Off-chain transaction networks can mitigate the scalability issues of today's trustless electronic cash systems such as Bitcoin. However, these peer-to-peer networks also introduce a new attack surface which is not well-understood today. This paper identifies and analyzes, a novel Denial-of-Service attack which is based on route hijacking, i.e., which exploits the way transactions are routed and executed along the created channels of the network. This attack is conceptually interesting as even a limited attacker that manipulates the topology through the creation of new channels can navigate tradeoffs related to the way it attacks the network. Furthermore, the attack also highlights a fundamental design tradeoff for the defender (who determines its own routes): to become less predictable and hence secure, a rational node has to pay higher fees to nodes that forward its payments. We find that the three most common implementations for payment channels in Bitcoin (lnd, C-lightning, Eclair) approach routing differently. We begin by surveying the current state of the Lightning network and explore the routes chosen by these implementations. We find that in the current network nearly 60\% of all routes pass through only five nodes, while 80\% go through only 10 nodes. Thus, a relatively small number of colluding nodes can deny service to a large fraction of the network. We then turn to study an external attacker who creates links to the network and draws more routes through its nodes by asking for lower fees. We find that just five new links are enough to draw the majority (65\% - 75\%) of the traffic regardless of the implementation being used. The cost of creating these links is very low. We discuss the differences between implementations and eventually derive our own suggested routing policy, which is based on a novel combination of existing approaches.
Shivam Saxena, Hany Farag, Hjalmar Turesson, Henry M. Kim
Transactive Energy Systems (TES) are modern mechanisms in electric power systems that allow disparate control agents to utilize distributed generation units (DGs) to engage in energy transactions and provide ancillary services to the grid. Although voltage regulation is a crucial ancillary service within active distribution networks (ADNs), previous work has not adequately explored how this service can be offered in terms of its incentivization, contract auditability and enforcement. Blockchain technology shows promise in being a key enabler of TES, allowing agents to engage in trustless, persistent transactions that are both enforceable and auditable. To that end, this paper proposes a blockchain based TES that enables agents to receive incentives for providing voltage regulation services by i) maintaining an auditable reputation rating for each agent that is increased proportionately with each mitigation of a voltage violation, ii) utilizing smart contracts to enforce the validity of each transaction and penalize reputation ratings in case of a mitigation failure and iii) automating the negotiation and bidding of agent services by implementing the contract net protocol (CNP) as a smart contract. Experimental results on both simulated and real-world ADNs are executed to demonstrate the efficacy of the proposed system.
Ilya Afanasyev, Alexander Kolotov, Ruslan Rezin, Konstantin Danilov · 13 authors
Decentralization, immutability and transparency make of Blockchain one of the most innovative technology of recent years. This paper presents an overview of solutions based on Blockchain technology for multi-agent robotic systems, and provide an analysis and classification of this emerging field. The reasons for implementing Blockchain in a multi-robot network may be to increase the interaction efficiency between agents by providing more trusted information exchange, reaching a consensus in trustless conditions, assessing robot productivity or detecting performance problems, identifying intruders, allocating plans and tasks, deploying distributed solutions and joint missions. Blockchain-based applications are discussed to demonstrate how distributed ledger can be used to extend the number of research platforms and libraries for multi-agent robotic systems.
Cryptocurrencies and blockchain networks have attracted tremendous attention from their volatile price movements and the promise of decentralization. However, most projects run on business narratives with no way to test and verify their assumptions and promises about the future. The complex nature of system dynamics within networked economies has rendered it difficult to reason about the growth and evolution of these networks. This paper drew concepts from differential games, classical control engineering, and stochastic dynamical system to come up with a framework and example to model, simulate, and engineer networked token economies. A model on a generalized token economy is proposed where miners provide service to a platform in exchange for a cryptocurrency and users consume service from the platform. Simulations of this model allow us to observe outcomes of complex dynamics and reason about the evolution of the system. Speculative price movements and engineered block rewards were then experimented to observe their impact on system dynamics and network-level goals. The model presented is necessarily limited so we conclude by exploring those limitations and outlining future research directions.
