CAGE: Consensus Algorithm Genetically Enhanced

Mitchell, Ian ORCID logoORCID: https://orcid.org/0000-0002-3882-9127 and Kamil, Maka (2023) CAGE: Consensus Algorithm Genetically Enhanced. In: Virtual 15th International Conference on Global Security, Safety & Sustainability, 11th & 12th October 2023, Online. . ISSN 1613-5113 [Conference or Workshop Item]

Abstract

Blockchain is a disruptive technology and relies on the development of consensus algorithms, CA. Currently, there are many CAs proposed and this paper explores a new avenue of nature-inspired CAs. In particular, emphasis is on selection techniques used in canonical genetic algorithms, GAs, and fatiguing.

The premise is that selection techniques used in GAs could be adapted and used to select nodes responsible for adding blocks in permissioned blockchain networks. This was then tested on a blockchain network and executed many times and compared to another CA for permission blockchain networks, Proof-of-Elapsed-Time, PoET.

The results are interesting and show an improvement in transaction throughput and block creation. Our initial results, however, had a biased node selection and could be vulnerable to take-over attacks. Therefore, a fatiguing element was introduced and the experiments were repeated with the results showing a less biased node selection.

The overall contribution is the exploration of nature as a solution to CAs. The initial results are comparable and places better than existing CAs.

Item Type: Conference or Workshop Item (Paper)
Sustainable Development Goals:
Theme:
Research Areas: A. > School of Science and Technology > Computer Science
Item ID: 37837
Depositing User: Ian Mitchell
Date Deposited: 18 Apr 2023 13:52
Last Modified: 02 Jun 2023 16:38
URI: https://eprints.mdx.ac.uk/id/eprint/37837

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