基于探索式分区和测试向量生成的硬件木马检测方法

摘要

本文提出基于分区和最优测试向量生成的硬件木马检测方法。首先，采用基于扫描细胞分布的分区算法将电路划分为多个区域。然后，提出测试向量重组算法，对各区域依据其自身结构生成近似最优的测试向量。最后，进行分区激活和功耗分析以检测木马，并采用信号校正技术消减制造变异和噪声的影响。优点是成倍提高了检测精度，克服了制造变异的影响，解决了面对大电路的扩展性问题，并可以定位木马。在基准电路上的验证实验表明检测性能有较大的提升。%A novel hardware Trojan detection method based on heuristic partition and optimal test pattern generation is proposed.First,we use a scan cell distribution based heuristic partition to divide the circuit into regions.Then,we propose a test vector ordering algorithm to generate near-optimal test patterns based on the circuit’s structure.Lastly,we activate each region separately and perform localized IDDT analysis to detect hardware Trojans while a signal calibration technique is used to eliminate the effect of process variations and noises.The benefits of this approach are that it can magnify detection sensitivity,eliminate the effects of process variations and noises,ensure the scalability of hardware Trojan detection facing large scale ICs,and determine Trojan’s location.We evaluate our approach on benchmark circuits and the experiment results show that the detection sensitivity is greatly improved.