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Anomaly detection in embedded systems using simultaneous power and temperature monitoring

机译:使用同时的功率和温度监控来检测嵌入式系统中的异常

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Embedded systems were traditionally considered impenetrable against security violations for a long duration. The recently discovered security attacks like W32. Stuxnet and the Duqu worm changed this almost established belief. Further, usual methods of anomaly detection cannot simply be employed in embedded systems since they are usually resource-constrained and the detection methods might interfere with performance of the main system tasks. However, behavior of applications running in embedded systems is relatively known, and profiling the correct behavior and comparing it with the runtime behavior is accounted as an effective approach for anomaly detection with no such interferences. In this paper, we consider the inter-effects of processor temperature and power consumption of embedded systems, and present a novel technique to detect malicious activities with minor delays with respect to the occurrences. This is done through analyzing the simultaneously observed power and temperature of the processor. The efficacy of the proposed method is evaluated by using the power and temperature traces of a real processor obtained through detailed simulations.
机译:传统上,嵌入式系统在很长一段时间内都无法抵御安全性违规。最近发现的安全攻击,例如W32。 Stuxnet和Duqu蠕虫改变了这种几乎确定的信念。此外,常规的异常检测方法不能简单地在嵌入式系统中使用,因为它们通常受资源限制,并且检测方法可能会干扰主要系统任务的性能。但是,在嵌入式系统中运行的应用程序的行为是相对已知的,并且分析正确的行为并将其与运行时行为进行比较被认为是一种在没有此类干扰的情况下进行异常检测的有效方法。在本文中,我们考虑了处理器温度和嵌入式系统功耗之间的相互影响,并提出了一种新颖的技术来检测恶意活动,并在发生这些事件时稍有延迟。这是通过分析同时观察到的处理器的功率和温度来完成的。通过使用通过详细仿真获得的真实处理器的功率和温度轨迹,可以评估所提出方法的有效性。

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