Presented By O’Reilly and Cloudera
Make Data Work
March 5–6, 2018: Training
March 6–8, 2018: Tutorials & Conference
San Jose, CA
Ram Shankar Siva Kumar

Ram Shankar Siva Kumar
Security Data Wrangler, Microsoft (Azure Security Data Science)

Ram Shankar is a security data wrangler in Azure Security Data Science, where he works on the intersection of ML and security. Ram’s work at Microsoft includes a slew of patents in the large intrusion detection space (called “fundamental and groundbreaking” by evaluators). In addition, he has given talks in internal conferences and received Microsoft’s Engineering Excellence award. Ram has previously spoken at data-analytics-focused conferences like Strata San Jose and the Practice of Machine Learning as well as at security-focused conferences like BlueHat, DerbyCon, FireEye Security Summit (MIRCon), and Infiltrate. Ram graduated from Carnegie Mellon University with master’s degrees in both ECE and innovation management.

Sessions

11:50am–12:30pm Thursday, March 8, 2018
Failed experiments in infrastructure security analytics and lessons learned from fixing them
Data science and machine learning, Platform security and cybersecurity
 Location: LL20 A
Secondary topics:  Graphs and Time-series
Ram Shankar Siva Kumar (Microsoft (Azure Security Data Science))
Average rating: ****.
(4.00, 1 rating)
How should you best debug a security data science system: change the ML approach, redefine the security scenario, or start over from scratch? Ram Shankar answers this question by sharing the results of failed experiments and the lessons learned when building ML detections for cloud lateral movement, identifying anomalous executables, and automating incident response process. Read more.