This report summarizes the requirements and proposes a high-level solution for interoperability across recently proposed COVID-19 exposure notification efforts. Our focus is on interoperability across exposure notification (EN) applications which are based on the decentralized Bluetooth Low Energy (BLE) protocol driven by Google/Apple Exposure Notifications API (including DP3T and similar protocols). We distinguish different interoperability use cases, such as worldwide public EN interoperability, as well as interoperability in the enterprise EN systems. This report also proposes an API and a backend implementation architecture for EN interoperability. Finally, we propose using a permissioned blockchain-based solution for managing EN backend certificates and configurations (without storing any users' data on the blockchain) for helping address EN interoperability challenges across different vendors.
Mayra Samaniego, Sara Hosseinzadeh Kassani, Cristian Espana, Ralph Deters
Computer-Aided Diagnosis (CAD) systems have emerged to support clinicians in interpreting medical images. CAD systems are traditionally combined with artificial intelligence (AI), computer vision, and data augmentation to evaluate suspicious structures in medical images. This evaluation generates vast amounts of data. Traditional CAD systems belong to a single institution and handle data access management centrally. However, the advent of CAD systems for research among multiple institutions demands distributed access management. This research proposes a blockchain-based solution to enable distributed data access management in CAD systems. This solution has been developed as a distributed application (DApp) using Ethereum in a consortium network.
Due to their rapid growth and deployment, the Internet of things (IoT) have become a central aspect of our daily lives. Unfortunately, IoT devices tend to have many vulnerabilities which can be exploited by an attacker. Unsupervised techniques, such as anomaly detection, can be used to secure these devices in a plug-and-protect manner. However, anomaly detection models must be trained for a long time in order to capture all benign behaviors. Furthermore, the anomaly detection model is vulnerable to adversarial attacks since, during the training phase, all observations are assumed to be benign. In this paper, we propose (1) a novel approach for anomaly detection and (2) a lightweight framework that utilizes the blockchain to ensemble an anomaly detection model in a distributed environment. Blockchain framework incrementally updates a trusted anomaly detection model via self-attestation and consensus among the IoT devices. We evaluate our method on a distributed IoT simulation platform, which consists of 48 Raspberry Pis. The simulation demonstrates how the approach can enhance the security of each device and the security of the network as a whole.
Blockchain protocols differ in fundamental ways, including the mechanics of selecting users to produce blocks (e.g., proof-of-work vs. proof-of-stake) and the method to establish consensus (e.g., longest chain rules vs. BFT-inspired protocols). These fundamental differences have hindered "apples-to-apples" comparisons between different categories of blockchain protocols and, in turn, the development of theory to formally discuss their relative merits. This paper presents a parsimonious abstraction sufficient for capturing and comparing properties of many well-known permissionless blockchain protocols, simultaneously capturing essential properties of both proof-of-work and proof-of-stake protocols, and of both longest-chain-type and BFT-type protocols. Our framework blackboxes the precise mechanics of the user selection process, allowing us to isolate the properties of the selection process which are significant for protocol design. We illustrate our framework's utility with two results. First, we prove an analog of the CAP theorem from distributed computing for our framework in a partially synchronous setting. This theorem shows that a fundamental dichotomy holds between protocols (such as Bitcoin) that are adaptive, in the sense that they can function given unpredictable levels of participation, and protocols (such as Algorand) that have certain finality properties. Second, we formalize the idea that proof-of-work (PoW) protocols and non-PoW protocols can be distinguished by the forms of permission that users are given to carry out updates to the state.
Mobile edge computing (MEC) and next-generation mobile networks are set to disrupt the way intelligent and autonomous systems are interconnected. This will have an effect on a wide range of domains, from the Internet of Things to autonomous mobile robots. The integration of such a variety of MEC services in a inherently distributed architecture requires a robust system for managing hardware resources, balancing the network load and securing the distributed applications. Blockchain technology has emerged a solution for managing MEC services, with consensus protocols and data integrity checks that enable transparent and efficient distributed decision-making. In addition to transparency, the benefits from a security point of view are evident. Nonetheless, blockchain technology faces significant challenges in terms of scalability. In this chapter, we review existing consensus protocols and scalability techniques in both well-established and next-generation blockchain architectures. From this, we evaluate the most suitable solutions for managing MEC services and discuss the benefits and drawbacks of the available alternatives.
