CyberNFTs: Conceptualizing a decentralized and reward-driven intrusion detection system with ML
| Autor: | Selimi, Synim, Rexha, Blerim, Vishi, Kamer |
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| Rok vydání: | 2024 |
| Předmět: | |
| Zdroj: | International Journal of Information and Computer Security (IJICS) 2023 |
| Druh dokumentu: | Working Paper |
| DOI: | 10.1504/IJICS.2023.133385 |
| Popis: | 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 decentralization 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 decentralized 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 decentralized cybersecurity models. Comment: 9 pages, 6 figures, 1 table, 1 algorithm, 1 listing, journal article |
| Databáze: | arXiv |
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