MIT CINCS (Communications Information Networks Circuits and Signals) / Hamilton Institute Seminar
Speaker: Professor Paul Patras, U. of Edinburgh
Title: "Making Sense of Mobile Network Traffic using Deep Learning"
Abstract: Accurate understanding of mobile network traffic at city scale is increasingly important for precision network engineering, demand-aware allocation of compute resources, and security. Gaining such knowledge is however difficult, because it requires large-scale measurement collection using dedicated equipment, substantial storage capabilities, and non-trivial post-processing. In this talk I will first make the case for harnessing the power of deep learning to obtain highly-accurate real-time mobile traffic analytics that can fuel the management of 5G networks. I will then show how machine learning can be used in a principled way to detect network threats in their infancy and how to build such detection systems with a view to deployment at the edge.
Bio: Paul Patras is a Reader/Associate Professor in the School of Informatics at the University of Edinburgh, where he leads the Mobile Intelligence Lab. His research crosses the boundaries between mobile networking, security, and data science. His team has been pioneering several applications of AI to the analysis, security, and management of next generation mobile systems. Paul is also a co-founder of Net AI, a university spin-out whose mission is to put mobile network management on autopilot in the cloud.