Off-grid networks are recently emerging as a solution to connect the unconnected or provide alternative services to networks of possibly untrusted participants. The systems currently used, however, exhibit limitations due to their centralized nature and thus prove inadequate to secure trust. Blockchain technology can be the tool that will enable trust and transparency in such networks. In this paper, we introduce a platform for secure and privacy-respecting decentralized data sharing among untrusted participants in off-grid networks. The proposed architecture realizes this goal via the integration of existing blockchain frameworks (Hyperledger Fabric, Indy, Aries) with an off-grid network device and a distributed file system. We evaluate the proposed platform through experiments and show results for its throughput and latency, which indicate its adequate performance for supporting off-grid decentralized applications.
Learning from data owned by several parties, as in federated learning, raises challenges regarding the privacy guarantees provided to participants and the correctness of the computation in the presence of malicious parties. We tackle these challenges in the context of distributed averaging, an essential building block of federated learning algorithms. Our first contribution is a scalable protocol in which participants exchange correlated Gaussian noise along the edges of a network graph, complemented by independent noise added by each party. We analyze the differential privacy guarantees of our protocol and the impact of the graph topology under colluding malicious parties, showing that we can nearly match the utility of the trusted curator model even when each honest party communicates with only a logarithmic number of other parties chosen at random. This is in contrast with protocols in the local model of privacy (with lower utility) or based on secure aggregation (where all pairs of users need to exchange messages). Our second contribution enables users to prove the correctness of their computations without compromising the efficiency and privacy guarantees of the protocol. Our verification protocol relies on standard cryptographic primitives like commitment schemes and zero knowledge proofs.
Blockchain technology provides an auditable and tamper-proof distributed storage infrastructure for information records. This can be leveraged to support distributed workflow management. Compared to proof-of-work consensus, popularized by Bitcoin and Ethereum, blockchains based on BFT (byzantine fault tolerance) ordering consensus trade scalability for immediacy and finality of consensus. This makes them easier to use as distribution infrastructure, as applications need not be adapted to deal with eventual consistency and delayed consensus of proof-of-work blockchains. Hence, applications such as workflow engines can be easily ported to such a blockchain infrastructure to take advantage of their decentralized integrity assurance and information distribution model. In this paper we describe how the YAWL workflow engine can be used on a BFT based blockchain infrastructure to enable collaborative workflows across different organizations.
Marcin Abram, David Galindo, Daniel Honerkamp, Jonathan Ward · 5 authors
We propose a novel consensus protocol based on a hybrid approach, that combines a directed acyclic graph (DAG) and a classical chain of blocks. This architecture allows us to enforce collective block construction, minimising the monopolistic power of the round-leader. In this way, we decrease the possibility for collusion among senders and miners, as well as miners themselves, allowing the use of more incentive compatible and fair pricing strategies. We investigate these possibilities alongside the ability to use the DAG structure to minimise the risk of transaction censoring. We conclude by providing preliminary benchmarks of our protocol and by exploring further research directions.
Zoltán Lux, Dirk Thatmann, Sebastian Zickau, Felix Beierle
Authentication with username and password is becoming an inconvenient process for the user. End users typically have little control over their personal privacy, and data breaches effecting millions of users have already happened several times. We have implemented a proof of concept decentralized OpenID Connect Provider by marrying it with Self-Sovereign Identity, which gives users the freedom to choose from a very large pool of identity providers instead of just a select few corporations, thus enabling the democratization of the highly centralized digital identity landscape. Furthermore, we propose a verifiable credential powered decentralized Public Key Infrastructure using distributed ledger technologies, which creates a straightforward and verifiable way for retrieving digital certificates.
Privacy preservation is a big concern for various sectors. To protect individual user data, one emerging technology is differential privacy. However, it still has limitations for datasets with frequent queries, such as the fast accumulation of privacy cost. To tackle this limitation, this paper explores the integration of a secured decentralised ledger, blockchain. Blockchain will be able to keep track of all noisy responses generated with differential privacy algorithm and allow for certain queries to reuse old responses. In this paper, a demo of a proposed blockchain-based privacy management system is designed as an interactive decentralised web application (DApp). The demo created illustrates that leveraging on blockchain will allow the total privacy cost accumulated to decrease significantly.
Existing Byzantine fault-tolerant (BFT) consensus protocols address only threshold failures, where the participating nodes fail independently of each other, each one fails equally likely, and the protocol's guarantees follow from a simple bound on the number of faulty nodes. With the widespread deployment of Byzantine consensus in blockchains and distributed ledgers today, however, more sophisticated trust assumptions are needed. This paper presents the first implementation of BFT consensus with generalized quorums. It starts from a number of generalized trust structures motivated by practice and explores methods to specify and implement them efficiently. In particular, it expresses the trust assumption by a monotone Boolean formula (MBF) with threshold operators and by a monotone span program (MSP), a linear-algebraic model for computation. An implementation of HotStuff BFT consensus using these quorum systems is described as well and compared to the existing threshold model. Benchmarks with HotStuff running on up to 40 replicas demonstrate that the MBF specification incurs no significant slowdown, whereas the MSP expression affects latency and throughput noticeably due to the involved computations.
