ObfAx: Obfuscation and IP Piracy Detection in Approximate Circuits

2026-05-11

AI Summary

This work addresses the emerging threat of “approximate obfuscation” piracy targeting approximate circuits deployed as reusable IP cores, wherein adversaries evade detection through structural obfuscation and functional modifications. Existing mechanisms lack effective countermeasures against such attacks. To bridge this gap, the paper presents the first automated framework for detecting IP piracy in approximate circuits, formally defining the “approximate obfuscation” adversarial model and introducing a novel paradigm based on statistical error profile comparison. By automatically extracting and matching error characteristics between the original IP core and a suspect circuit, the method enables efficient identification of unauthorized reuse. Experimental validation on diverse approximate multipliers demonstrates the framework’s efficacy and reveals varying resilience across approximation designs, thereby laying the groundwork for secure deployment and commercialization of approximate computing IPs.

Abstract

Approximate circuits often achieve exceptional trade-offs between computational accuracy and hardware efficiency, making them attractive for deployment as reusable Intellectual Property (IP) cores. However, safeguarding such circuits against piracy is critical for enabling sustainable commercialization of approximate computing. This work addresses the emerging challenge of IP protection and piracy detection in the context of approximate hardware. We introduce a novel adversarial threat model, approximate obfuscation, in which an attacker not only conceals the design through structural obfuscation but also introduces functional modifications to ensure that the resulting circuit exhibits nearly identical error characteristics and hardware metrics as the original IP. To counter this threat, we propose an automated framework that extracts and compares statistical error profiles of protected IP cores and suspicious circuits, enabling systematic detection of potential IP theft. Through extensive experiments on a diverse set of approximate multipliers, we analyze the resilience of different approximate multipliers against approximate obfuscation. Our results provide new insights into the interplay between obfuscation, approximation, and IP protection.

Problem

• approximate circuits
• IP piracy detection
• obfuscation
• intellectual property protection
• hardware security

Innovation

• approximate obfuscation
• IP piracy detection
• statistical error profiling
• approximate circuits
• hardware security