Data-driven networking and security

Using AI/ML to solve networking/security problems

The last few years have witnessed the coming of age of data-driven paradigm in various aspects of computing (partly) empowered by advances in distributed system research (cloud computing, MapReduce, etc). In this work, we observe that the benefits can flow the opposite direction: the design and management of networked systems and security solutions can be improved by data-driven paradigm. To this end, we are exploring new data-driven paradigms that have the the potential to significantly achieve better performance and security. Our overarching vision is to create unified framework for DDN to tackle common challenges and create reusable design principles. We believe that by systematizing this paradigm as a broader community, we can unleash the unharnessed potential of DDN.