A Novel Hardware Trojan Detection Method Based on Node Activity State

FENG Qiu-li; HOU Bo; LIU Yan-jiang; EN Yun-fei; WANG Li-wei

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A Novel Hardware Trojan Detection Method Based on Node Activity State

更新时间：2026-09-04

- A Novel Hardware Trojan Detection Method Based on Node Activity State
- Vol. 34, Issue 1, Pages: 35-39(2017)
- 作者机构：
  
  1. 工业和信息化部电子第五研究所电子元器件可靠性物理及其应用技术重点实验室,广东,广州,510610
  2. 广东工业大学机构材料与能源学院,广东,广州,510006
- 作者简介：
- 基金信息：
- DOI：
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- Published：2017
- 稿件说明：
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冯秋丽, 侯波, 刘燕江, 恩云飞, 王力纬. 基于节点活性的硬件木马检测方法[J]. 微电子学与计算机, 2017, 34(1): 35-39.

FENG Qiu-li, HOU Bo, LIU Yan-jiang, et al. A Novel Hardware Trojan Detection Method Based on Node Activity State[J]. 2017, 34(1): 35-39.
冯秋丽, 侯波, 刘燕江, 恩云飞, 王力纬. 基于节点活性的硬件木马检测方法[J]. 微电子学与计算机, 2017, 34(1): 35-39. DOI：

FENG Qiu-li, HOU Bo, LIU Yan-jiang, et al. A Novel Hardware Trojan Detection Method Based on Node Activity State[J]. 2017, 34(1): 35-39. DOI：

摘要

本文提出了一种基于节点活性的硬件木马检测方法

针对电路中的低活性节点生成测试向量

结合多参数旁路检测方法

实现对硬件木马的检测.以AES为目标电路并植入硬件木马

进行仿真及FPGA实验

实验结果表明与随机测试向量相比

本文生成的测试向量可将木马节点的翻转概率提高一个数量级、木马检测灵敏度分别提高6.75%(仿真)、77.4%(FPGA)

硬件木马的检测精度达到10.

Abstract

In this paper

we propose a hardware Trojan detection method based on nodes activity state

in view of the low activity nodes of original circuit generate test vectors

Combined with the method of multi-parameter side channel signals to detect Hardware Trojan. The proposed method is verified by simulation and FPGA experiment carried on AES original circuit which is implanted with hardware trojan. The results show that compared with random test vector

the proposed method can improve the transition probability of the trojans of nodes an order of magnitude and increase the sensitivity of the Hardware Trojan detection by 6.75%(simulation)

77.4%(FPGA)

detecte the Hardware Trojan whose equivalent area is as small as 10 of the total size of the circuit.

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Keywords

references

Wang X, Tehranipoor M, Plusquellic J. Detecting malicious inclusions in secure hardware: Challenges and solutions[C]// Hardware-Oriented Security and Trust, 2008. HOST 2008. IEEE International Workshop on. USA, Anaheim, IEEE, 2008: 15-19.

Jha S, Jha S K, Randomization based probabilistic approach to detect trojan circuits[C]// High Assurance Symposium, 2008. China, Nanjing, IEEE, 2008: 117-124.

Jin, Yier, Yiorgos Makris. Hardware Trojan detection using path delay fingerprint[C]// Hardware-Oriented Security and Trust, 2008. HOST 2008. IEEE International Workshop on. USA, Anaheim, IEEE, 2008.

Du D, Narasimhan S, Chakraborty R S, et al. Self-referencing: a scalable side-channel approach for hardware Trojan detection[C]// Proceedings of the 12th international conference on Cryptographic hardware and embedded systems. Santa Barbara, Springer-Verlage, 2010: 173-187.

尚子靖. 基于活性测度的硬件木杷检测方法研究[D]. 北京: 北京大学, 2012: 23-24.

刘华锋, 罗宏伟, 王力纬. 硬件木马检测技术的研究[C]// 2011第十四届全国可靠性物理学术讨论会. 中国, 苏州, 2011.

赵崇征, 邓高明, 赵强. 基于旁路分析的集成电路芯片硬件木马检测[J]. 微电子学与计算机, 2011, 28(11): 5-9. DOI: 5

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