Tin Leelavimolsilp, Long Tran-Thanh, Sebastian Stein, Viet Hung Nguyen
Proof-of-Work blockchain, despite its numerous benefits, is still not an entirely secure technology due to the existence of Selfish Mining (SM) strategies that can disrupt the system and its mining economy. While the effect of SM has been studied mostly in a two-miners scenario, it has not been investigated in a more practical context where there are multiple malicious miners individually performing SM. To fill this gap, we carry out an empirical study that separately accounts for different numbers of SM miners (who always perform SM) and strategic miners (who choose either SM or Nakamoto's mining protocol depending on which maximises their individual mining reward). Our result shows that SM is generally more effective as the number of SM miners increases, however its effectiveness does not vary in the presence of a large number of strategic miners. Under specific mining power distributions, we also demonstrate that multiple miners can perform SM and simultaneously gain higher mining rewards than they should. Surprisingly, we also show that the more strategic miners there are, the more robust the systems become. Since blockchain miners should naturally be seen as self-interested strategic miners, our findings encourage blockchain system developers and engineers to attract as many miners as possible to prevent SM and similar behaviour.
Tarun Chitra, Monica Quaintance, Stuart Haber, Will Martino
While many distributed consensus protocols provide robust liveness and consistency guarantees under the presence of malicious actors, quantitative estimates of how economic incentives affect security are few and far between. In this paper, we describe a system for simulating how adversarial agents, both economically rational and Byzantine, interact with a blockchain protocol. This system provides statistical estimates for the economic difficulty of an attack and how the presence of certain actors influences protocol-level statistics, such as the expected time to regain liveness. This simulation system is influenced by the design of algorithmic trading and reinforcement learning systems that use explicit modeling of an agent's reward mechanism to evaluate and optimize a fully autonomous agent. We implement and apply this simulation framework to Kadena's Chainweb, a parallelized Proof-of-Work system, that contains complexity in how miner incentive compliance affects security and censorship resistance. We provide the first formal description of Chainweb that is in the literature and use this formal description to motivate our simulation design. Our simulation results include a phase transition in block height growth rate as a function of shard connectivity and empirical evidence that censorship in Chainweb is too costly for rational miners to engage in. We conclude with an outlook on how simulation can guide and optimize protocol development in a variety of contexts, including Proof-of-Stake parameter optimization and peer-to-peer networking design.
While most of humanity is suddenly on the net, the value of this singularity is hampered by the lack of credible digital identities: Social networking, person-to-person transactions, democratic conduct, cooperation and philanthropy are all hampered by the profound presence of fake identities, as illustrated by Facebook's removal of 5.4Bn fake accounts since the beginning of 2019. Here, we introduce the fundamental notion of a \emph{genuine personal identifier}---a globally unique and singular identifier of a person---and present a foundation for a decentralized, grassroots, bottom-up process in which every human being may create, own, and protect the privacy of a genuine personal identifier. The solution employs mutual sureties among owners of personal identifiers, resulting in a mutual-surety graph reminiscent of a web-of-trust. Importantly, this approach is designed for a distributed realization, possibly using distributed ledger technology, and does not depend on the use or storage of biometric properties. For the solution to be complete, additional components are needed, notably a mechanism that encourages honest behavior and a sybil-resilient governance system.
Increased interest in scalable and high-throughput blockchains has led to an explosion in the number of committee selection methods in the literature. Committee selection mechanisms allow consensus protocols to safely select a committee, or a small subset of validators that is permitted to vote and verify a block of transactions, in a distributed ledger. There are many such mechanisms, each with substantially different methodologies and guarantees on communication complexity, resource usage, and fairness. In this paper, we illustrate that, despite these implementation-level differences, there are strong statistical similarities between committee selection mechanisms. We concretely show this by proving that the committee selection of the Avalanche consensus protocol can be used to choose committees in the Stellar Consensus Protocol that satisfy the necessary and sufficient conditions for Byzantine agreement. We also verify these claims using simulations and numerically observe sharp phase transitions as a function of protocol parameters. Our results suggest the existence of a "statistical taxonomy" of committee selection mechanisms in distributed consensus algorithms.
