Roman Mühlberger, Stefan Bachhofner, Eduardo Castelló Ferrer, Claudio Di Ciccio · 7 authors
Blockchain has evolved into a platform for decentralized applications, with beneficial properties like high integrity, transparency, and resilience against censorship and tampering. However, blockchains are closed-world systems which do not have access to external state. To overcome this limitation, oracles have been introduced in various forms and for different purposes. However so far common oracle best practices have not been dissected, classified, and studied in their fundamental aspects. In this paper, we address this gap by studying foundational blockchain oracle patterns in two foundational dimensions characterising the oracles: (i) the data flow direction, i.e., inbound and outbound data flow, from the viewpoint of the blockchain; and (ii) the initiator of the data flow, i.e., whether it is push or pull-based communication. We provide a structured description of the four patterns in detail, and discuss an implementation of these patterns based on use cases. On this basis we conduct a quantitative analysis, which results in the insight that the four different patterns are characterized by distinct performance and costs profiles.
Covenants are linguistic primitives that extend the Bitcoin script language, allowing transactions to constrain the scripts of the redeeming ones. Advocated as a way of improving the expressiveness of Bitcoin contracts while preserving the simplicity of the UTXO design, various forms of covenants have been proposed over the years. A common drawback of the existing descriptions is the lack of formalization, making it difficult to reason about properties and supported use cases. In this paper we propose a formal model of covenants, which can be implemented with minor modifications to Bitcoin. We use our model to specify some complex Bitcoin contracts, and we discuss how to exploit covenants to design high-level language primitives for Bitcoin contracts.
Xueping Liang, Sachin Shetty, Peter Foytik, Deepak K. Tosh
Distributed Ledger Technology (DLT) utilizes an architecture that can host a large number of nodes without pre-established trust to provide decentralized services. The blockchain is the most widely used architecture of distributed ledger, where transactions across the whole network are visible to all participants in a chain to prevent tampering. However, transactions may contain sensitive information such as business contract. To secure the system and protect user privacy, we propose a multi-channel architecture that leverages Intel Software Guard Extensions (SGX). We illustrate how SGX capabilities help to defend against attacks on distributed ledgers, by way of SGX enforcement on the participating machines. We adopt the design and implementation of a two layer architecture for securing the blockchain mining process and enhancing the transaction privacy. The security analysis and performance evaluation show that the design and protocols are capable of protecting privacy, defending against adversarial attacks and scalable.
Distributed ledger technology was expected to spark a technical revolution similar to the internet revolution. After the release of Bitcoin in 2008, many developments have significantly increased the performance of distributed ledger technology. Nevertheless, the first truly scalable ledger has yet to be deployed. All of them have issues with scaling in either the throughput, the number of nodes which can validate transaction or both. The concept behind a distributed ledger is that the integrity of the ledger is a shared responsibility. However, as soon as new technology emerges, also misuse surfaces, especially if there are financial gains involved. The general solution, to prevent such abuse, in distributed ledger technology is through the use of global consensus. If the majority of a network is honest, and we require a majority vote on the validity of a transaction, no malicious transactions will succeed. A downside of requiring a majority vote is that every node eligible to vote must contain full knowledge on all previous transactions. This work argues that the requirement of global consensus is a major limiting factor when it comes to the scalability of current ledgers. The goal of this work is to design a scalable distributed ledger whose security does not rely on global consensus. It proposes a novel algorithm that guarantees security, even under adversarial attack, by up to a third of the network exhibiting byzantine behavior. It does so using Trustchain, a pair-wise ledger designed by the Delft University of Technology, and `Fair Witness Selection Protocol', a newly designed publicly verifiable witness selection algorithm with an indicated message and communication complexity of $O(log^\\star(n))$. A mathematical lower-bound is given on the security level of the algorithm, and the security is reduced to the security of the underlying hash function. Several experiments were executed on the DAS-5 supercomputer to confirm the scalability of this work. These experiments show that the throughput of the network scales linearly, and has been tested up to 2500 nodes (simultaneously acting as validators and clients). To the best of the author's knowledge, it is the only ledger that has no theoretical limits on the number of clients, number of validators, or throughput. A peak-throughput of 7025 tx/s has been observed at a network size of 280 nodes. Furthermore, the total transaction time remained roughly constant at about 15 milliseconds regardless of the network size.
D.S. Popović, C. Avis, M. Byrne, Chong-Soo Cheung · 10 authors
Abstract Insurance industry practitioners have deep knowledge of their industry, but there is a lack of a simple-to-understand, practical blueprint on applying distributed ledger technology solutions, including blockchain. This paper provides a practical guide for actuaries, risk professionals, insurance companies and their Boards on blockchain, including an education piece to provide an understanding of the technology. Examples of real-world applications and use cases in insurance are provided to illustrate the capability of the technology. The current risks and challenges in adopting the technology are also considered. Finally, a checklist of issues to consider in adopting a blockchain solution for insurance business problems is provided.
