Abstract
Blockchain technology has gained prominence over the last decade. Numerous achievements have been made regarding how this technology can be utilized in different aspects of the industry, market, and governmental departments. Due to the safety-critical and security-critical nature of their uses, it is pivotal to model the dependability of blockchain-based systems. In this study, we focus on Bitcoin, a blockchain-based peer-to-peer cryptocurrency system. A continuous-time Markov chain-based analytical method is put forward to model and quantify the dependability of the Bitcoin system under selfish mining attacks. Numerical results are provided to examine the influences of several key parameters related to selfish miners’ computing power, attack triggering, and honest miners’ recovery capability. The conclusion made based on this research may contribute to the design of resilience algorithms to enhance the self-defense and robustness of cryptocurrency systems.
Highlights
Intensive research and development efforts from academia, industries and governments have been devoted to blockchain technology in the last decade (Ferrag et al, 2018; Kang et al, 2018; Dai et al, 2019; Bhushan et al, 2021)
Numerical Results and Impacts of Model Parameters the effects of several key parameters on the Bitcoin dependability are investigated through numerical results
Directions The Bitcoin network is vulnerable to selfish mining attacks, during which a malicious miner withholds the mined block and mines on its own private chain secretly
Summary
Intensive research and development efforts from academia, industries and governments have been devoted to blockchain technology in the last decade (Ferrag et al, 2018; Kang et al, 2018; Dai et al, 2019; Bhushan et al, 2021). In Zhou et al (2021a), a continuous-time Markov Chain-based approach was suggested for assessing the dependability of a Bitcoin node subject to Eclipse attacks; this work was extended in Zhou et al (2021b) through semi-Markov models for accommodating non-exponential state transition time distributions. Under state 1, if the malicious miner successfully finds the block on their private branch, the system transits to state 2 with transition rate of λ12. Under state 0’ (the chain has two branches of length one), if the malicious miner finds the new block with rate λ0’1, the system transits to state 1 where the selfish miner’s private branch is one block longer.
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: International Journal of Mathematical, Engineering and Management Sciences
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
