MAVERICK：一种在运行时对物联网系统实施策略的、独立于应用且平台无关的方法
MAVERICK: An App-independent and Platform-agnostic Approach to Enforce Policies in IoT Systems at Runtime
AI总结：
Maverick 提出一种独立于应用且平台无关的运行时策略执行机制，通过策略语言、合成器与分析器应对来自平台后端、第三方服务及物理交互的不安全行为，并以纠正措施恢复物联网系统安全状态。
摘要：
许多解决方案已被提出，通过在运行时实施安全策略来遏制安装在可编程物联网平台上的自动化应用的意外行为。然而，所有先前的工作由于采用了更简单、不切实际的威胁模型，只解决了实际问题的较弱版本。这些解决方案不够通用，因为它们严重依赖已安装的应用，并且针对特定的物联网平台。在此，我们通过一个现实的威胁模型来解决该问题的更强版本，其中（i）不期望的网络行为不仅可能来自自动化平台后端（例如 SmartThings），还可能来自闭源第三方服务（例如 IFTTT），并且（ii）设备上的物理行为（例如用户交互）可能使物联网系统进入不期望的状态。我们提出了一种运行时机制，称为 Maverick，它采用一个独立于应用、平台无关的中介来对所有不期望的网络行为实施策略，并应用纠正措施，使物联网系统从不安全的状态转换恢复到安全状态。Maverick 配备了一种能够表达丰富时序不变式的策略语言，以及一个自动化工具链，其中包括用于用户辅助的策略合成器和策略分析器。我们在一个原型中实现了 Maverick，并在物理和虚拟测试平台上展示了其有效性，同时仅带来极小的开销。
英文摘要：
Many solutions have been proposed to curb unexpected behavior of automation apps installed on programmable IoT platforms by enforcing safety policies at runtime. However, all prior work addresses a weaker version of the actual problem due to a simpler, unrealistic threat model. These solutions are not general enough as they are heavily dependent on the installed apps and catered to specific IoT platforms. Here, we address a stronger version of the problem via a realistic threat model, where (i) undesired cyber actions can come from not only automation platform backends (e.g., SmartThings) but also close-sourced third-party services (e.g., IFTTT), and (ii) physical actions (e.g., user interactions) on devices can move the IoT system to an undesirable state. We propose a runtime mechanism, dubbed Maverick, which employs an app-independent, platform-agnostic mediator to enforce policies against all undesired cyber actions and applies corrective-actions to bring the IoT system back to a safe state from an unsafe state transition. Maverick is equipped with a policy language capable of expressing rich temporal invariants and an automated toolchain that includes a policy synthesizer and a policy analyzer for user assistance. We implemented Maverick in a prototype and showed its efficacy in both physical and virtual testbeds, incurring minimal overhead.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
