5 papers
Learning Structural Manipulability in Gate-Level Netlists Using Graph Neural Networks
Rupesh Raj Karn, Ozgur Sinanoglu
Gate-level netlists exhibit intrinsic structural properties that influence signal propagation independently of functional simulation. We define a topology-driven structural manipul…
Leaking Circuit Secrets: Gradient Leakage Attacks on Graph Neural Networks
Rupesh Raj Karn, Johann Knechtel, Ozgur Sinanoglu
As graph neural networks (GNNs) become standard tools for critical tasks in circuit design and analysis, their security and privacy risks require careful attention. Here, we presen…
Revisiting Logic Encryption
Rupesh Raj Karn, Lakshmi Likhitha Mankali, Zeng Wang +5
Modern circuits face various threats like reverse engineering, theft of intellectual property (IP), side-channel attacks, etc. Here, we present a novel approach for IP protection b…
SALAD: Systematic Assessment of Machine Unlearning on LLM-Aided Hardware Design
Zeng Wang, Minghao Shao, Rupesh Karn +6
Large Language Models (LLMs) offer transformative capabilities for hardware design automation, particularly in Verilog code generation. However, they also pose significant data sec…
Linear Feedback Control Systems for Iterative Prompt Optimization in Large Language Models
Rupesh Raj Karn
Large Language Models (LLMs) have revolutionized various applications by generating outputs based on given prompts. However, achieving the desired output requires iterative prompt…