Ilya Afanasyev, Alexander Kolotov, Ruslan Rezin, Konstantin Danilov · 6 authors
The possibilities of decentralization and immutability make blockchain\nprobably one of the most breakthrough and promising technological innovations\nin recent years. This paper presents an overview, analysis, and classification\nof possible blockchain solutions for practical tasks facing multi-agent robotic\nsystems. The paper discusses blockchain-based applications that demonstrate how\ndistributed ledger can be used to extend the existing number of research\nplatforms and libraries for multi-agent robotic systems.\n
In this paper, we describe LUNES-Blockchain, an agent-based simulator of blockchains that is able to exploit Parallel and Distributed Simulation (PADS) techniques to offer a high level of scalability. To assess the preliminary implementation of our simulator, we provide a simplified modelling of the Bitcoin protocol and we study the effect of a security attack on the consensus protocol in which a set of malicious nodes implements a filtering denial of service (i.e. Sybil Attack). The results confirm the viability of the agent-based modelling of blockchains implemented by means of PADS.
Purposely modular, this protocol enables customization of several protocol properties, including the consensus properties implemented, blockchain type, the roots used, and virtual machine opcodes, among others. These modules enable implementing parties to control the behavior of their economy, with a minimal amount of effort, and no sacrifice in participant cryptoeconomic quality. This work also demonstrates the simplification of the developer experience by abstracting away all technological details, except basic CRUD-based operations, using various programming languages. We demonstrate the mechanism design approach taken, and formalize a process for deploying populations of blockchain economies at scale. The framework shown includes adequate tooling for simulation, development, deployment, maintenance, and analytic-based decision making. Lastly, we introduce an expressive programming language for the purpose of creating, and interacting with the cryptoeconomy designed by the implementing developer.
Tetris is an Asynchronous Byzantine Fault Tolerance consensus algorithm designed for next generation high-throughput permission and permissionless blockchain. The core concept of Tetris is derived from Reasoning About Knowledge, which we believe to be the most appropriate tools for revealing and analyzing the fundamental complexity of distributed systems. By analyzing the states of knowledge that each participant attained in an unreliable system, we can capture some of the basis underlying structure of the system, then help us designing effective & efficient protocols. Plus the adoption of Full Information Protocol (FIP) with the optimized message traffic model, Tetris has finally got high performance, with proved safety. Tetris achieve consensus finality in seconds, means transactions can be confirmed greatly faster than other scheme like Pow/Dpos. Tetris also achieve fairness, which is critically important in some areas such as stock market etc.
Decentralized content curation is the process through which uploaded posts are ranked and filtered based exclusively on users' feedback. Platforms such as the blockchain-based Steemit employ this type of curation while providing monetary incentives to promote the visibility of high quality posts according to the perception of the participants. Despite the wide adoption of the platform very little is known regarding its performance and resilience characteristics. In this work, we provide a formal model for decentralized content curation that identifies salient complexity and game-theoretic measures of performance and resilience to selfish participants. Armed with our model, we provide a first analysis of Steemit identifying the conditions under which the system can be expected to correctly converge to curation while we demonstrate its susceptibility to selfish participant behaviour. We validate our theoretical results with system simulations in various scenarios.
We study a stochastic game framework with dynamic set of players, for modeling and analyzing their computational investment strategies in distributed computing. Players obtain a certain reward for solving the problem or for providing their computational resources, while incur a certain cost based on the invested time and computational power. We first study a scenario where the reward is offered for solving the problem, such as in blockchain mining. We show that, in Markov perfect equilibrium, players with cost parameters exceeding a certain threshold, do not invest; while those with cost parameters less than this threshold, invest maximal power. Here, players need not know the system state. We then consider a scenario where the reward is offered for contributing to the computational power of a common central entity, such as in volunteer computing. Here, in Markov perfect equilibrium, only players with cost parameters in a relatively low range in a given state, invest. For the case where players are homogeneous, they invest proportionally to the 'reward to cost' ratio. For both the scenarios, we study the effects of players' arrival and departure rates on their utilities using simulations and provide additional insights.
