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Exposing Hardware Trojans in Embedded Platforms via Short-Term Aging

机译:通过短期老化在嵌入式平台中曝光硬件特洛伊木马

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We demonstrate a novel technique that employs transistor short-term aging effects in integrated circuits (ICs) to detect hardware Trojans in embedded systems. In advanced technology nodes (<= 45 nm), voltage scaling in combination with short-term aging opens doors for short-term degradations. The induced short-term degradations result in dynamic variation of delays along various paths within the IC. Aging degradation generated under fast voltage switching from high to low results in bit errors at the circuit output. Our experiments use short-term aging-aware standard cell libraries to show the effectiveness of short-term aging to detect hardware Trojans. We extract a rich set of features that capture bit error patterns at the outputs of the IC. We use a one class SVM-based classifier that uses these features to learn the distribution of bit errors at the outputs of a clean IC. We discern the deviation in the pattern of bit errors due to a Trojan in the IC from the baseline distribution. To reiterate, the method uses the model of a clean IC. Furthermore, it is robust against chip-to-chip variations. We illustrate the technique on six Trojans from Trust-Hub spanning two cryptographic chips and an embedded PIC microcontroller. Our approach detects Trojans with an accuracy >= 95%. It is easier to detect Trojans in an optimized-netlist circuit as more paths are close to the critical path. Even when the circuit is not optimized (i.e., when very few paths are close to the critical path), short-term aging plus mild overclocking can detect Trojans with high accuracy.
机译:我们展示了一种新颖的技术,用于在集成电路(IC)中采用晶体管短期老化效应来检测嵌入式系统中的硬件特洛伊木马。在先进的技术节点(<= 45nm)中,与短期老化结合的电压缩放打开门用于短期降级。诱导的短期降解导致IC内各种路径的延迟的动态变化。在快速电压切换下产生的老化劣化从高到低导致电路输出的比特误差。我们的实验使用短期老化感知标准单元库来显示短期老化的有效性来检测硬件特洛伊木马。我们提取了丰富的功能集,可在IC的输出端捕获位误差模式。我们使用一种基于SVM的基于SVM的分类器,该分类器使用这些功能来学习在清洁IC的输出端的位错误的分布。由于基线分布的IC中的特洛伊木马,我们辨别出比特误差模式的偏差。要重复,该方法使用清洁IC的模型。此外,对芯片到芯片变化是稳健的。我们从跨越两个加密芯片和嵌入式PIC微控制器的信任集线器和嵌入式PIC微控制器的六个特洛伊木马的技术。我们的方法检测特性的特性> = 95%。随着更多路径靠近关键路径,更容易检测优化的网发电路中的特洛伊木马。即使电路未被优化(即,当极小少数路径接近关键路径时,短期老化加上轻度超频可以检测高精度的特洛伊木马。

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