Junior Research Fellow Part-time Current
Thapar Institute of Engineering and Technology
Industry-sponsored research project funded by Xebia IT Architects: “A Privacy-Preserving Framework for Secure Knowledge Transfer in Large Language Models for Cyber Threat Intelligence”.
- I own the vision-plus-text security track. It tests how vision-language models respond to direct and indirect prompt injection and to jailbreak attempts delivered through images and text.
- I built the attack taxonomy from the literature and curated attack data from three public benchmarks (MM-SafetyBench, JailBreakV-28K and VLGuard). Each model is scored by attack success rate.
- The wider project studies privacy-preserving language models, including federated learning, reducing the accuracy lost to privacy noise, and testing against real privacy attacks.