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Research PaperResearchia:202604.16012

Temporary Power Adjusting Withholding Attack

Mustafa Doger

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 $β$ a...

Submitted: April 16, 2026Subjects: Cybersecurity; Computer Science

Description / Details

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 TT-time even when no other block is mined. We show that PAW attack corresponds to TT\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 αα, pool size ββ and adversarial network influence γγ 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)(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)(α,β) at least 1%1\% within 22 weeks in Bitcoin even when γ=0γ=0 (for PAW it was at most 0.01%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.


Source: arXiv:2604.14135v1 - http://arxiv.org/abs/2604.14135v1 PDF: https://arxiv.org/pdf/2604.14135v1 Original Link: http://arxiv.org/abs/2604.14135v1

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Date:
Apr 16, 2026
Topic:
Computer Science
Area:
Cybersecurity
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