A blockchain is an append-only linked-list of blocks, which is maintained at each participating node. Each block records a set of transactions and their associated metadata. Blockchain transactions act on the identical ledger data stored at each node. Blockchain was first perceived by Satoshi Nakamoto as a peer-to-peer digital-commodity (also known as crypto-currency) exchange system. Blockchains received traction due to their inherent property of immutability-once a block is accepted, it cannot be reverted.
Trust is the basis of any distributed, fault-tolerant, or secure system. A trust assumption specifies the failures that a system, such as a blockchain network, can tolerate and determines the conditions under which it operates correctly. In systems subject to Byzantine faults, the trust assumption is usually specified through sets of processes that may fail together. Trust has traditionally been symmetric, such that all processes in the system adhere to the same, global assumption about potential faults. Recently, asymmetric trust models have also been considered, especially in the context of blockchains, where every participant is free to choose who to trust. In both cases, it is an open question how to compose trust assumptions. Consider two or more systems, run by different and possibly disjoint sets of participants, with different assumptions about faults: how can they work together? This work answers this question for the first time and offers composition rules for symmetric and for asymmetric quorum systems. These rules are static and do not require interaction or agreement on the new trust assumption among the participants. Moreover, they ensure that if the original systems allow for running a particular protocol (guaranteeing consistency and availability), then so will the joint system. At the same time, the composed system tolerates as many faults as possible, subject to the underlying consistency and availability properties. Reaching consensus with asymmetric trust in the model of personal Byzantine quorum systems (Losa et al., DISC 2019) was shown to be impossible, if the trust assumptions of the processes diverge from each other. With asymmetric quorum systems, and by applying our composition rule, we show how consensus is actually possible, even with the combination of disjoint sets of processes.
Blockchains based on the celebrated Nakamoto consensus protocol have shown promise in several applications, including cryptocurrencies. However, these blockchains have inherent scalability limits caused by the protocol's consensus properties. In particular, the \emph{consistency} property demonstrates a tight trade-off between block production speed and the system's security in terms of resisting adversarial attacks. This paper proposes a novel method, Ironclad, that improves blockchain consistency bound by assigning a different weight to randomly selected blocks. We apply our method to the original Nakamoto protocol and rigorously prove that such a combination can improve the consistency bound significantly by analyzing the fundamental consensus properties. Such an improvement enables a much faster block production rate than the original Nakamoto protocol under the same security guarantee with the same proportion of malicious mining power (see Figure 1).
Cosimo Sguanci, Roberto Spatafora, Andrea Mario Vergani
Blockchain technology is affected by massive limitations in scalability with consequent repercussions on performance. This discussion aims at analyzing the state of the art of current available Layer II solutions to overcome these limitations, both focusing on theoretical and practical aspects and highlighting the main differences among the examined frameworks. The structure of the work is based on three major sections. In particular, the first one is an introductory part about the technology, the scalability issue and Layer II as a solution. The second section represents the core of the discussion and consists of three different subsections, each with a detailed examination of the respective solution (Lightning Network, Plasma, Rollups); the analysis of each solution is based on how it affects five key aspects of blockchain technology and Layer II: scalability, security, decentralization, privacy, fees and micropayments (the last two are analyzed together given their high correlation). Finally, the third section includes a tabular summary, followed by a detailed description of a use-case specifically thought for a practical evaluation of the presented frameworks. The results of the work met expectations: all solutions effectively contribute to increasing scalability. A crucial clarification is that none of the three dominates the others in all possible fields of application, and the consequences in adopting each, are different. Therefore, the choice depends on the application context, and a trade-off must be found between the aspects previously mentioned.
