Temporary Power Adjusting Withholding Attack

2026-04-15

AI Summary

This study addresses the suboptimality of the Power Adjusting Withholding (PAW) strategy in block withholding attacks against mining pools, particularly for attackers with limited computational power. The authors propose a novel Temporal PAW (T-PAW) attack, wherein an attacker withholds proof-of-work submissions for at most a duration T, significantly boosting profitability even in the absence of other block discoveries. They formally demonstrate that PAW corresponds to the limiting case of T→∞ and is provably non-optimal. By modeling miner incentives through game-theoretic analysis incorporating the attacker’s hash rate α, pool size β, and network influence γ, the work reveals that T-PAW can yield up to 22 times the revenue of PAW under (α,β,γ) = (0.05,0.05,0). In most realistic scenarios, T-PAW achieves over 1% profit increase within two weeks—substantially outperforming PAW’s marginal 0.01% gain—and exposes fundamental structural vulnerabilities in current mining pool mechanisms.

Technology Category

• Search and Optimization: Adversarial Search
• Multiagent Systems: Mechanism Design
• Game Theory and Economic Paradigms: Mechanism Design

Application Category

• Web Mining and Content Analysis: Content-based information diffusion
• User Modeling, Personalization and Recommendation: Attacks and countermeasures in recommendation systems
• Economics, Online Markets and Human Computation: Economic aspects of blockchain and cryptocurrencies

Abstract

We consider the block withholding attacks on pools, more specifically the state-of-the-art Power Adjusting Withholding (PAW) attack. We propose a generalization called Temporary PAW (T-PAW) where the adversary withholds a fPoW from pool mining at most $T$-time even when no other block is mined. We show that PAW attack corresponds to $T\to\infty$ and is not optimal. In fact, the extra reward of T-PAW compared to PAW improves by an unbounded factor as adversarial hash fraction $α$, pool size $β$ and adversarial network influence $γ$ decreases. For example, the extra reward of T-PAW is 22 times that of PAW when an adversary targets a pool with $(α,β,γ)=(0.05,0.05,0)$. We show that honest mining is sub-optimal to T-PAW even when there is no difficulty adjustment and the adversarial revenue increase is non-trivial, e.g., for most $(α,β)$ at least $1\%$ within $2$ weeks in Bitcoin even when $γ=0$ (for PAW it was at most $0.01\%$). Hence, T-PAW exposes a significant structural weakness in pooled mining-its primary participants, small miners, are not only contributors but can easily turn into potential adversaries with immediate non-trivial benefits.

Problem

• block withholding attack
• pooled mining
• adversarial mining
• temporary power adjusting
• structural weakness

Innovation

• Temporary PAW
• block withholding attack
• pooled mining
• adversarial mining strategy
• cryptocurrency security