With the recent considerable developments in the Internet of Things (IoT), billions of resource-constrained devices are interconnected through the internet. Monitoring this huge number of IoT devices that are heterogeneous in terms of underlying communication protocols and data format is challenging. The majority of existing IoT device monitoring solutions heavily rely on centralized architectures. Since using centralized architectures comes at the expense of trusting an authority, it has several inherent drawbacks, including vulnerability to security attacks, lack of data privacy, and unauthorized data manipulation. Hence, a new decentralized approach is crucial to remedy these drawbacks. One of the most promising technologies which is widely used to provide decentralization is blockchain. Additionally, to ease the burden of communication overhead and computational power on resource-constrained IoT devices, fog computing can be exploited to decrease communication latency and provide better network scalability. In this paper, we propose a scalable blockchain-based architecture for monitoring IoT devices using fog computing. To demonstrate the feasibility and usability of the proposed solution, we have implemented a proof-of-concept prototype, leveraging Ethereum smart contracts. Finally, a comprehensive evaluation is conducted. The evaluation results indicate that the proposed solution is significantly scalable and compatible with resource-constrained IoT devices.
Recent advances in blockchain technology have led to a significant interest in developing blockchain-based applications. While data can be retained in a blockchain, the stored values can be deleted or updated. From a user viewpoint that searches for data, it is unclear whether the discovered data from the blockchain storage is relevant for real-time decision-making processes for block-chain-based applications. The data freshness issue serves as a critical factor, especially in dynamic networks handling real-time information. In general, transactions to renew data require additional processing time inside the blockchain network, which is called ledger-commitment latency. Due to this problem, some users may receive outdated data. As a result, it is important to investigate if the blockchain is suitable for providing real-time data services. In this article, we first describe block-chain-enabled (BCE) networks with Hyperledger Fabric (HLF). Then, we define age-of-information (AoI) of BCE networks and investigate influential factors on this AoI. Experiments are conducted to explore the impacts of the influential factors on data freshness in BCE networks. Lastly, we conclude by discussing future challenges.
Initiated from Nakamoto's Bitcoin system, blockchain technology has demonstrated great capability of building secure consensus among decentralized parties at Internet-scale, i.e., without relying on any centralized trusted party. Nowadays, blockchain systems find applications in various fields. But the performance is increasingly becoming a bottleneck, especially when permissionless participation is retained for full decentralization. In this work, we present a new consensus protocol named GHAST (Greedy Heaviest Adaptive Sub-Tree) which organizes blocks in a Tree-Graph structure (i.e., a directed acyclic graph (DAG) with a tree embedded) that allows fast and concurrent block generation. GHAST protocol simultaneously achieves a logarithmically bounded liveness guarantee and low confirmation latency. More specifically, for maximum latency $d$ and adversarial computing power bounded away from 50\%, GHAST guarantees confirmation with confidence $\ge 1-\varepsilon$ after a time period of $O(d\cdot \log(1/\varepsilon))$. When there is no observable attack, GHAST only needs $3d$ time to achieve confirmation at the same confidence level as six-block-confirmation in Bitcoin, while it takes roughly $360d$ in Bitcoin.
In this paper, we present a pricing mechanism that aligns incentives of agents who exchange resources on a decentralized ledger with the goal of maximizing transaction throughput. Subdividing a blockchain ledger into shards promises to greatly increase transaction throughput with minimal loss of security. However, the organization and type of the transactions also affects the ledger's efficiency, which is increased by wallet agents transacting in a single shard whenever possible while collectively distributing their transactions uniformly across the available shards. Since there is no central authority to enforce these properties, the only means of achieving them is to design the system such that it is in agents' interest to act in a way that benefits overall throughput. We show that our proposed pricing policy does exactly this by inducing a potential game for the agents, where the potential function relates directly to ledger throughput. Simulations demonstrate that this policy leads to near-optimal throughput under a variety of conditions.
