4 trends in security data science for 2018
A glimpse into what lies ahead for response automation, model compliance, and repeatable experiments.
Ram Shankar Siva Kumar
Ram Shankar is a Security Data Wrangler on the Azure Security Data Science team at Microsoft, where his primary focus is modeling massive amounts of security logs to surface malicious activity. His work has appeared in security focused conferences like BlueHat, DerbyCon, MIRCon, Infiltrate as well as Big Data conferences like Strata+Hadoop World and Practice of Machine Learning. Ram graduated from Carnegie Mellon University with a Masters in Electrical and Computer Engineering, and a Masters in Engineering and Technology Innovation Management.
Content
4 trends in security data science for 2017
How bots, threat intelligence, adversarial machine learning, and deep learning are impacting the security landscape.
Strategies to validate your security detections
Machine learning to generate attack data and improve security analytics.
4 trends in security data science
From intelligent investigation to cloud “security-as-a-service,” what you need to know for 2016.
Best kept machine learning secret in security
Ranking algorithms bolster intrusion detection systems.
Suppressing false alerts in data security
How to prevent false positives from limiting intrusion detection systems