Automated Hardware Logic Obfuscation Framework Using GPT
Banafsheh Saber Latibari, Sujan Ghimire, Muhtasim Alam Chowdhury,, Najmeh Nazari, Kevin Immanuel Gubbi, Houman Homayoun, Avesta Sasan, Soheil, Salehi

TL;DR
This paper presents Obfus-chat, an innovative GPT-based framework that automates hardware obfuscation to protect intellectual property from reverse engineering, piracy, and tampering, demonstrating effective security enhancements.
Contribution
The paper introduces a novel GPT-driven framework for hardware obfuscation that automates design protection, a significant advancement over manual or traditional methods.
Findings
Effective obfuscation of hardware netlists against SAT attacks
Maintains functional correctness post-obfuscation
Demonstrates efficiency and security improvements using Trust-Hub benchmarks
Abstract
Obfuscation stands as a promising solution for safeguarding hardware intellectual property (IP) against a spectrum of threats including reverse engineering, IP piracy, and tampering. In this paper, we introduce Obfus-chat, a novel framework leveraging Generative Pre-trained Transformer (GPT) models to automate the obfuscation process. The proposed framework accepts hardware design netlists and key sizes as inputs, and autonomously generates obfuscated code tailored to enhance security. To evaluate the effectiveness of our approach, we employ the Trust-Hub Obfuscation Benchmark for comparative analysis. We employed SAT attacks to assess the security of the design, along with functional verification procedures to ensure that the obfuscated design remains consistent with the original. Our results demonstrate the efficacy and efficiency of the proposed framework in fortifying hardware IP…
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Taxonomy
TopicsPhysical Unclonable Functions (PUFs) and Hardware Security · Advanced Malware Detection Techniques · Integrated Circuits and Semiconductor Failure Analysis
