10:35 AM - 11:20 AM (PDT)
Anomaly Detection using ML & Data Science

10 years ago when you mention logs or event data to a cybersecurity professional, they would think how to use that data during a cyber incident. Today companies are using data and technology to increase productivity and efficiency. For forward looking cybersecurity teams they are thinking about how they can leverage the vast amount of data that is being collected and stored for cybersecurity functions. They holy grail is being able to use this data and actually extracting useful information for our #1 goal, keeping our organizations secure.

“In data analysis, anomaly detection (also referred to as outlier detection and sometimes as novelty detection) is generally understood to be the identification of rare items, events or observations which deviate significantly from the majority of the data and do not conform to a well defined notion of normal behavior”

In this discussion we will ask the subject matter experts to discuss what ingredients are required to build a scalable anomaly detection system.

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