Big Traffic, Big Trouble: Big Data Security Analytics

Big Traffic, Big Trouble: Big Data Security Analytics

Thursday, October 11
11:50 AM - 12:30 PM

With the rise of IoT and the increasing complexity of applications, clouds, networks and infrastructure, the battle to keep your data and your infrastructure safe from attackers is getting harder. As groups of bad actors collaborate, sharing information and offering illegal access, and botnets as a service, terabits of attack can be launched cheaply. Meanwhile, it’s hard to find enough security analysts to catch and prevent these attacks.

This is where community collaboration and open source efforts like Apache Metron come in. Metron presents a comprehensive framework for application and network, security built on Apache Hadoop and open source Streaming Analytics(ie Apache Nifi, Apache Kafka) tool’s highly scalable data management and processing stacks. Advanced features like profiling, machine learning, and visualization work with real-time streaming detection to make your SOC analysts more efficient, while the intrinsic extensibility of open source helps your data scientists get security insights out of the lab and into production fast.
We will discuss and demonstrate how some real-world businesses and managed service providers are using Apache Metron to identify and solve security threats at scale, and some approaches and ideas for how the platform can fit into your security architecture.


Simon Elliston Ball
Product Manager
Simon is a data scientist, has experience in product management, and has worked for numerous data technology companies, from vendors like Hortonworks to various data users in retail, hedge funds and the web. His focus is on big data, machine learning, and using these technologies to foster results.