UNSAIL: Thwarting Oracle-Less Machine Learning Attacks on Logic Locking

被引:25
作者
Alrahis, Lilas [1 ,2 ]
Patnaik, Satwik [3 ,4 ]
Knechtel, Johann [5 ]
Saleh, Hani [1 ,2 ]
Mohammad, Baker [1 ,2 ]
Al-Qutayri, Mahmoud [1 ,2 ]
Sinanoglu, Ozgur [5 ]
机构
[1] Khalifa Univ, Dept Elect Engn & Comp Sci EECS, Abu Dhabi 127788, U Arab Emirates
[2] Khalifa Univ, Syst Chip Ctr SoCC, Abu Dhabi 127788, U Arab Emirates
[3] NYU, Tandon Sch Engn, Dept Elect & Comp Engn, Brooklyn, NY 11201 USA
[4] Texas A&M Univ, Dept Elect & Comp Engn, College Stn, TX 77843 USA
[5] New York Univ Abu Dhabi, Div Engn, Abu Dhabi 129188, U Arab Emirates
关键词
Integrated circuit modeling; Logic gates; Redundancy; Supply chains; Security; System-on-chip; Predictive models; Logic locking; hardware security; IP protection; hardware obfuscation; machine learning; COMPLEXITY; SECURITY;
D O I
10.1109/TIFS.2021.3057576
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
Logic locking aims to protect the intellectual property (IP) of integrated circuit (IC) designs throughout the globalized supply chain. The SAIL attack, based on tailored machine learning (ML) models, circumvents combinational logic locking with high accuracy and is amongst the most potent attacks as it does not require a functional IC acting as an oracle. In this work, we propose UNSAIL, a logic locking technique that inserts key-gate structures with the specific aim to confuse ML models like those used in SAIL. More specifically, UNSAIL serves to prevent attacks seeking to resolve the structural transformations of synthesis-induced obfuscation, which is an essential step for logic locking. Our approach is generic; it can protect any local structure of key-gates against such ML-based attacks in an oracle-less setting. We develop a reference implementation for the SAIL attack and launch it on both traditionally locked and UNSAIL-locked designs. For SAIL, two ML models have been proposed (which we implement accordingly), namely a change-prediction model and a reconstruction model; the change-prediction model is used to determine which key-gate structures to restore using the reconstruction model. Our study on benchmarks ranging from the ISCAS-85 and ITC-99 suites to the OpenRISC Reference Platform System-on-Chip (ORPSoC) confirms that UNSAIL degrades the accuracy of the change-prediction model and the reconstruction model by an average of 20.13 and 17 percentage points (pp), respectively. When the aforementioned models are combined, which is the most powerful scenario for SAIL, UNSAIL reduces the attack accuracy of SAIL by an average of 11pp. We further demonstrate that UNSAIL thwarts other oracle-less attacks, i.e., SWEEP and the redundancy attack, indicating the generic nature and strength of our approach. Detailed layout-level evaluations illustrate that UNSAIL incurs minimal area and power overheads of 0.26% and 0.61%, respectively, on the million-gate ORPSoC design.
引用
收藏
页码:2508 / 2523
页数:16
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