Analyzing Vulnerabilities of Bitcoin: A Study of Sybil, Finney, and Vector76 Attacks and Their Mitigation Strategies

Qinhan Ren

2024

Abstract

This study explores three critical attack vectors includes Sybil, Finney, and Vector76 that pose significant threats to the security of Bitcoin and other blockchain networks. The research analyzes the mechanics of each attack and evaluates their success rates under different network conditions. The Sybil attack is examined in the context of node creation and identity manipulation in decentralized networks. The Finney attack is analyzed for its exploitation of transaction timing vulnerabilities, while the Vector76 attack is studied for how it leverages network propagation delays to achieve double spending. By investigating these attack mechanisms, the study identifies network synchronization and enhanced transaction processing as potential mitigation strategies. The findings highlight the importance of improving block propagation speeds and real-time monitoring systems to strengthen the resilience of blockchain networks. These insights offer valuable guidance for developers and researchers working to bolster the security and stability of decentralized systems, ensuring better protection against evolving threats in cryptocurrency environments.

Paper Citation

in Harvard Style

Ren Q. (2024). Analyzing Vulnerabilities of Bitcoin: A Study of Sybil, Finney, and Vector76 Attacks and Their Mitigation Strategies. In Proceedings of the 2nd International Conference on Data Analysis and Machine Learning - Volume 1: DAML; ISBN 978-989-758-754-2, SciTePress, pages 428-431. DOI: 10.5220/0013525400004619

in Bibtex Style

@conference{daml24,
author={Qinhan Ren},
title={Analyzing Vulnerabilities of Bitcoin: A Study of Sybil, Finney, and Vector76 Attacks and Their Mitigation Strategies},
booktitle={Proceedings of the 2nd International Conference on Data Analysis and Machine Learning - Volume 1: DAML},
year={2024},
pages={428-431},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013525400004619},
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 - Analyzing Vulnerabilities of Bitcoin: A Study of Sybil, Finney, and Vector76 Attacks and Their Mitigation Strategies
SN - 978-989-758-754-2
AU - Ren Q.
PY - 2024
SP - 428
EP - 431
DO - 10.5220/0013525400004619
PB - SciTePress