用区块链和NFT激励构建去中心化入侵检测网络
CyberNFTs: Conceptualizing a decentralized and reward-driven intrusion detection system with ML
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- 通过网络安全NFT奖励机制激励用户参与威胁上报
- 适合关注去中心化安全与激励机制的研究者
互联网的快速发展，尤其是Web3的兴起，改变了人们交互和共享数据的方式。尽管传统的入侵检测系统已显过时，但其仍具研究价值。本文提出一种基于概念验证的去中心化协同入侵检测网络（CIDN）新构想，结合区块链技术、网络安全非同质化代币（cyberNFT）激励、机器学习算法与发布/订阅架构。研究采用分析与比较方法，探讨前沿Web3技术与信息安全的融合潜力。最后讨论该系统的优缺点，揭示去中心化网络安全模型的应用前景。
原文摘要 · Abstract (English)
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.
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