Decentralized techniques are becoming crucial and ubiquitous with the rapid advancement of distributed ledger technologies such as the blockchain. Numerous decentralized systems have been developed to address security and privacy issues with great dependability and reliability via these techniques. Meanwhile, formalization and verification of the decentralized systems is the key to ensuring correctness of the design and security properties of the implementation. In this paper, we propose a novel method of formalizing and verifying decentralized systems with a kind of extended concurrent separation logic. Our logic extends the standard concurrent separation logic with new features including communication encapsulation, environment perception, and node-level reasoning, which enhances modularity and expressiveness. Besides, we develop our logic with unitarity and compatibility to facilitate implementation. Furthermore, we demonstrate the effectiveness and versatility of our method by applying our logic to formalize and verify critical techniques in decentralized systems including the consensus mechanism and the smart contract.
Distributed ledger technology is envisioned as one of the cornerstones of promising solutions for building the next generation of critical applications.However, there is still quite a bit of confusion and hype around the real security guarantees this technology offers.This is especially due to the fact that for the vast majority of existing blockchain-based consensus protocols it is really hard to find sufficiently detailed documentation that fully captures their behavior.A number of recent papers have formalized the behavior of Bitcoin-like protocols in order to rigorously study the security and privacy properties of their underlying structure, but surprisingly very little work has been devoted to the formalization of distributed ledger systems using BFTlike approaches.In this work, we focus on XRP Ledger, better known as Ripple, and take the first steps towards the complete formalization of its consensus protocol.To this end, we have investigated all the existing documentation and analyzed its source code.We present a formal description of its consensus protocol for every step.Furthermore, we provide an accurate view of its security guarantees in terms of safety and liveness and show how to increase the desired tolerance by changing the value of specific protocol parameters.
Distributed ledger technology (DLT) stands to benefit industries such as financial services with transparency and censorship resistance. DLT systems need to be scalable to handle mass user adoption. Mass user adoption is required to demonstrate the true value of DLT. This dissertation first analyses scalability in ethereum and EOS. Currently, ethereum 1.0 uses proof of work (PoW) and handles only 14 transactions per second (tps) compared to Visa's peak 47 000 tps. Ethereum 2.0, known as Serenity, introduces sharding, proof of stake (Casper), plasma and state channels in and effort to scale the system. EOS uses a delegated proof of stake (DPoS) protocol, where 21 super-nodes, termed ‘block producers' (BPs), facilitate consensus, bringing about significant scalability improvements (4000 tps). The trade-off is decentralisation. EOS is not sufficiently decentralised because the BPs yield significant power, but are not diverse. This dissertation conducts an empirical analysis using unsupervised machine learning to show that there is a high probability collusion is occurring between certain BPs. It then suggests possible protocol alterations such as inverse vote weighting that could curb adverse voting behaviour in DPoS. It further analyses whether universities are suitable BP's before mapping out required steps for universities to become block producers (leading to improved decentralisation in EOS)
Myoungwon Oh, Sujin Ha, Jin Hyuk Yoon, Kang‐Won Lee · 6 authors
Distributed ledger technology faces scalability problems due to a long commit time despite recent successes for cryptocurrency. Small group consensus studies have improved this scalability of distributed ledgers. However, they still have problems of the consensus process itself. For example, most blockchain systems perform serialized block proposal and consensus processing, guarantee the finality with high overhead, and handle byzantine nodes inefficiently. To address these problems, we propose a consensus system, named graph learning byzantine fault tolerance (GL BFT), which offers high parallelism and low latency under Byzantine fault. To do this, we enable a parallel pipelined agreement by separating the block proposal and the consensus process. Second, we devise two techniques of merging blocks and commit learning to guarantee the finality with little overhead. Finally, we present a path learning approach which chooses optimal paths to handle Byzantine fault. The proposed GL BFT can achieve instant finality with low message overhead among a small group of nodes even if Byzantine nodes exit. Also, we evaluate its performance on an open source blockchain protocol. Experimental results show that our design reduces data traffic required by the consensus up to 30%, one transaction is finalized within a few seconds, and optimal performance is maintained.
Bitcoin users can offer fees to the miners who record transactions on the blockchain. We document the blockchain rarely runs at capacity, even though there appears to be excess demand and higher fee orders are not always prioritized. We show this is inconsistent with competitive mining, but is consistent with miners exercising market power. If users believe that only high fee transactions will be executed expeditiously then we show how strategic capacity management can be used to increase fee revenue. Using a novel data set, we present evidence consistent with strategic capacity management. We show that mining pools facilitate collusion, and estimate that they have extracted least 300 million USD a year in excess fees by making processing capacity artificially scarce.
