johannes Sedlmeir, Tim Wagner, Emil Djerekarov, Ryan Green · 6 authors
Enterprises have been attracted by the capability of blockchains to provide a single source of truth for workloads that span companies, geographies, and clouds while retaining the independence of each party's IT operations. However, so far production applications have remained rare, stymied by technical limitations of existing blockchain technologies and challenges with their integration into enterprises' IT systems. In this paper, we collect enterprises' requirements on distributed ledgers for data sharing and integration from a technical perspective, argue that they are not sufficiently addressed by available blockchain frameworks, and propose a novel distributed ledger design that is "serverless", i.e., built on cloud-native resources. We evaluate its qualitative and quantitative properties and give evidence that enterprises already heavily reliant on cloud service providers would consider such an approach acceptable, particularly if it offers ease of deployment, low transactional cost structure, and a combination of latency and scalability aligned with real-time IT application needs.
Beatriz Soret, Lam Duc Nguyen, Jan Seeger, Arne Bröring · 10 authors
An Intelligent IoT Environment (iIoTe) is comprised of heterogeneous devices that can collaboratively execute semi-autonomous IoT applications, examples of which include highly automated manufacturing cells or autonomously interacting harvesting machines. Energy efficiency is key in such edge environments, since they are often based on an infrastructure that consists of wireless and battery-run devices, e.g., e-tractors, drones, Automated Guided Vehicle (AGV)s and robots. The total energy consumption draws contributions from multiple iIoTe technologies that enable edge computing and communication, distributed learning, as well as distributed ledgers and smart contracts. This paper provides a state-of-the-art overview of these technologies and illustrates their functionality and performance, with special attention to the tradeoff among resources, latency, privacy and energy consumption. Finally, the paper provides a vision for integrating these enabling technologies in energy-efficient iIoTe and a roadmap to address the open research challenges.
Shantanu Pal, Ambrose Hill, Tahiry Rabehaja, Michael Hitchens
Allocation of resources and their control over multiple organisations is challenging. This is especially true for a large-scale and dynamic system like the Internet of Things (IoT). One of the core issues in such a system is the provision of secure access control. In particular, transfer of access rights from one entity to another in a secure, flexible and fine-grained manner. In this paper, we present a multi-organisational delegation framework using blockchain. Our framework takes advantage of blockchain smart contracts to define the interactions and resource allocation between the consortium of organisations. We show the feasibility of our solution in a real-world scenario using the allocation of transportation credits in a multi-level organisational setting as a use-case. We provide proof of implementation of the proposed framework using the Hyperledger Fabric blockchain platform. Our results indicate that the proposed framework is efficient and can be used for city-wide transport, potentially even scale country-wide with a shared blockchain with complex access control rules. It also bestows better transparency to the delegation of access rights and control over the employees' transportation access for the organisations.
Advances in blockchains have influenced the State-Machine-Replication (SMR) world and many state-of-the-art blockchain-SMR solutions are based on two pillars: Chaining and Leader-rotation. A predetermined round-robin mechanism used for Leader-rotation, however, has an undesirable behavior: crashed parties become designated leaders infinitely often, slowing down overall system performance. In this paper, we provide a new Leader-Aware SMR framework that, among other desirable properties, formalizes a Leader-utilization requirement that bounds the number of rounds whose leaders are faulty in crash-only executions. We introduce Carousel, a novel, reputation-based Leader-rotation solution to achieve Leader-Aware SMR. The challenge in adaptive Leader-rotation is that it cannot rely on consensus to determine a leader, since consensus itself needs a leader. Carousel uses the available on-chain information to determine a leader locally and achieves Liveness despite this difficulty. A HotStuff implementation fitted with Carousel demonstrates drastic performance improvements: it increases throughput over 2x in faultless settings and provided a 20x throughput increase and 5x latency reduction in the presence of faults.
