Adaptive Fuzzy Logic Framework for Threat Detection in Distributed Honeypot Systems Leveraging Blockchain Technology

In the continuous expanding domain of cybersecurity, the rise of more cyber threats is also increasing. Therefore, it demands the development of more efficient defense strategies. In past, honeypots are used as lucrative devices to attract malicious activity. However, most of the honeypot systems are static in nature, which may not be efficient in distributed environment. This paper introduces a Dynamic Distributed Honeypot System (DDHS) for the same purpose. In these honeypots nodes are dynamically distributed and connected via blockchain technology, aimed at improving threat detection and response capabilities. By distributing honeypots across multiple nodes in a blockchain network, the proposed system is more secure against external attack. This paper discusses the dynamic fuzzy rules method for the threat detection in the distributed honeypot systems.