【摘要】 为了解决制造变异和噪声对已有硬件木马检测方法的挑战和干扰,提出了一种新的微弱木马信号检测技术,能够在较大的制造变异和噪声的背景下提取出木马特征信号.首先,将木马检测问题建模为特征提取模型,然后提出了一个基于时域约束估计器和主成分投影的统一子空间木马检测方法.并通过特定的子空间投影或重构信号分析,证实弱小的木马信号可以与各种噪声和干扰区分开来.该方法为已有的硬件木马检测方法提供了一种通用的消除制造变异和噪声影响的方法.设计实现了2个时序硬件木马,在ISCAS89基准电路上进行了仿真实验验证,并在FPGA上进行了硬件实物验证,实验结果均表明了所提方法的有效性和高检测精度.更多还原

【Abstract】 In order to eliminate the challenge and interference of the process variation and noises on existing hardware Trojan detection methods,a novel hardware Trojan detection technique is presented,which can detect tiny hardware Trojan characteristics under large process variation and background noises. First,the hardware Trojan detection problem is mathematically formulated as a feature extraction model. Then,a unified subspace hardware Trojan detection technique is proposed based on time domain constrained estimator and principal component projection. It is proved that the weak hardware Trojan signal can be distinguished from various noise sources through particular subspace projections or reconstructed clean signal analysis. The proposed technique provides a general method for related works to eliminate the impact of process variations and noises. Two sequential hardware Trojans are designed and implemented. Both simulation experiments on ISCAS89 benchmark circuits and hardware validations on FPGA( field programmable gate array) boards show the effectiveness and high sensitivity of the proposed hardware Trojan detection technique.更多还原