Mitigating Double-Spending and Selfish Mining Attacks in Blockchain Networks

Zimeng Gu

2024

Abstract

Blockchain technology offers significant potential across various fields due to its decentralized and tamper-proof nature. However, it is not without its security challenges. This paper focuses on two prominent attacks in blockchain networks: double-spending and selfish mining. It provides a detailed explanation of the double-spending attack, highlighting how it exploits confirmation time differences and transaction revocability to enable the repeated spending of the same digital asset. This attack can result in substantial damage to user assets and undermine system trust. In contrast, selfish mining involves a miner-controlled node deliberately withholding mined blocks to increase its chances of block confirmation. This behavior can disrupt the consensus mechanism, impair system efficiency, and compromise fairness. The paper also explores existing defense mechanisms against these attacks, including enhancements to transaction confirmation processes, the application of advanced cryptographic techniques, and the strengthening of regulatory measures. Additionally, it examines the optimization of consensus algorithms, adjustments to incentive mechanisms, and the establishment of effective monitoring and warning systems. The aim is to provide insights that can enhance blockchain security and support the stable development of blockchain technology.

Paper Citation

in Harvard Style

Gu Z. (2024). Mitigating Double-Spending and Selfish Mining Attacks in Blockchain Networks. In Proceedings of the 2nd International Conference on Data Analysis and Machine Learning - Volume 1: DAML; ISBN 978-989-758-754-2, SciTePress, pages 385-389. DOI: 10.5220/0013524500004619

in Bibtex Style

@conference{daml24,
author={Zimeng Gu},
title={Mitigating Double-Spending and Selfish Mining Attacks in Blockchain Networks},
booktitle={Proceedings of the 2nd International Conference on Data Analysis and Machine Learning - Volume 1: DAML},
year={2024},
pages={385-389},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013524500004619},
isbn={978-989-758-754-2},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 2nd International Conference on Data Analysis and Machine Learning - Volume 1: DAML
TI - Mitigating Double-Spending and Selfish Mining Attacks in Blockchain Networks
SN - 978-989-758-754-2
AU - Gu Z.
PY - 2024
SP - 385
EP - 389
DO - 10.5220/0013524500004619
PB - SciTePress