CyberNFTs: conceptualising a decentralised and reward-driven intrusion detection system with ML Online publication date: Thu, 14-Sep-2023
by Synim Selimi; Blerim Rexha; Kamer Vishi
International Journal of Information and Computer Security (IJICS), Vol. 22, No. 1, 2023
Abstract: The rapid evolution of the internet, particularly the emergence of Web3, has transformed the ways people interact and share data. Web3, although still not well defined, is thought to be a return to the decentralisation of corporations' power over user data. Despite the obsolescence of the idea of building systems to detect and prevent cyber intrusions, this is still a topic of interest. This paper proposes a novel conceptual approach for implementing decentralised collaborative intrusion detection networks (CIDN) through a proof-of-concept. The study employs an analytical and comparative methodology, examining the synergy between cutting-edge Web3 technologies and information security. The proposed model incorporates blockchain concepts, cyber non-fungible token (cyberNFT) rewards, machine learning algorithms, and publish/subscribe architectures. Finally, the paper discusses the strengths and limitations of the proposed system, offering insights into the potential of decentralised cybersecurity models.
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