Theses and Dissertations
Date of Award
12-2022
Document Type
Dissertation
Degree Name
Ph.D.
Department
Computing
Committee Chair
Todd Andel, Ph.D.
Abstract
Selfish mining is an attack against a blockchain where miners hide newly discovered blocks instead of publishing them to the rest of the network. Selfish mining has been a potential issue for blockchains since it was first discovered by Eyal and Sirer. It can be used by malicious miners to earn a disproportionate share of the mining rewards or in conjunction with other attacks to steal money from network users. Several of these attacks were launched in 2018, 2019, and 2020 with the attackers stealing as much as $18 Million. Developers made several different attempts to fix this issue, but the effectiveness of the fixes is currently unknown. Despite the known vulnerability, there is little researching into detecting these attacks either historically or in real-time. In this research, we build a program to gather data from known selfish mining attacks against the Ethereum Classic blockchain. We then use this data to train a machine-learning algorithm to discover the important features for detecting selfish mining.
Recommended Citation
Peterson, Matthew A., "Detecting Selfish Mining Attacks Against a Blockchain Using Machine Learing" (2022). Theses and Dissertations. 118.
https://jagworks.southalabama.edu/theses_diss/118
Included in
Information Security Commons, Numerical Analysis and Scientific Computing Commons, Other Computer Sciences Commons, Systems Architecture Commons