Kumar Sharad's Blog Posts
Kumar Sharad is a Sr. Staff Software Engineer on the Splunk Machine Learning for Security team, where he leads the development of AI-driven SIEM and UEBA solutions. He holds a PhD from Cambridge and works at the intersection of security and machine learning, with deep expertise in adversarial ML, data privacy, and large-scale behavioral analytics. His research experience across the UK and Germany informs his focus on translating ML research into effective security defenses.
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The Insider Threat That Doesn’t Sleep
These .conf26 sessions will guide practitioners through building ML-based detections, understanding AI agent risks, and applying these techniques to real attack scenarios.
Print, Leak, Repeat: UEBA Insider Threats You Can't Ignore
UEBA excels at identifying small deviations in user and device behavior across authentication, data access, data movement, and privilege usage.
Machine Learning in Security: Detecting Suspicious Processes Using Recurrent Neural Networks
Splunk's Kumar Sharad explains how to detect suspicious processes using recurrent neural networks.