Kevin Coutinho, Ponnie Clark, Ferdinand Azis, Norman Lip · 5 authors
Interoperability and scalability are currently the bottlenecks preventing mass adoption of blockchain technology. Development of an interoperable and scalable network that promotes a truly decentralised, permissionless and secure blockchain as well as one that enables micro validation is the main goal of this project. Layer-One.X, a truly decentralised ledger which utilises para-sharding, Directed Acyclic Graphs, Proof of Participation consensus mechanism, mobile computing, flash contracts and nucleus scripting is introduced in this paper. The conceptual framework including tokenomics is also explained along with a number of use cases. The framework facilitates the growing need of transaction per second enabling micro based payments and value transfer through tokenisation.
Low latency is one of the desired properties for partially synchronous Byzantine consensus protocols. Previous protocols have achieved consensus with just two communication steps either by reducing the bound on the number of faults the protocol can tolerate ($f \leq \frac{n-1}{5}$) or use of trusted hardware like Trusted Execution Environment or TEEs. In this paper, we propose a protocol called Fast B4B, in which the protocol achieves consensus in just two communication steps. Fast B4B can tolerate maximum number of faults a partial BFT consensus can tolerate ($f \leq \frac{n-1}{3}$). Furthermore, Fast B4B does not require the use of any trusted hardware. The trade-off for this achievement is that at most $f$ times some nodes may revert their blocks. We show that this reversion of a block will not compromise the safety of the protocol at all, yet it may incur a small amount of additional latency during view change.
Recent years have witnessed an increasing interest in the blockchain technology, and many blockchain-based applications have been developed to take advantage of its decentralization, transparency, fault tolerance, and strong security. In the field of smart grids, a plethora of proposals have emerged to utilize blockchain for augmenting intelligent energy management, energy trading, security and privacy protection, microgrid management, and energy vehicles. Compared with traditional centralized approaches, blockchain-based solutions are able to exploit the advantages of blockchain to realize better functionality in smart grids. However, the blockchain technology itself has its disadvantages in low processing throughput and weak privacy protection. Therefore, it is of paramount importance to study how to integrate blockchain with smart grids in a more effective way so that the advantages of blockchain can be maximized and its disadvantages can be avoided. This article surveys the state-of-the-art solutions aiming to integrate the emergent blockchain technology with smart grids. The goal of this survey is to discuss the necessity of applying blockchain in different components of smart grids, identify the challenges encountered by current solutions, and highlight the frameworks and techniques used to integrate blockchain with smart grids. We also present thorough comparison studies among blockchain-based solutions for smart grids from different perspectives, with the aim to provide insights on integrating blockchain with smart grids for different smart grid management tasks. Finally, we list the current projects and initiatives demonstrating the current effort from the practice side. Additionally, we draw attention to open problems that have not yet been tackled by existing solutions, and point out possible future research directions.
Sebastian Müller, Angelo Capossele, Bartosz Kuśmierz, Vivian Lin · 9 authors
The security of any Distributed Ledger Technology (DLT) depends on the safety of the network layer. Much effort has been put into understanding the consensus layer of DLTs. However, many network layer designs seem ad-hoc and lack a careful analysis of the influence of the design decisions on the whole DLT system. We propose a salt-based automated neighbor selection protocol that shows the inherent tradeoffs of certain design decisions and allows a quantitative treatment of some network topology requirements. This example may serve as a design framework and facilitate future research. We provide a selection of results from simulations to highlight some tradeoffs in the design decisions.
This paper describes BigBFT, a multi-leader Byzantine fault tolerance protocol that achieves high throughput and scalable consensus in blockchain systems. BigBFT achieves this by (1) enabling every node to be a leader that can propose and order the blocks in parallel, (2) piggybacking votes within rounds, (3) pipelining blocks across rounds, and (4) using only two communication steps to order blocks in the common case. BigBFT has an amortized communication cost of $O(n)$ over $n$ requests. We evaluate BigBFT's performance both analytically, using back-of-the-envelope load formulas to construct a cost analysis, and also empirically by implementing it in our PaxiBFT framework. Our evaluation compares BigBFT with PBFT, Tendermint, Streamlet, and Hotstuff under various workloads using deployments of 4 to 20 nodes. Our results show that BigBFT outperforms PBFT, Tendermint, Streamlet, and Hotstuff protocols either in terms of latency (by up to $70\%$) or in terms of throughput (by up to $190\%$).
