Disguising Topology and Side-Channel Information through Covert Gate- and ML-Enabled IP Camouflaging

TL;DR

This paper introduces a novel IP camouflaging technique called mimetic deception that disguises functional IPs as different appearances, effectively thwarting reverse engineering and side-channel attacks through structural and logical misclassification.

Contribution

It presents a comprehensive evaluation of three deceptive methodologies and demonstrates their effectiveness in resisting GNN-based analysis and differential power analysis attacks.

Findings

Mimetic deception causes misclassification of cryptographic primitives.

The approach successfully thwarts reverse engineering toolchains.

It causes DPA attacks to fail by poisoning the power model.

Abstract

Semiconductor intellectual property (IP) theft incurs hundreds of billions in annual losses, driven by advanced reverse engineering (RE) techniques. Traditional ``cryptic'' IC camouflaging methods typically focus on hiding localized gate functionality but remain vulnerable to system-level structural analysis. This paper explores ``mimetic deception,'' where a functional IP (F) is designed to structurally and visually masquerade as a completely different appearance IP (A). We provide a comprehensive evaluation of three deceptive methodologies: IP Camouflage, Graph Matching, and DNAS-NAND Gate Array, analyzing their resilience against GNN-based node classification, and Differential Power Analysis (DPA). Crucially, we demonstrate that mimetic deception achieves a novel anti-side-channel defense: by forcing the mis-classification of cryptographic primitives, the adversary is led to apply an incorrect power model, causing the DPA attack to fail. Our results validate that this multi-layered approach effectively thwarts the entire RE toolchain by poisoning the structural and logical data used for netlist understanding.