Konstantin Danilov, Ruslan Rezin, Alexander Kolotov, Ilya Afanasyev
The decentralized trading market approach, where both autonomous agents and people can consume and produce services expanding own opportunities to reach goals, looks very promising as a part of the Fourth Industrial revolution. The key component of the approach is a blockchain platform that allows an interaction between agents via liability smart contracts. Reliability of a service provider is usually determined by a reputation model. However, this solution only warns future customers about an extent of trust to the service provider in case it could not execute any previous liabilities correctly. From the other hand a blockchain consensus protocol can additionally include a validation procedure that detects incorrect liability executions in order to suspend payment transactions to questionable service providers. The paper presents the validation methodology of a liability execution for agent-based service providers in a decentralized trading market, using the Model Checking method based on the mathematical model of finite state automata and Temporal Logic properties of interest. To demonstrate this concept, we implemented the methodology in the Duckietown application, moving an autonomous mobile robot to achieve a mission goal with the following behavior validation at the end of a completed scenario.
Tin Leelavimolsilp, Long Tran-Thanh, Sebastian Stein
Eyal and Sirer's selfish mining strategy has demonstrated that Bitcoin system is not secure even if 50% of total mining power is held by altruistic miners. Since then, researchers have been investigating either to improve the efficiency of selfish mining, or how to defend against it, typically in a single selfish miner setting. Yet there is no research on a selfish mining strategies concurrently used by multiple miners in the system. The effectiveness of such selfish mining strategies and their required mining power under such multiple selfish miners setting remains unknown. In this paper, a preliminary investigation and our findings of selfish mining strategy used by multiple miners are reported. In addition, the conventional model of Bitcoin system is slightly redesigned to tackle its shortcoming: namely, a concurrency of individual mining processes. Although a theoretical analysis of selfish mining strategy under this setting is yet to be established, the current findings based on simulations is promising and of great interest. In particular, our work shows that a lower bound of power threshold required for selfish mining strategy decreases in proportion to a number of selfish miners. Moreover, there exist Nash equilibria where all selfish miners in the system do not change to an honest mining strategy and simultaneously earn their unfair amount of mining reward given that they equally possess sufficiently large mining power. Lastly, our new model yields a power threshold for mounting selfish mining strategy slightly greater than one from the conventional model.
Permission-less blockchains can realise trustless trust, albeit at the cost of limiting the complexity of computation tasks. To explain the implications for scalability, we have implemented a trust model for smart contracts, described as agents in an open multi-agent system. Agent intentions are not necessarily known and autonomous agents have to be able to make decisions under risk. The ramifications of these general conditions for scalability are analysed for Ethereum and then generalised to other current and future platforms.
We examine blockchain technologies, especially smart contracts, as a platform for decentralized applications. By providing a basis for consensus, blockchain promises to upend business models that presuppose a central authority. However, blockchain suffers from major shortcomings arising from an over-regimented way of organizing computation that limits its prospects. We propose a sociotechnical, yet computational, perspective that avoids those shortcomings. A centerpiece of our vision is the notion of a declarative, violable contract in contradistinction to smart contracts. This new way of thinking enables flexible governance, by formalizing organizational structures; verification of correctness without obstructing autonomy; and a meaningful basis for trust.
The electricity distribution grid was not designed to cope with load dynamics imposed by high penetration of electric vehicles, neither to deal with the increasing deployment of distributed Renewable Energy Sources. Distribution System Operators (DSO) will increasingly rely on flexible Distributed Energy Resources (flexible loads, controllable generation and storage) to keep the grid stable and to ensure quality of supply. In order to properly integrate demand-side flexibility, DSOs need new energy management architectures, capable of fostering collaboration with wholesale market actors and pro-sumers. We propose the creation of Virtual Distribution Grids (VDG) over a common physical infrastructure , to cope with heterogeneity of resources and actors, and with the increasing complexity of distribution grid management and related resources allocation problems. Focusing on residential VDG, we propose an agent-based hierarchical architecture for providing Demand-Side Management services through a market-based approach, where households transact their surplus/lack of energy and their flexibility with neighbours, aggregators, utilities and DSOs. For implementing the overall solution, we consider fine-grained control of smart homes based on Inter-net of Things technology. Homes seamlessly transact self-enforcing smart contracts over a blockchain-based generic platform. Finally, we extend the architecture to solve existing problems on smart home control, beyond energy management.
