A Multi-Layer Hardware Trojan Protection Framework for IoT Chips

被引:40
|
作者
Dong, Chen [1 ,2 ]
He, Guorong [1 ,2 ]
Liu, Ximeng [1 ,2 ]
Yang, Yang [1 ,2 ]
Guo, Wenzhong [1 ,3 ]
机构
[1] Fuzhou Univ, Coll Math & Comp Sci, Fuzhou 350116, Fujian, Peoples R China
[2] Fuzhou Univ, Key Lab Informat Secur Network Syst, Fuzhou 350116, Fujian, Peoples R China
[3] Fuzhou Univ, Fujian Prov Key Lab Network Comp & Intelligent In, Fuzhou 350116, Fujian, Peoples R China
基金
中国国家自然科学基金;
关键词
Internet of Things; protection framework; hardware security; hardware Trojan; GATE-LEVEL NETLISTS; SECURITY THREATS; CLASSIFICATION;
D O I
10.1109/ACCESS.2019.2896479
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Since integrated circuits are performed by several untrusted manufacturers, malicious circuits (hardware Trojans) can be implanted in any stage of the Internet-of-Things (IoT) devices. With the globalization of the IoT device manufacturing technologies, protecting the system-on-chip (SoC) security is always the keys issue for scientists and IC manufacturers. The existing SoC high-level synthesis approaches cannot guarantee both register-transfer-level and gate-level security, such as some formal verification and circuit characteristic analysis technologies. Based on the structural characteristics of hardware Trojans, we propose a multi-layer hardware Trojan protection framework for the Internet-of-Things perception layer called RG-Secure, which combines the third-party intellectual property trusted design strategy with the scan-chain netlist feature analysis technology. Especially at the gate level of chip design, our RG-Secure is equipped with a distributed, lightweight gradient lifting algorithm called lightGBM. The algorithm can quickly process high-dimensional circuit feature information and effectively improve the detection efficiency of hardware Trojans. In the meanwhile, a common evaluation index F-measure is used to prove the effectiveness of our method. The experiments show that RG-Secure framework can simultaneously detect register-transfer-level and gate-level hardware Trojans. For the trust-HUB benchmarks, the optimized lightGBM classifier achieves up to 100% true positive rate and 94% true negative rate; furthermore, it achieves 99.8% average F-measure and 99% accuracy, which shows a promising approach to ensure security during the design stage.
引用
收藏
页码:23628 / 23639
页数:12
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