More than 500,000 people experience homelessness in America each day. Local and federal solutions to the problem have had limited success because of the fragmentation of services and lack of valid and timely information. Billions of dollars spent to provide reliable, timely, and actionable information in health care have exposed the difficulty of establishing such a system using the prevalent information technology solutions. However, relying on successful examples of the use of blockchain to help refugee populations and poor farmers internationally, we have partnered to propose an innovative solution to this problem using the case of people experiencing homelessness in Austin, Texas. This paper aims to describe one of the first applications of blockchain technology for addressing homelessness in the United States by creating a digital identity for people experiencing homelessness and engaging emergency medical services and clinical providers. The authors argue that a lack of documentation to prove personal identity and the inability to access own records are major hurdles for empowering persons experiencing homelessness to be resilient and overcome the life challenges they face. Furthermore, it is argued that this lack of information causes misdiagnosis, duplication, and fragmentation in service delivery, which can be potentially addressed by blockchain technology. Further planning for creating a program on the ground with additional funding will demonstrate the results of using blockchain technology to establish digital identity for persons experiencing homelessness.
Information fusion has been a topic of immense interest owing to its applicability in various applications. This brings to the fore the need for a flexible and accurate fusion algorithm that can be versatile. The Brooks–Iyengar algorithm is one such fusion algorithm. It has since its inception found numerous applications that deal with the fusion of data from multiple sources. The uniqueness of the Brooks–Iyengar algorithm is the ease with which the data from multiple sensors in a local system can be fused and also reach consensus in a distributed system with the added capability of fault tolerance. Blockchain has found its use as a distributed ledger and has successfully supported and fueled many crypto-currencies over the years. Information fusion with regards to Blockchains is a topic of great research interest in the past couple of years. Since blockchain has no official node, the introduction of a decentralized network and a consensus algorithm is required in making the interactions and exchanges between multiple suppliers easier and thus leads to business being carried out without any hassles. In this paper, we attempt to understand and describe the deployment of multiple sensors to measure various aspects of the physical world. We discuss a novel technique of employing the Brooks–Iyengar algorithm in the design of the system that would decentralize the data source from the corresponding measurements and thus ensure the integrity of the transactions in the Blockchain. Finally, a theoretical analysis of the performance of the algorithm when used in a blockchain based decentralized environment is also discussed.
Open access
Distributed systems and fault tolerance
Distributed Sensor Networks and Detection Algorithms
Target Tracking and Data Fusion in Sensor Networks
Industrial Internet of Things (IIoT) plays an indispensable role for Industry 4.0, where people are committed to implement a general, scalable, and secure IIoT system to be adopted across various industries. However, existing IIoT systems are vulnerable to single point of failure and malicious attacks, which cannot provide stable services. Due to the resilience and security promise of blockchain, the idea of combining blockchain and Internet of Things (IoT) gains considerable interest. However, blockchains are power-intensive and low-throughput, which are not suitable for power-constrained IoT devices. To tackle these challenges, we present a blockchain system with credit-based consensus mechanism for IIoT. We propose a credit-based proof-of-work (PoW) mechanism for IoT devices, which can guarantee system security and transaction efficiency simultaneously. In order to protect sensitive data confidentiality, we design a data authority management method to regulate the access to sensor data. In addition, our system is built based on directed acyclic graph -structured blockchains, which is more efficient than the Satoshi-style blockchain in performance. We implement the system on Raspberry Pi, and conduct a case study for the smart factory. Extensive evaluation and analysis results demonstrate that credit-based PoW mechanism and data access control are secure and efficient in IIoT.
Human societies engage in a number of games which use tokens as a means to allocate, issue and access gated resources and property rights: The notion of exchanging tokens that represent and carry value from the past into the future to facilitate economic exchange is a fundamental concept. As agents exchange tokens a network structure is created in which the tokens move from agent to agent. Agents form the vertices in the network and the exchange of tokens creates the link structure. The rules of exchange adopted collectively by agents shape the network structure and affect the distribution of tokens amongst agents. Many inventions including banking, payments networks and blockchain technology have been created for the purpose of keeping accurate records of these implicit networks. However, our formal understanding of tokenised systems as large scale, iterative, interacting structures is limited. The aim of this paper is to study the dynamics of token exchanges as a game, and introduce a mathematical framework for understanding ledgers as complex networks.
