Kuai Xu Books

Focusing on network behavior analysis, this book explores the mining of Internet traffic data to identify and model behavioral patterns in various Internet entities, including end hosts and IoT devices. It aims to address the existing gap in literature on this crucial aspect of network security, highlighting its significance for data center, backbone, enterprise, and edge networks. By providing a thorough overview, it serves as a valuable resource for understanding and enhancing network security solutions in today's digital landscape.

Focusing on the intersection of mathematics and social media, this book introduces a dynamic modeling approach using partial differential equations to analyze information diffusion in online networks. It employs the Laplacian matrix to identify user communities, embedding them in Euclidean space for further analysis. The authors validate their models with Twitter data, exploring significant events like the Egyptian revolution and predicting influenza prevalence. This innovative method proposes a paradigm shift in understanding information flow, offering a foundation for future spatio-temporal modeling in the big-data era.