A companion paper defined the notion of digital social contracts, presented a design for a social-contracts programming language, and demonstrated its potential utility via example social contracts. The envisioned setup consists of people with genuine identifiers, which are unique and singular cryptographic key pairs, that operate software agents thus identified on their mobile device. The abstract model of digital social contracts consists of a transition system specifying concurrent, non-deterministic asynchronous agents that operate on a shared ledger by performing digital speech acts, which are cryptographically-signed sequentially-indexed digital actions. Here, we address the distributed-ledger implementation of digital social contracts in the presence of faulty agents: we present a design of a fault-tolerant distributed-ledger transition system and show that it implements the abstract shared-ledger model of digital social contracts, and discuss its resilience to faulty agents. The result is a novel ledger architecture that is distributed with a blockchain-per-person (as opposed to centralized with one blockchain for all), partially-ordered (as opposed to totally-ordered), locally-replicated (as opposed to globally-replicated), asynchronous (as opposed to globally-synchronized), peer-to-peer with each agent being both an actor and a validator (as opposed to having dedicated miners, validators, and clients), environmentally-friendly (as opposed to the environmentally-harmful Proof-of-Work), self-sufficient (as opposed to the energy-hogging Proof-of-Work or capital-hogging Proof-of-Stake) and egalitarian (as opposed to the plutocratic Proof-of-Work and Proof-of-Stake).
Rafael Belchior, André Vasconcelos, Sérgio Guerreiro, Miguel Correia
Blockchain interoperability is emerging as one of the crucial features of blockchain technology, but the knowledge necessary for achieving it is fragmented. This fact makes it challenging for academics and the industry to seamlessly achieve interoperability among blockchains. Given the novelty and potential of this new domain, we conduct a literature review on blockchain interoperability, by collecting 262 papers, and 70 grey literature documents, constituting a corpus of 332 documents. From those 332 documents, we systematically analyzed and discussed 80 documents, including both peer-reviewed papers and grey literature. Our review classifies studies in three categories: Cryptocurrency-directed interoperability approaches, Blockchain Engines, and Blockchain Connectors. Each category is further divided into sub-categories based on defined criteria. We discuss not only studies within each category and subcategory but also across categories, providing a holistic overview of blockchain interoperability, paving the way for systematic research in this domain. Our findings show that blockchain interoperability has a much broader spectrum than cryptocurrencies. The present survey leverages an interesting approach: we systematically contacted the authors of grey literature papers and industry solutions to obtain an updated view of their work. Finally, this paper discusses supporting technologies, standards, use cases, open challenges, and provides several future research directions.
Ivan Homoliak, Larangeira, Mario, Peresini, Martin, Szalachowski, Pawel
Distributed ledger systems (i.e., blockchains) have received a lot of attention. They promise to enable mutually untrusted participants to execute transactions while providing the immutability of the data and censorship resistance. Although decentralized ledgers are a disruptive innovation, as of today, they suffer from scalability, privacy, or governance issues. Therefore, they are inapplicable for many important use cases, where interestingly, centralized ledger systems might gain adoption. Unfortunately, centralized ledgers have also drawbacks, e.g., a lack of efficient verifiability or a higher risk of censorship and equivocation. In this paper, we present AQUAREUM, a novel framework for centralized ledgers removing their main limitations. By a unique combination of a trusted execution environment (TEE) with a public blockchain, AQUAREUM provides publicly verifiable non-equivocating censorship-evident private and high-performance ledgers. AQUAREUM is integrated with a Turing-complete virtual machine (e.g., EVM), allowing arbitrary transaction processing logic, such as transfers or client-specified smart contracts. AQUAREUM is fully implemented and can process over 400 transactions per second on a commodity PC. Furthermore, we modeled AQUAREUM using the Universal Composability framework and proved its security.
The Byzantine agreement problem is considered to be a core problem in distributed systems. For example, Byzantine agreement is needed to build a blockchain, a totally ordered log of records. Blockchains are asynchronous distributed systems, fault-tolerant against Byzantine nodes. In the literature, the asynchronous byzantine agreement problem is studied in a fully connected network model where every node can directly send messages to every other node. This assumption is questionable in many real-world environments. In the reality, nodes might need to communicate by means of an incomplete network, and Byzantine nodes might not forward messages. Furthermore, Byzantine nodes might not behave correctly and, for example, corrupt messages. Therefore, in order to truly understand Byzantine Agreement, we need both ingredients: asynchrony and incomplete communication networks. In this paper, we study the asynchronous Byzantine agreement problem in incomplete networks. A classic result by Danny Dolev proved that in a distributed system with n nodes in the presence of f Byzantine nodes, the vertex connectivity of the system communication graph should be at least (2f+1). While Dolev's result was for synchronous deterministic systems, we demonstrate that the same bound also holds for asynchronous randomized systems. We show that the bound is tight by presenting a randomized algorithm, and a matching lower bound.
