Countering Selfish Mining in Blockchains

Abstract

Selfish mining is a well known vulnerability in blockchains exploited by miners to steal block rewards. In this paper, we explore a new form of selfish mining attack that guarantees high rewards with low cost. We show the feasibility of this attack facilitated by recent developments in blockchain technology opening new attack avenues. By outlining the limitations of existing countermeasures, we highlight a need for new defense strategies to counter this attack, and leverage key system parameters in blockchain applications to propose an algorithm that enforces fair mining. We use the expected transaction confirmation height and block publishing height to detect selfish mining behavior and develop a network-wide defense mechanism to disincentivize selfish miners. Our design involves a simple modifications to transactions' data structure in order to obtain a "truth state" used to catch the selfish miners and prevent honest miners from losing block rewards.

Exploring the Attack Surface of Blockchain: A Comprehensive Survey

“…Their proposed design incorporates nonoutsourceable puzzles in PoW, in which mining pools that outsource their mining work risk losing mining rewards. Saad et al [144] leveraged the expected transaction confirmation height and the block publishing height to detect selfish mining behavior in PoW-based Blockchains. Using the relationship between the two features, they created a "truth state" for each published block in order to distinguish between a legitimate block and a selfishly mined block.…”

Exploring Sybil and Double-Spending Risks in Blockchain Systems

“…The countermeasures are categorised under six defensive strategies. The study [130] utilised the notion of "truth state" for blocks by adding the expected confirmation height parameter in each transaction data structure to recognise selfish mining in the network.…”

Blockchain System Defensive Overview for Double-Spend and Selfish Mining Attacks: A Systematic Approach

“…The "truth state" is another detection method [112]. This strategy is ideally integrated for the fork instant and used to identify selfish mining attacks.…”

“…To combat against selfish mining attack, several recent proposed approaches are proved with experiment to mitigate selfish mining attack effectively, including weighted FRP (Fork-Resolving Policy) [113], truth state [112] in the detection type method, blockchain fork heights [119] in the monitoring type method, and SquirRL [116] in the inform type method and chain locks [30] in the conceptual research design type method. Some methods bring a lot of computational overhead which limits the possibility of realworld deployment, such as FruitChain [103] introduced a second mining process, counter mining [111] introduced sensor miners, and new payoff scheme [118].…”