TY - GEN
T1 - Premining in the Shadows
T2 - 30th European Symposium on Research in Computer Security, ESORICS 2025
AU - Zeng, Wanying
AU - Xie, Lijia
AU - Zhang, Xiao
N1 - Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2026.
PY - 2026
Y1 - 2026
N2 - Nakamoto Consensus (NC), the foundational mechanism of Bitcoin, secures permissionless blockchains through Proof-of-Work (PoW) and the longest-chain rule. Although classical analyses suggest exponentially low success probabilities for attackers with less than 50% hash power, real-world double-spending attacks (DSAs) persist, especially when pre-mining is involved. However, existing models either neglect pre-mining or inadequately capture its trade-offs with post-transaction mining. In this paper, we first develop a pre-mining DSA model with fixed cost constraints, deriving closed-form expressions for success probability and expected revenue. Next, we propose an Adaptive Pre-mining DSA strategy that dynamically optimizes attack timing for profit maximization using Stochastic Dynamic Programming (SDP). Through comprehensive simulations, we evaluate the effectiveness of our attack strategies, demonstrating their superior performance over existing models. Based on transaction values, we propose optimal confirmation block thresholds. These insights contribute to both theoretical and practical security improvements for decentralized system protocols.
AB - Nakamoto Consensus (NC), the foundational mechanism of Bitcoin, secures permissionless blockchains through Proof-of-Work (PoW) and the longest-chain rule. Although classical analyses suggest exponentially low success probabilities for attackers with less than 50% hash power, real-world double-spending attacks (DSAs) persist, especially when pre-mining is involved. However, existing models either neglect pre-mining or inadequately capture its trade-offs with post-transaction mining. In this paper, we first develop a pre-mining DSA model with fixed cost constraints, deriving closed-form expressions for success probability and expected revenue. Next, we propose an Adaptive Pre-mining DSA strategy that dynamically optimizes attack timing for profit maximization using Stochastic Dynamic Programming (SDP). Through comprehensive simulations, we evaluate the effectiveness of our attack strategies, demonstrating their superior performance over existing models. Based on transaction values, we propose optimal confirmation block thresholds. These insights contribute to both theoretical and practical security improvements for decentralized system protocols.
KW - Blockchain Security
KW - Double-Spending Attack
KW - Nakamoto Consensus
KW - Pre-Mining Strategy
KW - Stochastic Dynamic Programming
UR - https://www.scopus.com/pages/publications/105020013033
U2 - 10.1007/978-3-032-07901-5_22
DO - 10.1007/978-3-032-07901-5_22
M3 - 会议稿件
AN - SCOPUS:105020013033
SN - 9783032079008
T3 - Lecture Notes in Computer Science
SP - 433
EP - 451
BT - Computer Security – ESORICS 2025 - 30th European Symposium on Research in Computer Security, Proceedings
A2 - Nicomette, Vincent
A2 - Benzekri, Abdelmalek
A2 - Boulahia-Cuppens, Nora
A2 - Vaidya, Jaideep
PB - Springer Science and Business Media Deutschland GmbH
Y2 - 22 September 2025 through 24 September 2025
ER -