Minh Quang Nguyen, Dumitrel Loghin, Tien Tuan Anh Dinh
The rapid growth of blockchain systems leads to increasing interest in understanding and comparing blockchain performance at scale. In this paper, we focus on analyzing the performance of Hyperledger Fabric v1.1 - one of the most popular permissioned blockchain systems. Prior works have analyzed Hyperledger Fabric v0.6 in depth, but newer versions of the system undergo significant changes that warrant new analysis. Existing works on benchmarking the system are limited in their scope: some consider only small networks, others consider scalability of only parts of the system instead of the whole. We perform a comprehensive performance analysis of Hyperledger Fabric v1.1 at scale. We extend an existing benchmarking tool to conduct experiments over many servers while scaling all important components of the system. Our results demonstrate that Fabric v1.1's scalability bottlenecks lie in the communication overhead between the execution and ordering phase. Furthermore, we show that scaling the Kafka cluster that is used for the ordering phase does not affect the overall throughput.
We analyze Bitcoin mining from the perspective of a game and propose an optimal mining model that maximizes profits of pools and miners. The model is a two-stage Stackelberg game in which each stage forms a sub-game. In stage I, pools are the leaders who assign a computing power to be consumed by miners. In stage II, miners decide of their power consumption and distribution. They find themselves in a social dilemma in which they must choose between mining in solo, therefore prioritizing their individual preferences, and participating in a pool for the collective interest. The model relies on a pool protocol based on a simulated game in which the miners compete for the reward won by the pool. The solutions for the stage I sub-game and the simulated protocol game are unique and stable Nash equilibriums while the stage II sub-game leads to a stable cooperative equilibrium only when miners choose their strategies according to certain criteria. We conclude that the cooperative optimal mining model has the potential to favor Bitcoin decentralization and stability. Mainly, the social dilemma faced by miners together with the balance of incentives ensure a certain distribution of the network computing power between pools and solo miners, while equilibriums in the game solutions provide stability to the system.
Most self-service payment terminals require network connectivity for processing electronic payments. The necessity to maintain network connectivity increases costs, introduces cybersecurity risks, and significantly limits the number of places where the terminals can be installed. Leading payment service providers have proposed offline payment solutions that rely on algorithmically generated payment tokens. Existing payment token solutions, however, require complex mechanisms for authentication, transaction management, and most importantly, security risk management. In this paper, we present VolgaPay, a blockchain-based system that allows merchants to deploy secure offline payment terminal infrastructure that does not require collection and storage of any sensitive data. We design a novel payment protocol which mitigates security threats for all the participants of VolgaPay, such that the maximum loss from gaining full access to any component by an adversary incurs only a limited scope of harm. We achieve significant enhancements in security, operation efficiency, and cost reduction via a combination of polynomial multi-hash chain micropayment channels and blockchain grafting for off-chain channel state transition. We implement the VolgaPay payment system, and with thorough evaluation and security analysis, we demonstrate that VolgaPay is capable of delivering a fast, secure, and cost-efficient solution for offline payment terminals.
Ege Erdogan, Can Arda Aydin, Oznur Ozkasap, Waris Gill
As blockchain-based systems see wider adoption, it becomes increasingly critical to ensure their reliability, security, and efficiency. Running simulations is an effective method of gaining insights on the existing systems and analyzing potential improvements. However, many of the existing blockchain simulators have various shortcomings that yield them insufficient for a wide range of scenarios. In this demo paper, we present Zelig: our blockchain simulator designed with the main goals of customizability and extensibility. To the best of our knowledge, Zelig is the only blockchain simulator that enables simulating custom network topologies without modifying the simulator code. We explain our simulator design, validate via experimental analysis against the real-world Bitcoin network, and highlight potential use cases.
