A Survey on Applications of Game Theory in Blockchain

Liu, Ziyao; Luong, Nguyen Cong; Wang, Wenbo; Niyato, Dusit; Wang, Ping; Liang, Ying-Chang; Kim, Dong In

doi:10.48550/arxiv.1902.10865

Cited by 19 publications

(23 citation statements)

References 89 publications

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“…Indeed, assigning rewards to miners and clients has been shown to leverage the FLchain scheme to obtain better results [60]. A comprehensive survey on game theory in BC can be found in [61].…”

Section: Blockchain Consensusmentioning

confidence: 99%

Analysis and Evaluation of Synchronous and Asynchronous FLchain

Wilhelmi¹,

Giupponi²,

Dini³

2021

Preprint

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Motivated by the heterogeneous nature of devices participating in large-scale Federated Learning (FL) optimization, we focus on an asynchronous server-less FL solution empowered by Blockchain (BC) technology. In contrast to mostly adopted FL approaches, which assume synchronous operation, we advocate an asynchronous method whereby model aggregation is done as clients submit their local updates. The asynchronous setting fits well with the federated optimization idea in practical large-scale settings with heterogeneous clients. Thus, it potentially leads to higher efficiency in terms of communication overhead and idle periods. To evaluate the learning completion delay of BC-enabled FL, we provide an analytical model based on batch service queue theory. Furthermore, we provide simulation results to assess the performance of both synchronous and asynchronous mechanisms. Important aspects involved in the BC-enabled FL optimization, such as the network size, link capacity, or user requirements, are put together and analyzed. As our results show, the synchronous setting leads to higher prediction accuracy than the asynchronous case. Nevertheless, asynchronous federated optimization provides much lower latency in many cases, thus becoming an appealing FL solution when dealing with large data sets, tough timing constraints (e.g., near-real-time applications), or highly varying training data.

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Section: Blockchain Consensusmentioning

confidence: 99%

Analysis and Evaluation of Synchronous and Asynchronous FLchain

Wilhelmi¹,

Giupponi²,

Dini³

2021

Preprint

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“…There are a number of published surveys on game theoretical approaches to blockchain-related issues. Liu et al (2019) reviews game models proposing to address common issues, including security , mining management , and economic and energy trading in blockchains.…”

Section: Related Workmentioning

confidence: 99%

“…Using the equilibrium of a noncooperative game can help the consensus protocol to achieve this outcome. Instead of picking a random node, we can build a game environment that lets a large number of risk neutral nodes compete for the right to build block B(n), so that new transactions are verified by numerous confirmations derived from competition between nodes (a process normally referred to as mining a block) (Liu et al 2019). Apart from the consensus protocol, nodes do not face any other strategic restrictions.…”

Section: Introductionmentioning

confidence: 99%

A Mean Field Game Analysis of Consensus Protocol Design

Klinger

Zhang

Zhou

2021

Preprint

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A decentralized blockchain is a distributed ledger that is often used as a platform for exchanging goods and services. This ledger is maintained by a network of nodes that obeys a set of rules, called a consensus protocol, which helps to resolve inconsistencies among local copies of a blockchain. In this paper, we build a mathematical framework for the consensus protocol designer that specifies (a) the measurement of a resource which nodes strategically invest in and compete for in order to win the right to build new blocks in the blockchain; and (b) a payoff function for their efforts. Thus the equilibrium of an associated stochastic differential game can be implemented by selecting nodes in proportion to this specified resource and penalizing dishonest nodes by its loss. This associated, induced game can be further analyzed by using mean field games. The problem can be broken down into two coupled PDEs, where an individual node's optimal control path is solved using a Hamilton-Jacobi-Bellman equation, where the evolution of states distribution is characterized by a Fokker-Planck equation. We develop numerical methods to compute the mean field equilibrium for both steady states at the infinite time horizon and evolutionary dynamics. As an example, we show how the mean field equilibrium can be applied to the Bitcoin blockchain mechanism design. We demonstrate that a blockchain can be viewed as a mechanism that operates in a decentralized setup and propagates properties of the mean field equilibrium over time, such as the underlying security of the blockchain.

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“…A comprehensive survey summarizing numerous applications of game theory to blockchains is provided by Liu et al [33]. There is large interest in the game-theoretic analysis of attacks such as selfish mining attacks [34], block withholding attacks [35], among others.…”

Section: Related Workmentioning

confidence: 99%

Reward Mechanism for Blockchains Using Evolutionary Game Theory

Shashank¹,

Jacobsen²

2021

Preprint

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Blockchains have witnessed widespread adoption in the past decade in various fields. The growing demand makes their scalability and sustainability challenges more evident than ever. As a result, more and more blockchains have begun to adopt proof-of-stake (PoS) consensus protocols to address those challenges. One of the fundamental characteristics of any blockchain technology is its crypto-economics and incentives. Lately, each PoS blockchain has designed a unique reward mechanism, yet, many of them are prone to free-rider and nothing-at-stake problems. To better understand the ad-hoc design of reward mechanisms, in this paper, we develop a reward mechanism framework that could apply to many PoS blockchains. We formulate the block validation game wherein the rewards are distributed for validating the blocks correctly. Using evolutionary game theory, we analyze how the participants' behaviour could potentially evolve with the reward mechanism. Also, penalties are found to play a central role in maintaining the integrity of blockchains.

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A Survey on Applications of Game Theory in Blockchain

Cited by 19 publications

References 89 publications

Analysis and Evaluation of Synchronous and Asynchronous FLchain

Analysis and Evaluation of Synchronous and Asynchronous FLchain

A Mean Field Game Analysis of Consensus Protocol Design

Reward Mechanism for Blockchains Using Evolutionary Game Theory

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