Any wireless network is built on the mutually reinforcing pillars of privacy and security. Security measures often cover data connections, physical security, outside threats, and internal node operations. Whereas privacy covers the selective exchange of d

Wireless networks rely on the interplay between privacy and security, addressing data protection, physical security, and internal operations. Traditional privacy algorithms, such as l-diversity and k-anonymity, often struggle to scale effectively. To tackle this issue, a new protocol utilizing machine learning and blockchain technology is proposed, focusing on efficient attribute-based privacy while enhancing overall network Quality of Service.