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Anomaly detection in embedded systems using simultaneous power and temperature monitoring

机译:使用同时电力和温度监测的嵌入式系统中的异常检测

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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,嵌入式系统被认为是持续时间较长的安全违规行为。最近发现了像W32这样的安全攻击。 Stuxnet和Duqu Worm改变了这几乎建立的信念。此外,通常在嵌入式系统中使用通常的异常检测方法,因为它们通常是资源受限的,并且检测方法可能会干扰主系统任务的性能。然而,在嵌入式系统中运行的应用程序的行为相对较为令人着重,并且逐步分析正确的行为并将其与运行时行为进行比较被认为是异常检测的有效方法,没有这种干扰。在本文中,我们考虑了嵌入式系统的处理器温度和功耗的互效,并提出了一种新颖的技术来检测具有次要延迟的恶意活动。这是通过分析处理器的同时观察的功率和温度来完成的。通过使用通过详细仿真获得的实际处理器的功率和温度迹线来评估所提出的方法的功效。

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