一句话：提出 IoTCOM，结合程序分析与形式化违例检测，可扩展地发现 IoT 应用中隐藏的交互安全威胁。
IoT 应用与物理设备之间的非期望或恶意协调会在交互层面引发复杂的安全与安全隐患，且这类威胁往往难以发现。本文提出 IoTCOM，以组合化且可扩展的方式自动发现此类隐藏的不安全交互威胁。该方法依赖程序分析自动推断应用的相关行为，并利用一种新颖的策略在将提取出的行为转换为可分析的形式化规约之前对其进行裁剪，从而缓解形式化分析中的状态爆炸问题；其后端由形式化严格的违例检测引擎支撑。作者在大量真实 IoT 应用组合上开展实验，结果表明 IoTCOM 能有效检测通过信息与物理通道触发的多种交互威胁，其中许多此前未知，并且在可扩展性上显著优于现有技术。
The ubiquity of Internet of Things (IoT) and our growing reliance on IoT apps are leaving us more vulnerable to safety and security threats than ever before. Many of these threats are manifested at the interaction level, where undesired or malicious coordinations between apps and physical devices can lead to intricate safety and security issues. This paper presents IoTCOM, an approach to automatically discover such hidden and unsafe interaction threats in a compositional and scalable fashion. It is backed with auto-mated program analysis and formally rigorous violation detection engines. IoTCOM relies on program analysis to automatically infer the relevant app’s behavior. Leveraging a novel strategy to trim the extracted app’s behavior prior to translating them to analyzable formal specifications,IoTCOM mitigates the state explosion associated with formal analysis. Our experiments with numerous bundles of real-world IoT apps have corroborated IoTCOM’s ability to effectively detect a broad spectrum of interaction threats triggered through cyber and physical channels, many of which were previously unknown, and to significantly outperform the existing techniques in terms of scalability.
DOI 原文 ·
@inproceedings{paperbot6070,
title = {Scalable analysis of interaction threats in IoT systems},
author = {Mohannad Alhanahnah and Clay Stevens and Hamid Bagheri},
booktitle = {ISSTA},
year = {2020},
doi = {10.1145/3395363.3397347}
}