Adaptive Defense Mechanisms Against Phishing Threats in 6G Wireless Environments

Phishing attacks remain a persistent and evolving cybersecurity threat, particularly in the context of 6G wireless networks. This paper introduces an innovative approach to combat phishing threats, leveraging advanced techniques tailored to the unique challenges of 6G environments. Our research focuses on enhancing the security posture of 6G networks by deploying adaptive defense mechanisms for real-time phishing attack detection and prevention. In this study, we employ cutting-edge deep learning models specifically customized to the 6G landscape. A multi-layer neural network architecture is utilized, fortified with advanced activation functions optimized for the dynamic nature of 6G wireless communication. The proposed model is trained on an extensive and diverse dataset, carefully curated to include phishing and legitimate activities specific to 6G networks, enabling robust learning and broad generalization.