Manas Kumar Yogi

Safe Intelligence for All: Building Adversarially Resilient LLM Interfaces for CTI

A novel Multi-Layer Adversarial Defense Framework (MLADF), a composite metric for evaluating the robustness of CTI LLM interfaces, and a Confidence-Aware Response Sanitization (CARS) technique combining Monte Carlo dropout uncertainty quantification with knowledgebase factgrounding are introduced.