Pietro Danzi, Anders E. Kalør, René Sørensen, Alexander Korsvang Hagelskjær · 7 authors
The pervasive need to safely share and store information between devices calls for the replacement of centralized trust architectures with the decentralized ones. Distributed Ledger Technologies (DLTs) are seen as the most promising enabler of decentralized trust, but they still lack technological maturity and their successful adoption depends on the understanding of the fundamental design trade-offs and their reflection in the actual technical design. This work focuses on the challenges and potential solutions for an effective integration of DLTs in the context of Internet-of-Things (IoT). We first introduce the landscape of IoT applications and discuss the limitations and opportunities offered by DLTs. Then, we review the technical challenges encountered in the integration of resource-constrained devices with distributed trust networks. We describe the common traits of lightweight synchronization protocols, and propose a novel classification, rooted in the IoT perspective. We identify the need of receiving ledger information at the endpoint devices, implying a two-way data exchange that contrasts with the conventional uplink-oriented communication technologies intended for IoT systems.
Our aim in this paper is to investigate the profitability of double-spending (DS) attacks that manipulate an a priori mined transaction in a blockchain. It was well understood that a successful DS attack is established when the proportion of computing power an attacker possesses is higher than that the honest network does. What is not yet well understood is how threatening a DS attack with less than 50% computing power used can be. Namely, DS attacks at any proportion can be of a threat as long as the chance to making a good profit exists. Profit is obtained when the revenue from making a successful DS attack is greater than the cost of carrying out one. We have developed a novel probability theory for calculating a finite time attack probability. This can be used to size up attack resources needed to obtain the profit. The results enable us to derive a sufficient and necessary condition on the value of a transaction targeted by a DS attack. Our result is quite surprising: we theoretically show that DS attacks at any proportion of computing power can be made profitable. Given one's transaction size, the results can also be used to assess the risk of a DS attack. An example of the attack resources is provided for the BitcoinCash network.
Eric Venner, Mullai Murugan, Walker Hale, Jordan M Jones · 7 authors
MOTIVATION: Clinical genome sequencing laboratories return reports containing clinical testing results, signed by a board-certified clinical geneticist, to the ordering physician. This report is often a PDF, but can also be a paper copy or a structured data file. The reports are frequently modified and reissued due to changes in variant interpretation or clinical attributes. MATERIALS AND METHODS: To precisely track report authenticity, we developed ARBoR (Authenticated Resources in a Hashed Block Registry), an application for tracking the authenticity and lineage of versioned clinical reports even when they are distributed as PDF or paper copies. ARBoR tracks clinical reports as cryptographically signed hash blocks in an electronic ledger file, which is then exactly replicated to many clients. RESULTS: ARBoR was implemented for clinical reporting in the Human Genome Sequencing Center Clinical Laboratory, initially as part of the National Institute of Health's Electronic Medical Record and Genomics (eMERGE) project. CONCLUSIONS: To date, we have issued 15 205 versioned clinical reports tracked by ARBoR. This system has provided us with a simple and tamper-proof mechanism for tracking clinical reports with a complicated update history.
Bruno W. França, Sophie Radermacher, Reto Trinkler
Katallassos is a new blockchain that provides a standard way to build and deploy decentralized financial applications.
It brings together all the components necessary for the backend of a financial application, namely: a high-performance consensus, an authenticated data feed system, a standard for financial contracts and connectivity to the rest of the blockchain ecosystem.
Katallassos enables and simplifies the creation of financial services that are non-custodial, trustless, fast, convenient and interoperable.
Ferdiansyah Ferdiansyah, Edi Surya Negara, Yeni Widyanti
Cryptocurrency trade is now a popular type of investment. Cryptocurrency market has been treated similar to foreign exchange and stock market. The Characteristics of Bitcoin have made Bitcoin keep rising In the last few years. Bitcoin exchange rate to American Dollar (USD) is $3990 USD on November 2018, with daily pice fluctuations could reach 4.55%2. It is important to able to predict value to ensure profitable investment. However, because of its volatility, there’s a need for a prediction tool for investors to help them consider investment decisions for cryptocurrency trade. Nowadays, computing based tools are commonly used in stock and foreign exchange market predictions. There has been much research about SVM prediction on stocks and foreign exchange as case studies but none on cryptocurrency. Therefore, this research studied method to predict the market value of one of the most used cryptocurrency, Bitcoin. The preditct methods will be used on this research is regime prediction to develop model to predict the close value of Bitcoin and use Support vector classifier algorithm to predict the current day’s trend at the opening of the market
Pietro Danzi, Anders E. Kalør, René Sørensen, Alexander Korsvang Hagelskjær · 7 authors
