<p>Honeypot technology is a network-based system deployed to attract attackers and identify cyber-attacks or attempts to gain unauthorized access to network information. However, traditional honeypots can be easily detected using anti-honeypot techniques. In contrast, dynamic honeypots can analyze real-time scenarios within information systems and interact with attackers while remaining undetected. Conventional honeypot systems typically rely on centralized hosts, which introduces the risk of a single point of failure. A single point of failure in the context of honeypots refers to a situation in which the entire honeypot system becomes compromised or ineffective due to the failure of a central component or host. To address this limitation, there is a need for a distributed architecture for dynamic honeypot systems that can effectively detect security attacks. This paper proposes a novel approach called the Dynamic Fuzzy-Based Blockchain Transport Layer Security Algorithm for attack detection. The dynamic nature of the honeypot system helps in determining the location and authenticity of both real and decoy honeypots across multiple hosts. The proposed attack detection model is evaluated using several performance metrics, including TCP bandwidth, response time, end-to-end delay, and communication overhead. The results demonstrate the effectiveness of the proposed approach in enhancing network security and mitigating cyber threats<b>.</b></p>