Hao Xu, Lei Zhang, Oluwakayode Onireti, Yang Fang · 6 authors
The outbreak of the coronavirus disease 2019 (COVID-19) pandemic has exposed an urgent need for effective contact tracing solutions through mobile phone applications to prevent the infection from spreading further. However, due to the nature of contact tracing, public concern on privacy issues has been a bottleneck to the existing solutions, which is significantly affecting the uptake of contact tracing applications across the globe. In this article, we present a blockchain-enabled privacy-preserving contact tracing scheme: BeepTrace, where we propose to adopt blockchain bridging the user/patient and the authorized solvers to desensitize the user ID and location information. Compared with recently proposed contact tracing solutions, our approach shows higher security and privacy with the additional advantages of being battery friendly and globally accessible. Results show viability in terms of the required resource at both server and mobile phone perspectives. Through breaking the privacy concerns of the public, the proposed BeepTrace solution can provide a timely framework for authorities, companies, software developers, and researchers to fast develop and deploy effective digital contact tracing applications, to conquer the COVID-19 pandemic soon. Meanwhile, the open initiative of BeepTrace allows worldwide collaborations, integrate existing tracing and positioning solutions with the help of blockchain technology.
Ranvir Rana, Sreeram Kannan, David Tse, Pramod Viswanath
Propelled by the growth of large-scale blockchain deployments, much recent progress has been made in designing sharding protocols that achieve throughput scaling linearly in the number of nodes. However, existing protocols are not robust to an adversary adaptively corrupting a fixed fraction of nodes. In this paper, we propose Free2Shard -- a new architecture that achieves near-linear scaling while being secure against a fully adaptive adversary. The focal point of this architecture is a dynamic self-allocation algorithm that lets users allocate themselves to shards in response to adversarial action, without requiring a central or cryptographic proof. This architecture has several attractive features unusual for sharding protocols, including: (a) the ability to handle the regime of large number of shards (relative to the number of nodes); (b) heterogeneous shard demands; (c) requiring only a small minority to follow the self-allocation; (d) asynchronous shard rotation; (e) operation in a purely identity-free proof-of-work setting. The key technical contribution is a deep mathematical connection to the classical work of Blackwell in dynamic game theory.
Consensus is arguably one of the most important notions in distributed computing. Among asynchronous, randomized, and signature-free implementations, the protocols of Mostéfaoui et al. (PODC 2014 and JACM 2015) represent a landmark result, which has been extended later and taken up in practical systems. The protocols achieve optimal resilience and takes, in expectation, only a constant expected number of rounds of quadratic message complexity. Randomization is provided through a common-coin primitive. In traditional consensus protocols, all involved processes adhere to a global, symmetric failure model, typically only defined by bounds on the number of faulty processes. Motivated by applications to blockchains, however, more flexible trust assumptions have recently been considered. In particular, with asymmetric trust, a process is free to choose which other processes it trusts and which ones might collude against it. This paper revisits the optimal asynchronous protocol of Mostéfaoui et al. and shows how to realize it with asymmetric trust. The paper starts by pointing out in detail why some versions of this protocol may violate liveness. Then it proposes a fix for the protocol that does not affect its properties, but lets it regain the simplicity of its original version (PODC 2014). At the same time, the paper shows how to realize randomized signature-free asynchronous Byzantine consensus with asymmetric quorums. This results in an optimal consensus protocol with subjective, asymmetric trust and constant expected running time. It is suitable for applications to blockchains, for instance.
Quorum systems are a key mathematical abstraction in distributed fault-tolerant computing for capturing trust assumptions. A quorum system is a collection of subsets of all processes, called quorums, with the property that each pair of quorums have a non-empty intersection. They can be found at the core of many reliable distributed systems, such as cloud computing platforms, distributed storage systems and blockchains. In this paper we give a new interpretation of quorum systems, starting with classical majority-based quorum systems and extending this to Byzantine quorum systems. We propose an algebraic representation of the theory underlying quorum systems making use of multivariate polynomial ideals, incorporating properties of these systems, and studying their algebraic varieties. To achieve this goal we will exploit properties of Boolean Groebner bases. The nice nature of Boolean Groebner bases allows us to avoid part of the combinatorial computations required to check consistency and availability of quorum systems. Our results provide a novel approach to test quorum systems properties from both algebraic and algorithmic perspectives.