The pervasive need to safely share and store information between devices\ncalls for the replacement of centralized trust architectures with the\ndecentralized ones. Distributed Ledger Technologies (DLTs) are seen as the most\npromising enabler of decentralized trust, but they still lack technological\nmaturity and their successful adoption depends on the understanding of the\nfundamental design trade-offs and their reflection in the actual technical\ndesign. This work focuses on the challenges and potential solutions for an\neffective integration of DLTs in the context of Internet-of-Things (IoT). We\nfirst introduce the landscape of IoT applications and discuss the limitations\nand opportunities offered by DLTs. Then, we review the technical challenges\nencountered in the integration of resource-constrained devices with distributed\ntrust networks. We describe the common traits of lightweight synchronization\nprotocols, and propose a novel classification, rooted in the IoT perspective.\nWe identify the need of receiving ledger information at the endpoint devices,\nimplying a two-way data exchange that contrasts with the conventional\nuplink-oriented communication technologies intended for IoT systems.\n
In this paper, we design and implement the first-ever decentralized replicated relational database with blockchain properties that we term blockchain relational database. We highlight several similarities between features provided by blockchain platforms and a replicated relational database, although they are conceptually different, primarily in their trust model. Motivated by this, we leverage the rich features, decades of research and optimization, and available tooling in relational databases to build a blockchain relational database. We consider a permissioned blockchain model of known, but mutually distrustful organizations each operating their own database instance that are replicas of one another. The replicas execute transactions independently and engage in decentralized consensus to determine the commit order for transactions. We design two approaches, the first where the commit order for transactions is agreed upon prior to executing them, and the second where transactions are executed without prior knowledge of the commit order while the ordering happens in parallel. We leverage serializable snapshot isolation (SSI) to guarantee that the replicas across nodes remain consistent and respect the ordering determined by consensus, and devise a new variant of SSI based on block height for the latter approach. We implement our system on PostgreSQL and present detailed performance experiments analyzing both approaches.
Cristina Elena Turcu, Cornel Turcu, Iuliana Chiuchisan
The proposed paper presents a literature review regarding the status of integrating the dynamic blockchain technology in the educational field. Blockchain is a relatively new technology and the same is its implementation in education. The emerging need in this area of research, which still is in its infancy, is justified by the possible use cases; some of these cases are in piloting phase, while others have already been adopted by educational institutions. This paper focuses on extending knowledge about blockchain and on identifying the benefits, risks and the associated challenges regarding the successful implementation of blockchain-based solutions in the field of education, fully in line with standards and guidelines for quality assurance.
Bruno W. França, Sophie Radermacher, Reto Trinkler
Katal is a new blockchain that provides a standard way to build and deploy decentralized financial applications. It brings together all the components necessary for the backend of a financial application, namely: a high-performance consensus, an authenticated data feed system, a standard for financial contracts and connectivity to the rest of the blockchain ecosystem. Katal enables and simplifies the creation of financial services that are non-custodial, trustless, fast, convenient and interoperable.
In this paper we introduce Enso, a virtual machine designed to be used as general-purpose state transition function in blockchains. This design allows the blockchain application logic to be coded into the state, instead of into the state transition function, making it much more flexible and easier to modify. A byproduct is reducing the frequency of forks, concerted or not.
Transactive energy systems (TES) are emerging as a transformative solution for the problems that distribution system operators face due to an increase in the use of distributed energy resources and rapid growth in scalability of managing active distribution system (ADS). On the one hand, these changes pose a decentralized power system control problem, requiring strategic control to maintain reliability and resiliency for the community and for the utility. On the other hand, they require robust financial markets while allowing participation from diverse prosumers. To support the computing and flexibility requirements of TES while preserving privacy and security, distributed software platforms are required. In this paper, we enable the study and analysis of security concerns by developing Transactive Energy Security Simulation Testbed (TESST), a TES testbed for simulating various cyber attacks. In this work, the testbed is used for TES simulation with centralized clearing market, highlighting weaknesses in a centralized system. Additionally, we present a blockchain enabled decentralized market solution supported by distributed computing for TES, which on one hand can alleviate some of the problems that we identify, but on the other hand, may introduce newer issues. Future study of these differing paradigms is necessary and will continue as we develop our security simulation testbed.
Blockchain technology and cryptoassets may have seized the attention of the financial services space, but as the technology ecosystem continues to mature there are additional considerations coming to the forefront. Smart contracts represent an important piece of the blockchain conversation and play a critical role in how blockchains interact with other technology platforms. Accounting and auditing professionals will need to understand both how smart contracts function, and also how these applications will impact accounting and auditing processes. The present paper, written keeping both the academic and practitioner audience in mind, seeks to examine how smart contracts interact with blockchain technology, analyze how these applications can change audit processes, and propose potential future roles for the profession.