Mihai Christodorescu, Erin English, Wanyun Catherine Gu, David Kreissman · 10 authors
With the innovation of distributed ledger technology (DLT), often known as blockchain technology, there has been significant growth of digital tokens in the form of cryptocurrencies, stablecoins, and central bank digital currencies. As the number of DLT networks increases, each with varying design characteristics, the likelihood that transacting parties are on the same network decreases. Thus, it is crucial to facilitate payments that are universal across networks, scalable to massive loads, and highly available. We envision a future payment network that may be built on top of DLT networks without being subject to their limitations on interoperability, scalability, and availability faced by DLT payment solutions today. Specifically, we propose a hub-and-spoke payment route, referred to here as Universal Payment Channels (UPC), that can be used to support digital token transfers of funds across different networks through payment channels. We further discuss the potential use cases of the UPC technology to support, and not complicate, an already robust digital payment ecosystem. Finally, through the paper, we share some future directions of the UPC technology.
Many aspects of blockchain-based decentralized finance can be understood as an extension of classical distributed computing. In this paper, we trace the evolution of two interrelated notions: failure and fault-tolerance. In classical distributed computing, a failure to complete a multi-party protocol is typically attributed to hardware malfunctions. A fault-tolerant protocol is one that responds to such failures by rolling the system back to an earlier consistent state. In the presence of Byzantine failures, a failure may be the result of an attack, and a fault-tolerant protocol is one that ensures that attackers will be punished and victims compensated. In modern decentralized finance however, failure to complete a protocol can be considered a legitimate option, not a transgression. A fault-tolerant protocol is one that ensures that the party offering the option cannot renege, and the party purchasing the option provides fair compensation (in the form of a fee) to the offering party. We sketch the evolution of such protocols, starting with two-phase commit, and finishing with timed hashlocked smart contracts.
Several distributed system paradigms utilize Distributed Hash Tables (DHTs) to realize structured peer-to-peer (P2P) overlays. DHT structures arise as the most commonly used organizations for peers that can efficiently perform crucial services such as data storage, replication, query resolution, and load balancing. With the advances in various distributed system technologies, novel and efficient solutions based on DHTs emerge and play critical roles in system design. DHT-based methods and communications have been proposed to address challenges such as scalability, availability, reliability and performance, by considering unique characteristics of these technologies. In this article, we propose a classification of the state-of-the-art DHT-based methods focusing on their system architecture, communication, routing and technological aspects across various system domains. To the best of our knowledge, there is no comprehensive survey on DHT-based applications from system architecture and communication perspectives that spans various domains of recent distributed system technologies. We investigate the recently emerged DHT-based solutions in the seven key domains of edge and fog computing, cloud computing, blockchain, the Internet of Things (IoT), Online Social Networks (OSNs), Mobile Ad Hoc Networks (MANETs), and Vehicular Ad Hoc Networks (VANETs). In contrast to the existing surveys, our study goes beyond the commonly known DHT methods such as storage, routing, and lookup, and identifies diverse DHT-based solutions including but not limited to aggregation, task scheduling, resource management and discovery, clustering and group management, federation, data dependency management, and data transmission. Furthermore, we identify open problems and discuss future research guidelines for each domain.
