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Context-Aware Sensor Fusion for Securing Cyber-Physical Systems

机译:用于保护网络物理系统的上下文感知传感器融合

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The goal of this dissertation is to provide detection and estimation techniques in order to ensure the safety and security of modern Cyber-Physical Systems (CPS) even in the presence of arbitrary sensors faults and attacks. We leverage the fact that modern CPS are equipped with various sensors that provide redundant information about the system's state. In such a setting, the system can limit its dependence on any individual sensor, thereby providing guarantees about its safety even in the presence of arbitrary faults and attacks.;In order to address the problem of safety detection, we develop sensor fusion techniques that make use of the sensor redundancy available in modern CPS. First of all, we develop a multidimensional sensor fusion algorithm that outputs a bounded fusion set which is guaranteed to contain the true state even in the presence of attacks and faults. Furthermore, we provide two approaches for strengthening sensor fusion's worst-case guarantees: 1) incorporating historical measurements as well as 2) analyzing sensor transmission schedules (e.g., in a time-triggered system using a shared bus) in order to minimize the attacker's available information and impact on the system. In addition, we modify the sensor fusion algorithm in order to provide guarantees even when sensors might experience transient faults in addition to attacks. Finally, we develop an attack detection technique (also in the presence of transient faults) in order to discard attacked sensors.;In addition to standard plant sensors, we note that modern CPS also have access to multiple environment sensors that provide information about the system's context (e.g., a camera recognizing a nearby building). Since these context measurements are related to the system's state, they can be used for estimation and detection purposes, similar to standard measurements. In this dissertation, we first develop a nominal context-aware filter (i.e., with no faults or attacks) for binary context measurements (e.g., a building detection). Finally, we develop a technique for incorporating context measurements into sensor fusion, thus providing guarantees about system safety even in cases where more than half of standard sensors might be under attack.
机译:本文的目的是提供检测和估计技术,即使在存在任意传感器故障和攻击的情况下,也能确保现代网络物理系统(CPS)的安全性。我们利用了以下事实:现代CPS配备了各种传感器,这些传感器可提供有关系统状态的冗余信息。在这种情况下,系统可以限制其对任何单个传感器的依赖性,从而即使在出现任意故障和攻击时也能保证其安全性。为了解决安全检测的问题,我们开发了传感器融合技术,使用现代CPS中可用的传感器冗余。首先,我们开发了一种多维传感器融合算法,该算法可输出有界融合集,即使在出现攻击和错误的情况下,该集也可以保证包含真实状态。此外,我们提供了两种方法来加强传感器融合的最坏情况保证:1)结合历史测量以及2)分析传感器传输计划(例如,在使用共享总线的时间触发系统中),以最大程度地减少攻击者的可利用性信息及其对系统的影响。此外,我们修改了传感器融合算法,以便即使在传感器可能遭受除攻击之外的瞬态故障时也能提供保证。最后,我们开发了一种攻击检测技术(也在存在瞬时故障的情况下),以丢弃被攻击的传感器。;除了标准的工厂传感器,我们注意到现代CPS还可以访问多个环境传感器,这些传感器提供有关系统的信息。上下文(例如,摄像头识别附近的建筑物)。由于这些上下文测量与系统状态有关,因此可以将它们用于估计和检测目的,类似于标准测量。在本文中,我们首先为二进制上下文测量(例如,建筑物检测)开发了一个标称的上下文感知过滤器(即没有故障或攻击)。最后,我们开发了一种将上下文测量合并到传感器融合中的技术,从而即使在一半以上的标准传感器可能受到攻击的情况下,也可以保证系统安全。

著录项

  • 作者单位

    University of Pennsylvania.;

  • 授予单位 University of Pennsylvania.;
  • 学科 Computer science.
  • 学位 Ph.D.
  • 年度 2017
  • 页码 219 p.
  • 总页数 219
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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