Distributed Ledger Technology (DLT) enables data storage in a decentralized manner among collaborating parties. The software architecture of such solutions encompasses models placed in the relevant architectural views. A lot of research is devoted to smart contracts and consensus algorithms, which are realized by distributed applications and can be positioned within the Logical view. However, we see the need to provide modeling support for the Deployment view of distributed ledger solutions. Especially since the chosen DLT framework has a significant impact on implementation and deployment. Besides, consistency between models and configuration deployment scripts should be ensured. So, we have applied Model-Driven Engineering (MDE) that allows on the transformation of models into more detailed models, source code, or tests. We have proposed Unified Modeling Language (UML) stereotypes and tagged values for distributed ledger deployment modeling and placed them in the UML Profile for Distributed Ledger Deployment. We have also designed the UML2Deployment model-to-code transformation for the R3 Corda DLT framework. A UML Deployment model is the source whereas a Gradle Groovy deployment script is the target of the transformation. We have provided the complete solution by incorporating the transformation into the Visual Paradigm modeling tool. Furthermore, we have designed a dedicated plug-in to validate generated deployment scripts. In the paper, we have shown how to design transformation for generating deployment scripts for the R3 Corda DLT framework with the ability to switch to another one.
We present the main concepts, components, and usage of GASOL, a Gas AnalysiS and Optimization tooL for Ethereum smart contracts. GASOL offers a wide variety of cost models that allow inferring the gas consumption associated to selected types of EVM instructions and/or inferring the number of times that such types of bytecode instructions are executed. Among others, we have cost models to measure only storage opcodes, to measure a selected family of gas-consumption opcodes following the Ethereum's classification, to estimate the cost of a selected program line, etc. After choosing the desired cost model and the function of interest, GASOL returns to the user an upper bound of the cost for this function. As the gas consumption is often dominated by the instructions that access the storage, GASOL uses the gas analysis to detect under-optimized storage patterns, and includes an (optional) automatic optimization of the selected function. Our tool can be used within an Eclipse plugin for Solidity which displays the gas and instructions bounds and, when applicable, the gas-optimized Solidity function.
The blockchain data structure maintained via the longest-chain rule—popularized by Bitcoin—is a powerful algorithmic tool for consensus algorithms. Such algorithms achieve consistency for blocks in the chain as a function of their depth from the end of the chain. While the analysis of Bitcoin guarantees consistency with error 2−k for blocks of depth O(k), the state-of-the-art of proof-of-stake (PoS) blockchains suffers from a quadratic dependence on k: these protocols, exemplified by Ouroboros (Crypto 2017), Ouroboros Praos (Eurocrypt 2018) and Sleepy Consensus (Asiacrypt 2017), can only establish that depth Θ(k2) is sufficient. Whether this quadratic gap is an intrinsic limitation of PoS—due to issues such as the nothing-at-stake problem—has been an urgent open question, as deployed PoS blockchains further rely on consistency for protocol correctnes. We give an axiomatic theory of blockchain dynamics that permits rigorous reasoning about the longest-chain rule and achieve, in broad generality, Θ(k) dependence on depth in order to achieve consistency error 2−k In particular, for the first time we show that PoS protocols can match proof-of-work protocols for linear consistency. We analyze the associated stochastic process, give a recursive relation for the critical functionals of this process, and derive tail bounds in both i.i.d. and martingale settings via associated generating functions.
A blockchain is a Distributed Ledger Technology that has been defined as a “distributed, shared, encrypted database that serves as an irreversible and incorruptible repository of information. Blockchain can be defined as a peer-to-peer distributed ledger that is cryptographically secure, append-only, immutable and updatable only via consensus or agreement among peers. In blockchain platforms, each transaction in the public ledger is verified by consensus of the majority of the system participants in a transparent and secure way. The consensus algorithm refers to the process of attaining an unified agreement on the state of the network in a decentralized way and to facilitate the verification and validation of information being added to the blockchain. This paper aims at providing a comparison between most of the recent consensus algorithms regarding the scalability of the algorithm; the type of blockchain, node identity, the performance of the algorithm (in terms of throughput & latency) and Adversial Tolerance and to deliver a solid basis for discussions about current statistics. In this research, we also presented a new category of the Blockchain consensus algorithms, which consist of three groups as follows; the proof based on Hardware, the proof based on stake, and the proof based on voting.
