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

Fuente: arXiv
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Main Authors: Fan, Junling, Koblah, David, Forte, Domenic
Format: Preprint
Published: 2026
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author Fan, Junling
Koblah, David
Forte, Domenic
author_facet Fan, Junling
Koblah, David
Forte, Domenic
contents 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.
format Preprint
id arxiv_https___arxiv_org_abs_2603_25904
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Disguising Topology and Side-Channel Information through Covert Gate- and ML-Enabled IP Camouflaging
Fan, Junling
Koblah, David
Forte, Domenic
Cryptography and Security
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.
title Disguising Topology and Side-Channel Information through Covert Gate- and ML-Enabled IP Camouflaging
topic Cryptography and Security
url https://arxiv.org/abs/2603.25904