Theme Leader: Bo Wei (Newcastle) and Shishir Nagaraj (Newcastle)

RT2 aims to study and handle how cyber problems affect data and learning in edge computing.

Our goal is to understand and predict these issues, improving the reliability of Edge AI algorithms. Although current methods have shown promise, they have limitations. They do not fully consider how cyber problems affect data quality, learning algorithms, and overall system resilience. Plus, there’s a lack of data on different cyber issues and their effects on edge computing. Also, existing methods don’t adapt well to new problems that weren’t in the original training data.

To overcome these challenges, our project has three main objectives. First, we will identify known cyber problems and their impacts. We will gather information from research and industry partners to understand how these problems affect data and Edge AI algorithms. We will use a new method called Knowledge Graphs to model these problems and their effects.

Second, we will improve our simulation tools to better represent real-world cyber problems. This will help researchers and developers understand and prepare for different scenarios. We will integrate these tools with existing simulators and update them based on community feedback.

Third, we will develop Edge AI models to detect cyber problems in edge computing systems. These models will learn from simulated data and adapt to new challenges over time. We will also explore new Edge AI techniques to improve their performance and efficiency.

Overall, our project aims to create a community-driven platform for understanding and managing cyber problems in edge computing. We will provide tools, data, and models to help researchers and developers build more secure and reliable systems.