Rishikesh Sahay

The paper proposes an automated, LLM-enabled threat hunting framework integrated with Splunk to help SOC analysts autonomously monitor evolving threats and prioritize suspicious network traffic.

This paper evaluates and compares HAZOP and Bow-Tie analysis, demonstrating that while both are useful for cyber risk assessment in hydropower, a coordinated adversary can bypass conventional safeguards by compromising shared network infrastructure.

The paper proposes a management framework, using a governed AI query-broker artifact, to safely integrate generative AI into high-risk operational decision support, such as Security Operations Centers (SOCs).

This paper develops an explainable and deployable machine learning system for highly accurate phishing detection across diverse, heterogeneous datasets, achieving up to 99.78% accuracy using transformer models.