I Wayan Budi Sentana, Muhammad Ikram, Mohamed Ali Kaafar
We propose BlockJack, a system based on a distributed and tamper-proof consortium Blockchain that aims at blocking IP prefix hijacking in the Border Gateway Protocol (BGP). In essence, BlockJack provides synchronization among BlockChain and BGP network through interfaces ensuring operational independence and this approach preserving the legacy system and accommodates the impact of a race condition if the Blockchain process exceeds the BGP update interval. BlockJack is also resilient to dynamic routing path changes during the occurrence of the IP prefix hijacking in the routing tables. We implement BlockJack using Hyperledger Fabric Blockchain and Quagga software package and we perform initial sets of experiments to evaluate its efficacy. We evaluate the performance and resilience of BlockJack in various attack scenarios including single path attacks, multiple path attacks, and attacks from random sources in the random network topology. The Evaluation results show that BlockJack is able to handle multiple attacks caused by AS paths changes during a BGP prefix hijacking. In experiment settings with 50 random routers, BlockJack takes on average 0.08 seconds (with a standard deviation of 0.04 seconds) to block BGP prefix hijacking attacks. The test result showing that BlockJack conservative approach feasible to handle the IP Prefix hijacking in the Border Gateway Protocol.
Recently, a new generation of P2P systems capable of addressing data integrity and authenticity has emerged for the development of new applications for a "more" decentralized Internet, i.e., Distributed Ledger Technologies (DLT) and Decentralized File Systems (DFS). However, these technologies still have some unanswered issues, mostly related to data lookup and discovery. In this paper, first, we propose a Distributed Hash Table (DHT) system that efficiently manages decentralized keyword-based queries executed on data stored in DFS. Through a hypercube logical layout, queries are efficiently routed among the network, where each node is responsible for a specific keywords set and the related contents. Second, we provide a framework for the governance of the above network, based on a Decentralized Autonomous Organization (DAO) implementation. We show how the use of smart contracts enables organizational decision making and rewards for nodes that have actively contributed to the DHT. Finally, we provide experimental validation of an implementation of our proposal, where the execution of the same protocol for different logical nodes of the hypercube allows us to evaluate the efficiency of communication within the network.
In distributed environments, such as distributed ledgers technologies and other peer-to-peer architectures, communication represents a crucial topic. The ability to efficiently disseminate contents is strongly influenced by the type of system architecture, the protocol used to spread such contents over the network and the actual dynamicity of the communication links (i.e. static vs. temporal nets). In particular, the dissemination strategies either focus on achieving an optimal coverage, minimizing the network traffic or providing assurances on anonymity (that is a fundamental requirement of many cryptocurrencies). In this work, the behaviour of multiple dissemination protocols is discussed and studied through simulation. The performance evaluation has been carried out on temporal networks with the help of LUNES-temporal, a discrete event simulator that allows to test algorithms running on a distributed environment. The experiments show that some gossip protocols allow to either save a considerable number of messages or to provide better anonymity guarantees, at the cost of a little lower coverage achieved and/or a little increase of the delivery time.
Jianyu Niu, Fangyu Gai, Mohammad M. Jalalzai, Chen Feng
HotStuff is a state-of-the-art Byzantine fault-tolerant consensus protocol. It can be pipelined to build large-scale blockchains. One of its variants called LibraBFT is adopted in Facebook's Libra blockchain. Although it is well known that pipelined HotStuff is secure against up to $1/3$ of Byzantine nodes, its performance in terms of throughput and delay is still under-explored. In this paper, we develop a multi-metric evaluation framework to quantitatively analyze pipelined \mbox{HotStuff's performance} with respect to its chain growth rate, chain quality, and latency. We then propose two attack strategies and evaluate their effects on the performance of pipelined HotStuff. Our analysis shows that the chain growth rate (resp, chain quality) of pipelined HotStuff under our attacks can drop to as low as 4/9 (resp, 12/17) of that without attacks when $1/3$ nodes are Byzantine. As another application, we use our framework to evaluate certain engineering optimizations adopted by LibraBFT. We find that these optimizations make the system more vulnerable to our attacks than the original pipelined HotStuff. Finally, we provide two countermeasures to thwart these attacks. We hope that our studies can shed light on the rigorous understanding of the state-of-the-art pipelined HotStuff protocol as well as its variants.
