Surya Nepal

This paper provides a comprehensive, practitioner-oriented framework and survey to guide the selection and evaluation of differentially private methods for releasing sensitive graph data.

The paper evaluates multi-LLM strategies for secure code generation, finding that hybrid pipelines combining ensembling, static analysis, and patching achieve the strongest security performance, outperforming single models and purely collaborative systems.

HySecTwin introduces a knowledge-driven digital twin framework that uses semantic modeling and hybrid reasoning to provide explainable, context-aware, and high-speed threat detection for complex Cyber-Physical Systems.