Giorgia Azzurra Marson, Sebastien Andreina, Lorenzo Alluminio, Konstantin Munichev · 5 authors
Scalability remains one of the biggest challenges to the adoption of permissioned blockchain technologies for large-scale deployments. Permissioned blockchains typically exhibit low latencies, compared to permissionless deployments -- however at the cost of poor scalability. Various solutions were proposed to capture "the best of both worlds", targeting low latency and high scalability simultaneously, the most prominent technique being blockchain sharding. However, most existing sharding proposals exploit features of the permissionless model and are therefore restricted to cryptocurrency applications. We present MITOSIS, a novel approach to practically improve scalability of permissioned blockchains. Our system allows the dynamic creation of blockchains, as more participants join the system, to meet practical scalability requirements. Crucially, it enables the division of an existing blockchain (and its participants) into two -- reminiscent of mitosis, the biological process of cell division. MITOSIS inherits the low latency of permissioned blockchains while preserving high throughput via parallel processing. Newly created chains in our system are fully autonomous, can choose their own consensus protocol, and yet they can interact with each other to share information and assets -- meeting high levels of interoperability. We analyse the security of MITOSIS and evaluate experimentally the performance of our solution when instantiated over Hyperledger Fabric. Our results show that MITOSIS can be ported with little modifications and manageable overhead to existing permissioned blockchains, such as Hyperledger Fabric.
In this paper we describe LUNES-Blockchain, an agent-based simulator of blockchains that relies on Parallel and Distributed Simulation (PADS) techniques to obtain high scalability. The software is organized as a multi-level simulator that permits to simulate a virtual environment, made of many nodes running the protocol of a specific Distributed Ledger Technology (DLT), such as the Bitcoin or the Ethereum blockchains. This virtual environment is executed on top of a lower-level Peer-to-Peer (P2P) network overlay, which can be structured based on different topologies and with a given number of nodes and edges. Functionalities at different levels of abstraction are managed separately, by different software modules and with different time granularity. This allows for accurate simulations, where (and when) it is needed, and enhances the simulation performance. Using LUNES-Blockchain, it is possible to simulate different types of attacks on the DLT. In this paper, we specifically focus on the P2P layer, considering the selfish mining, the 51% attack and the Sybil attack. For which concerns selfish mining and the 51% attack, our aim is to understand how much the hash-rate (i.e. a general measure of the processing power in the blockchain network) of the attacker can influence the outcome of the misbehaviour. On the other hand, in the filtering denial of service (i.e. Sybil Attack), we investigate which dissemination protocol in the underlying P2P network makes the system more resilient to a varying number of nodes that drop the messages. The results confirm the viability of the simulation-based techniques for the investigation of security aspects of DLTs.
Christos Chrysoulas, A. M. Thomson, Nikolaos Pitropakis, Pavlos Papadopoulos · 10 authors
The continuously advancing digitization has provided answers to the bureaucratic problems faced by eGovernance services. This innovation led them to an era of automation it has broadened the attack surface and made them a popular target for cyber attacks. eGovernance services utilize internet, which is currently a location addressed system where whoever controls the location controls not only the content itself, but the integrity of that content, and the access to that content. We propose GLASS, a decentralised solution which combines the InterPlanetary File System (IPFS) with Distributed Ledger technology and Smart Contracts to secure EGovernance services. We also create a testbed environment where we measure the IPFS performance.
Guntur Dharma Putra, Volkan Dedeoglu, Salil S Kanhere, Raja Jurdak
The salient features of blockchain, such as decentralisation and transparency, have allowed the development of Decentralised Trust and Reputation Management Systems (DTRMS), which mainly aim to quantitatively assess the trustworthiness of the network participants and help to protect the network from adversaries. In the literature, proposals of DTRMS have been applied to various Cyber-physical Systems (CPS) applications, including supply chains, smart cities and distributed energy trading. In this chapter, we outline the building blocks of a generic DTRMS and discuss how it can benefit from blockchain. To highlight the significance of DTRMS, we present the state-of-the-art of DTRMS in various field of CPS applications. In addition, we also outline challenges and future directions in developing DTRMS for CPS.