As the world becomes more urbanized, cities are facing a growing number of challenges related to security, sustainability, and connectivity. To address these challenges, many cities are turning to modern sustainable cognitive approaches that leverage advanced technology and data analytics to optimize energy efficiency, reduce environmental impact, and enhance the well-being of citizens. However, as cities become more connected and technologically advanced, they also become more vulnerable to security threats, such as cyberattacks, terrorism, natural disasters, and crime.

This is where the concept of the security of modern sustainable cognitive cities comes into play. The security of these cities refers to the measures and practices put in place to ensure the safety and protection of citizens, infrastructure, and assets in urban environments that are sustainable, connected, and intelligent. It requires a comprehensive approach that incorporates advanced sensors and surveillance systems, data analytics, artificial intelligence, and cloud-based security platforms.

This project aims to improve the security of modern sustainable cognitive cities using Federated Learning (FL) with encryption. By leveraging FL, our approach enables devices to learn collaboratively while keeping data locally, reducing the risk of data breaches and preserving privacy. The addition of encryption provides an additional layer of security, ensuring that sensitive data remains protected even in the event of a security breach. Our project focuses on developing and implementing advanced optimization algorithms that are specifically designed for FL, minimizing network communication expenses, and improving the overall efficiency of the communication process. This approach has the potential to significantly enhance the security and privacy of citizens and infrastructure in modern sustainable cognitive cities, promoting safety, sustainability, and resilience.