We argue that there is a hierarchy of levels describing to that particular level relevant features of reality behind the content and behavior of blockchain and smart contracts in their realistic deployment. Choice, design, audit and legal control of these systems could be more informed, easier and raised to a higher level, if research on foundations of these descriptions develops and sets the formalisms, tools and standards for such descriptions.
Payment channel is a protocol which allows cryptocurrency users to route multiple transactions through network without committing them to the main blockchain network (mainnet). This ability makes them the most prominent solution to blockchains' scalability problem. Each modification of payment channels requires a transaction on the mainnet and therefore, big transaction fees. In this paper, we assume that a set of payment transactions are given (batch or online) and we study the problem of scheduling modificiations on payment channels to route all of the transactions with minimum modification cost. We investigate two cost models for aforementioned problem: the step cost function in which every channel modification has a constant cost and the linear cost function in which modification costs are proportional to the amount of change. For the step cost function model, we prove impossibility results for both batch and online case. Moreover, some heuristic methods for the batch case are presented and compared. For the linear cost we propose a polynomial time algorithm using linear programming for the batch case.
Mohd Anuar Mat Isa, Muzaffar Hamzah, Daimler Benz Alebaba
A variety of mobile devices and applications have spread the usability of blockchain solutions to over 5.27 billion unique mobile phone users. The rising of Bitcoin price up to USD 50,000 in March 2021 has made many blockchain mobile wallets and smart contracts DApps popular for current and future investment of cryptocurrency and digital-asset managements. To understand the trend, this chapter will present the design and implementation of mobile blockchain DApps using Android Studio together with Ethereum smart contract as the digital-asset management tool. Java Android and Ethereum Web3-Java APIs will be demonstrated as a practical deployment of the mobile DApps. The logic and decision-making of the mobile DApps will be demonstrated and coded as a smart contract. The source codes of the mobile DApps and smart-contract were published in Github as open-source codes for those who are interested to build and run the project.
Oliver Stengele, Markus Raiber, Jörn Müller‐Quade, Hannes Hartenstein
We address the Threshold Information Disclosure (TID) problem on Ethereum: An arbitrary number of users commit to the scheduled disclosure of their individual messages recorded on the Ethereum blockchain if and only if all such messages are disclosed. Before a disclosure, only the original sender of each message should know its contents. To accomplish this, we task a small council with executing a distributed generation and threshold sharing of an asymmetric key pair. The public key can be used to encrypt messages which only become readable once the threshold-shared decryption key is reconstructed at a predefined point in time and recorded on-chain. With blockchains like Ethereum, it is possible to coordinate such procedures and attach economic stakes to the actions of participating individuals. In this paper, we present ETHTID, an Ethereum smart contract application to coordinate Threshold Information Disclosure. We base our implementation on ETHDKG [1], a smart contract application for distributed key generation and threshold sharing, and adapt it to fit our differing use case as well as add functionality to oversee a scheduled reconstruction of the decryption key. For our main cost saving optimisation, we show that the security of the underlying cryptographic scheme is maintained. We evaluate how the execution costs depend on the size of the council and the threshold and show that the presented protocol is deployable on Ethereum with a council of more than 200 members with gas savings of 20-40% compared to ETHDKG.
Climate change and global warming are the significant challenges of the new century. A viable solution to mitigate greenhouse gas emissions is via a globally incentivized market mechanism proposed in the Kyoto protocol. In this view, the carbon dioxide (or other greenhouse gases) emission is considered a commodity, forming a carbon trading system. There have been attempts in developing this idea in the past decade with limited success. The main challenges of current systems are fragmented implementations, lack of transparency leading to over-crediting and double-spending, and substantial transaction costs that transfer wealth to brokers and agents. We aim to create a Carbon Credit Ecosystem using smart contracts that operate in conjunction with blockchain technology in order to bring more transparency, accessibility, liquidity, and standardization to carbon markets. This ecosystem includes a tokenization mechanism to securely digitize carbon credits with clear minting and burning protocols, a transparent mechanism for distribution of tokens, a free automated market maker for trading the carbon tokens, and mechanisms to engage all stakeholders, including the energy industry, project verifiers, liquidity providers, NGOs, concerned citizens, and governments. This approach could be used in a variety of other credit/trading systems.
