BSides Las Vegas: Scalability, Not as Simple as it SIEMs

Cyber security is a big data problem, the volume and velocity of data from devices requires a new approach that allows exploration at scale across enterprise data. Cyber security is facing a scaling limitation as the number of devices and traffic increases across networks, and current tools are not effective at addressing the key issues of scale and speed. Analysts and companies are inundated with alerts and are unable to distinguish noise from threats until it is too late.

In this 23-minutes presentation, Keith Kraus, associate principal engineer at Accenture Security Labs, explains how Open source big data technologies reduce costs and act as the building blocks of a scalable platform with the speed and scale necessary for enterprises to overcome these challenges.

Kraus is an associate principal for the Accenture Cybersecurity Lab in the Washington, DC, area. Over the past year, Keith has done extensive data engineering, systems engineering, and data visualization work in the cybersecurity domain. His main focus is on building a GPU-accelerated big data solution for advanced threat detection and cyber-hunting capabilities. Prior to working for the Accenture Cybersecurity Lab, Keith was a member of a research team that built a tool designed to optimally place automated defibrillators in urban environments. Keith graduated from Stevens Institute of Technology with a BEng in computer engineering and an MEng in networked information systems.