A Secure and Trusted Communication Solution for Web 3.0 Based on Edge Intelligence

ABSTRACT The rise of AI has positioned edge computing as a pivotal domain for deploying machine learning technologies, fostering agile processing, and enhancing network robustness and decision‐making capabilities. This paper addresses the underexplored aspects of DDoS and phishing attacks, and precise decision‐making at network edge devices within blockchain‐based frameworks. The contribution lies in proposing an incentive‐based security mechanism to divert intruders from genuine routes. Legitimate devices conducting accurate decision‐making are rewarded, enticing their participation in identifying false devices. A honeypot intrusion detection system attracts false devices, and real‐time trust computation monitors communication devices. This approach is analyzed under security threats and network delays, demonstrating its efficacy compared to existing methods in safeguarding edge computing environments.