Public blockchains have spurred the growing popularity of decentralized transactions and smart contracts, especially on the financial market. However, public blockchains exhibit their limitations on the transaction throughput, storage availability, and compute capacity. To avoid transaction gridlock, public blockchains impose large fees and per-block resource limits, making it difficult to accommodate the ever-growing high transaction demand. Previous research endeavors to improve the scalability and performance of blockchain through various technologies, such as side-chaining, sharding, secured off-chain computation, communication network optimizations, and efficient consensus protocols. However, these approaches have not attained a widespread adoption due to their inability in delivering a cloud-like performance, in terms of the scalability in transaction throughput, storage, and compute capacity. In this work, we determine that the major obstacle to public blockchain scalability is their underlying unstructured P2P networks. We further show that a centralized network can support the deployment of decentralized smart contracts. We propose a novel approach for achieving scalable decentralization: instead of trying to make blockchain scalable, we deliver decentralization to already scalable cloud by using an Ethereum smart contract. We introduce Blockumulus, a framework that can deploy decentralized cloud smart contract environments using a novel technique called overlay consensus. Through experiments, we demonstrate that Blockumulus is scalable in all three dimensions: computation, data storage, and transaction throughput. Besides eliminating the current code execution and storage restrictions, Blockumulus delivers a transaction latency between 2 and 5 seconds under normal load. Moreover, the stress test of our prototype reveals the ability to execute 20,000 simultaneous transactions under 26 seconds, which is on par with the average throughput of worldwide credit card transactions.
The financial industry is a pioneer in Blockchain technology. One of the most popular platforms in Token-based banking is the flexible Stellar platform. This platform is open-source, and today, its wide range of features makes it possible for many countries and companies to use it in cryptocurrency and Token-based modern banking. This network charges a fee for each transaction. As well, a percentage of the net amount is generated as the inflation rate of the network due to the increased number of tokens. These fees and inflationary amounts are aggregated into a general account and ultimately distributed among members of the network on a collective vote basis. In this mechanism, network users select an account as the destination for which they wish to transfer assets using their user interface, which is generally a wallet. This account could be the account of charities that need this help. It is then determined the target distribution network based on the voting results of all members. One of the challenges in this network is the purposeful and fair distribution of these funds between accounts. In this paper, the first step is a complete infrastructure of a Stellar financial network that will consist of three network-based segments of the core network, off-chain server, and wallet interface. In the second step, a context-aware recommendation system will be explored and implemented as a solution for the purposeful management of payroll account selection. The results of this study concerning the importance of the purposeful division of collective assets and showing a context-aware recommendation system as a solution to improve the process of stellar users' participation in the voting process by effectively helping them in choosing an eligible destination
Blockchain technology is among the fastest-growing technologies in the world today. It has been adopted in diverse areas but mostly in financial systems, such as Bitcoin cryptocurrency. Therefore, it is a niche that has attracted interest from researchers from various fields, including computer science. Other areas where Blockchain is being embraced are the Smart Grid and Internet of Things (IoT) technologies, among others. While it is all good and improving many areas of applications, Blockchain still has some shortcomings. For example, it is not designed for high scalability when accommodating normal transactions. On the other hand, a parallel technology that has diverse applications in distributed networks better known as edge computing has emerged. Its main advantage is that it increases the speed of pf processes within those networks. However, like Blockchain, edge computing has its shortcomings. Its security systems and management systems have been found to be wanting. Hence the idea to integrate the two technologies and take advantage of their strengths. A blend of the two would lead to advanced network servers, huge data storage, and heightened security in transactions. However, this integration will best happen when some measures are taken. For example, there is a need to address scalability, resource management satisfactorily, and the security of the systems. To solve the integration problem, a decentralized Blockchain-based model of Edge computing is proposed in this paper.