There are many consensus algorithms that exist in parallel computing that involve multiple computing units like virtual machines which make use of available resources and arrive at a single agreeable state for the combined system. This is done on the basis of voting which itself branches into several arrangements like voting, functions of central tendencies, weighted functions of central tendencies etc. Some applications that consensus algorithms try to cover are: deciding on transaction operations (read, write, commit); deciding on node leaders of a system; maintaining replicas in the state of a machine (also called a state machine) and creating consistency between them. Some common algorithms of this type are Proof of Work algorithm (PoW), the practical Byzantine fault tolerance algorithm (PBFT), the proof-of-stake algorithm (PoS) and the delegated proof-of-stake algorithm (DPoS), Paxos algorithm and the Raft consensus algorithm.
Cryptocurrency networks, such as Bitcoin, have emerged as a distributed alternative to traditional centralized financial transaction networks. However, there are major challenges in scaling up the throughput of such networks. Lightning network and Spider network are alternates that build bidirectional payment channels on top of cryptocurrency networks using smart contracts, to enable fast transactions that bypass the Blockchain. In this article, we study the problem of routing transactions in such a payment processing network. We first propose a Stochastic model to study such a system, as opposed to a fluid model that is studied in the literature. Each link in such a model is a two-sided queue, and unlike classical queues, such queues are not stable unless there is an external control. We propose a notion of stability for the payment processing network consisting of such two-sided queues using the notion of on-chain rebalancing. We then characterize the capacity region and propose a throughput optimal algorithm that stabilizes the system under any load within the capacity region. The stochastic model enables us to study closed-loop policies, which typically have better queuing/delay performance than the open-loop policies (or static split rules) studied in the literature. We investigate this through simulations.
The goal of this article is to extend the ideas concerning Bracha-Toueg asynchronous Byzantine Fault Tolerant consensus algorithm and Baird's Hashgraph consensus. We propose a family of atomic broadcast algorithms, which Hashgraph consensus is closely related to. We also do preliminary comparative algorithm speed analysis which shows that some members of the family seriously outperform Hashgraph consensus. These algorithms can also be readily used as a base of proof-of-stake consensuses. In appendix we provide an extension of Hashgraph gossip protocol, which efficiently handles byzantine fault information exchange between nodes.
Michael Neuder, Daniel J. Moroz, Rithvik Rao, David C. Parkes
Proof-of-Stake consensus protocols give rise to complex modeling challenges. We analyze the Babylon update (October 2019) to the Proof-of-Stake protocol on the Tezos blockchain, and demonstrate that, under certain conditions, rational participants are incentivized to behave dishonestly. In doing so, we provide a theoretical analysis of the feasibility and profitability of a block stealing attack that we call selfish endorsing, a concrete instance of an attack previously only theoretically considered. We propose and analyze a simple change to the Tezos protocol which significantly reduces the (already small) profitability of this dishonest behavior, and introduce a new delay and reward scheme that is provably secure against length-1 and length-2 selfish endorsing attacks. Our framework provides a template for analyzing other Proof-of-Stake protocols for the possibility of selfish behavior.
Vero Estrada-Galiñanes, Racin Nygaard, Viktor Trón, Rodrigo Q. Saramago · 6 authors
Blockchain is the driving force behind a myriad of decentralized applications (dapps) that promise to transform the Internet. The next generation Internet, or web3, introduces a "universal state layer" to store data in p2p networks. Swarm, a native layer of the Ethereum web3 stack, aims at providing redundant storage for dapp code, data, as well as, blockchain and state data. Based on a diploma verification dapp use case, we share insights on the role of redundancy strategies in designing a reliable storage layer. Our proof-of-concept improves Swarm's resilience to failures by balancing repairs and storage, with a slightly added latency.
Óscar Lage, Santiago de Diego, Borja Urkizu, Eneko Gómez · 5 authors
Blockchain has been widely known thanks to Bitcoin and the cryptocurrencies. In this chapter, we analyze different aspects that relate to the application of blockchain with techniques commonly used in the field of cybersecurity. Beginning by introducing the use of blockchain technology as a secure infrastructure, the document delves into how blockchain can be useful to achieve several security requirements, common to most applications. The document has been focused on some specific cybersecurity disciplines to maintain simplicity: backup and recovery, threat intelligence and content delivery networks. As illustrated, some projects and initiatives are in the process of joining these two fields to provide solutions to existing problems.
Distributed consensus mechanisms have been widely researched and made popular with a number of blockchain-based token applications, such as Bitcoin, and Ethereum. Although these general-purpose platforms have matured for scale and security, they are designed for human incentive and continue to require currency reward and contract functions that are not requisite in machine communications. Redes Chain is a custom designed blockchain, built to support fully decentralized self-organization in wireless networks-without a cryptocurrency or contract dependency.