José Horta, Daniel Kofman, David Menga, Alonso Silva
Future electricity distribution grids will host a considerable share of variable renewable energy sources and local storage resources. Moreover, they will face new load structures due for example to the growth of the electric vehicle market. These trends raise the need for new paradigms for distribution grids operation, in which Distribution System Operators will increasingly rely on demand side flexibility and households will progressively become prosumers playing an active role on smart grid energy management. However, in present energy management architectures, the lack of coordination among actors limits the capability of the grid to enable the mentioned trends. In this paper we tackle this problem by proposing an architecture that enables households to autonomously exchange energy blocks and flexibility services with neighbors, operators and market actors. The solution is based on a blockchain transactive platform. We focus on a market application, where households can trade energy with their neighbors, aimed to locally balancing renewable energy production. We propose a market mechanism and dynamic transport prices that provide an incentive for households to locally manage energy resources in a way that responds to both pro-sumer and operator needs. We evaluate the impact of such markets through comprehensive simulations using power flow analysis and realistic load profiles, providing valuable insight for the design of appropriate mechanisms and incentives.
Pietro Danzi, Marko Angjelichinoski, Čedomir Stefanović, Petar Popovski
Residential microgrids (MGs) may host a large number of Distributed Energy Resources (DERs). The strategy that maximizes the revenue for each individual DER is the one in which the DER operates at capacity, injecting all available power into the grid. However, when the DER penetration is high and the consumption low, this strategy may lead to power surplus that causes voltage increase over recommended limits. In order to create incentives for the DER to operate below capacity, we propose a proportional-fairness control strategy in which (i) a subset of DERs decrease their own power output, sacrificing the individual revenue, and (ii) the DERs in the subset are dynamically selected based on the record of their control history. The trustworthy implementation of the scheme is carried out through a custom-designed blockchain mechanism that maintains a distributed database trusted by all DERs. In particular, the blockchain is used to stipulate and store a smart contract that enforces proportional fairness. The simulation results verify the potential of the proposed framework.
Multi-agents systems communication is a technology, which provides a way for multiple interacting intelligent agents to communicate with each other and with environment. Multiple-agent systems are used to solve problems that are difficult for solving by individual agent. Multiple-agent communication technologies can be used for management and organization of computing fog and act as a global, distributed operating system. In present publication we suggest technology, which combines decentralized P2P BOINC general-purpose computing tasks distribution, multiple-agents communication protocol and smart-contract based rewards, powered by Ethereum blockchain. Such system can be used as distributed P2P computing power market, protected from any central authority. Such decentralized market can further be updated to system, which learns the most efficient way for software-hardware combinations usage and optimization. Once system learns to optimize software-hardware efficiency it can be updated to general-purpose distributed intelligence, which acts as combination of single-purpose AI.
Swarms of robots will revolutionize many industrial applications, from targeted material delivery to precision farming. However, several of the heterogeneous characteristics that make them ideal for certain future applications --- robot autonomy, decentralized control, collective emergent behavior, etc. --- hinder the evolution of the technology from academic institutions to real-world problems. Blockchain, an emerging technology originated in the Bitcoin field, demonstrates that by combining peer-to-peer networks with cryptographic algorithms a group of agents can reach an agreement on a particular state of affairs and record that agreement without the need for a controlling authority. The combination of blockchain with other distributed systems, such as robotic swarm systems, can provide the necessary capabilities to make robotic swarm operations more secure, autonomous, flexible and even profitable. This work explains how blockchain technology can provide innovative solutions to four emergent issues in the swarm robotics research field. New security, decision making, behavior differentiation and business models for swarm robotic systems are described by providing case scenarios and examples. Finally, limitations and possible future problems that arise from the combination of these two technologies are described.