Data-driven Security Analytics

Catalog description

Today's security event monitoring and correlation tools are being taxed more than ever before. The constant deluge of data being output by the many devices in our security infrastructures and input into log managers, SIEM (Security information and event management) and other security management interfaces creates quite a load on our analytics systems. In the noise of all this security and event-related data, it is difficult to sort through and obtain real, actionable events that need attention. The market is in need of a new generation of security tools - ones that process much larger datasets, are capable of deep-dive analytics and rely more on intelligence than attack signatures. The proposed course will cover the fundamental data science techniques that are applied to enhance security intelligence. This course will complement the existing computer science and software engineering curriculum. It also prepares students for both a career as a data scientist and as a cybersecurity analyst.