Leon Witt, Usama Zafar, KuoYeh Shen, Felix Sattler · 6 authors
The recent advent of various forms of Federated Knowledge Distillation (FD) paves the way for a new generation of robust and communication-efficient Federated Learning (FL), where mere soft-labels are aggregated, rather than whole gradients of Deep Neural Networks (DNN) as done in previous FL schemes. This security-per-design approach in combination with increasingly performant Internet of Things (IoT) and mobile devices opens up a new realm of possibilities to utilize private data from industries as well as from individuals as input for artificial intelligence model training. Yet in previous FL systems, lack of trust due to the imbalance of power between workers and a central authority, the assumption of altruistic worker participation and the inability to correctly measure and compare contributions of workers hinder this technology from scaling beyond small groups of already entrusted entities towards mass adoption. This work aims to mitigate the aforementioned issues by introducing a novel decentralized federated learning framework where heavily compressed 1-bit soft-labels, resembling 1-hot label predictions, are aggregated on a smart contract. In a context where workers' contributions are now easily comparable, we modify the Peer Truth Serum for Crowdsourcing mechanism (PTSC) for FD to reward honest participation based on peer consistency in an incentive compatible fashion. Due to heavy reductions of both computational complexity and storage, our framework is a fully on-blockchain FL system that is feasible on simple smart contracts and therefore blockchain agnostic. We experimentally test our new framework and validate its theoretical properties.
Rachit Agarwal, Tanmay Thapliyal, Sandeep K. Shukla
Smart Contracts (SCs) in Ethereum can automate tasks and provide different functionalities to a user. Such automation is enabled by the `Turing-complete' nature of the programming language (Solidity) in which SCs are written. This also opens up different vulnerabilities and bugs in SCs that malicious actors exploit to carry out malicious or illegal activities on the cryptocurrency platform. In this work, we study the correlation between malicious activities and the vulnerabilities present in SCs and find that some malicious activities are correlated with certain types of vulnerabilities. We then develop and study the feasibility of a scoring mechanism that corresponds to the severity of the vulnerabilities present in SCs to determine if it is a relevant feature to identify suspicious SCs. We analyze the utility of severity score towards detection of suspicious SCs using unsupervised machine learning (ML) algorithms across different temporal granularities and identify behavioral changes. In our experiments with on-chain SCs, we were able to find a total of 1094 benign SCs across different granularities which behave similar to malicious SCs, with the inclusion of the smart contract vulnerability scores in the feature set.
Xu Wang, Wei Ni, Xuan F. Zha, Guangsheng Yu · 7 authors
As distributed ledgers, blockchains run consensus protocols which trade capacity for consistency, especially in non-ideal networks with incomplete connectivity and erroneous links. Existing studies on the tradeoff between capacity and consistency are only qualitative or rely on specific assumptions. This paper presents discrete-time Markov chain models to quantify the capacity of Proof-of-Work based public blockchains in non-ideal networks. The comprehensive model is collapsed to be ergodic under the eventual consistency of blockchains, achieving tractability and efficient evaluations of blockchain capacity. A closed-form expression for the capacity is derived in the case of two miners. Another important aspect is that we extend the ergodic model to analyze the capacity under strong consistency, evaluating the robustness of blockchains against double-spending attacks. Validated by simulations, the proposed models are accurate and reveal the effect of link quality and the distribution of mining rates on blockchain capacity and the ratio of stale blocks.
A survey is given of approaches to the problem of distributed consensus, focusing particularly on methods based on cellular automata and related systems. A variety of new results are given, as well as a history of the field and an extensive bibliography. Distributed consensus is of current relevance in a new generation of blockchain-related systems.