Pascal Berrang, Philipp von Styp-Rekowsky, Marvin Wißfeld, Bruno W. França · 5 authors
The consensus protocol is a critical component of distributed ledgers and blockchains. Achieving consensus over a decentralized network poses challenges to transaction finality and performance. Currently, the highest-performing consensus algorithms are speculative BFT algorithms, which, however, compromise on the transaction finality guarantees offered by their non-speculative counterparts. In this paper, we introduce Albatross, a Proof-of-Stake (PoS) blockchain consensus algorithm that aims to combine the best of both worlds. At its heart, Albatross is a high-performing, speculative BFT algorithm that offers strong probabilistic finality. We complement this by periodically guaranteeing finality through the Tendermint protocol. We prove our protocol to be secure under standard BFT assumptions and analyze its performance both on a theoretical and practical level. For that, we provide an open-source Rust implementation of Albatross. Our real-world measurements support that our protocol has a performance close to the theoretical maximum for single-chain Proof-of-Stake consensus algorithms.
This paper investigates the importance of "time of execution" and the relevance of "precision time" in order driven transactions done over distributed ledgers. We created a distributed marketplace using stock market price data from the Toronto Stock Exchange (TMX). We then proceeded to test and measure the impact of timing of orders at the nanosecond level. Whilst price discovery in order driven markets is done instantaneously, with distributed markets, it is necessary to know which order to process first to avoid "front-running". We argue that a protocol for the time of order of receipt and execution should be subject to nanosecond stacking. Our approach incorporates both transitory and permanent price discovery components. It allows for the efficient processing of transactions and the order that are received by a market clearing distributed ledger.
We propose a proof of mining system. Roughly speaking, in this system the mining stake ${\rm mstak}(A)$ with discrimination index $a\in[0,1]$ of an account $A$ is defined by the formula: $${\rm mstak}(A)=(1-a)\cdot\frac{1}{\rm NOM}+a\cdot\frac{{\rm NOBM}(A)}{L},$$ where $L$ is the length of the block-chain, ${\rm NOM}$ is the number of miners in the block-chain, and ${\rm NOBM}(A)$ is the number of blocks mined by $A$.
We study the dependency and causality structure of the cryptocurrency market investigating collective movements of both prices and social sentiment related to almost two thousand cryptocurrencies traded during the first six months of 2018. This is the first study of the whole cryptocurrency market structure. It introduces several rigorous innovative methodologies applicable to this and to several other complex systems where a large number of variables interact in a non-linear way, which is a distinctive feature of the digital economy. The analysis of the dependency structure reveals that prices are significantly correlated with sentiment. The major, most capitalised cryptocurrencies, such as bitcoin, have a central role in the price correlation network but only a marginal role in the sentiment network and in the network describing the interactions between the two. The study of the causality structure reveals a causality network that is consistently related with the correlation structures and shows that both prices cause sentiment and sentiment cause prices across currencies with the latter being stronger in size but smaller in number of significative interactions. Overall our study uncovers a complex and rich structure of interrelations where prices and sentiment influence each other both instantaneously and with lead-lag causal relations. A major finding is that minor currencies, with small capitalisation, play a crucial role in shaping the overall dependency and causality structure. Despite the high level of noise and the short time-series we verified that these networks are significant with all links statistically validated and with a structural organisation consistently reproduced across all networks.
In this manuscript, we investigate the adoption of blockchain for over-the-counter (OTC) electricity wholesale trading under the EU regulatory framework. Our analysis of the core legislation reveals six potential issues: (1) data immutability-related error correction, (2) personal data protection and immutability, (3) access to different data layers, (4) obligation and capacity to report, (5) identification of counterparties and (6) conflict of interest. These six issues were used as basis for a survey with experts in this field from industry and academia. The majority of our respondents indicated four major points: (i) reduction of transaction costs is the main expected benefit, (ii) the application of blockchain can be compliant with the current regulatory framework, (iii) a sandbox is the most welcome regulatory approach to reduce legal uncertainty, and (iv) the first use case to be commercially implemented is expected to be a P2P platform, ahead of a use case focused on post-trade processes. We believe that the results presented in this manuscript might serve as guidance for market participants aiming to enable the development of blockchain.
Blockchain is a disruptive technology that is normally used within financial applications, however it can be very beneficial also in certain robotic contexts, such as when an immutable register of events is required. Among the several properties of Blockchain that can be useful within robotic environments, we find not just immutability but also decentralization of the data, irreversibility, accessibility and non-repudiation. In this paper, we propose an architecture that uses blockchain as a ledger and smart-contract technology for robotic control by using external parties, Oracles, to process data. We show how to register events in a secure way, how it is possible to use smart-contracts to control robots and how to interface with external Artificial Intelligence algorithms for image analysis. The proposed architecture is modular and can be used in multiple contexts such as in manufacturing, network control, robot control, and others, since it is easy to integrate, adapt, maintain and extend to new domains.