IoTGaze: IoT Security Enforcement via Wireless Context Analysis
| Autor: | Prasant Mohapatra, Tianbo Gu, Zheng Fang, Pengfei Hu, Allaukik Abhishek, Hao Fu |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
Networking and Internet Architecture (cs.NI)
FOS: Computer and information sciences Computer Science - Cryptography and Security business.industry Computer science Event (computing) Context (language use) Encryption Computer security computer.software_genre Computer Science - Networking and Internet Architecture Context analysis Wireless User interface business Enforcement Internet of Things Cryptography and Security (cs.CR) Wireless sensor network computer |
| Zdroj: | INFOCOM |
| Popis: | Internet of Things (IoT) has become the most promising technology for service automation, monitoring, and interconnection, etc. However, the security and privacy issues caused by IoT arouse concerns. Recent research focuses on addressing security issues by looking inside platform and apps. In this work, we creatively change the angle to consider security problems from a wireless context perspective. We propose a novel framework called IoTGaze, which can discover potential anomalies and vulnerabilities in the IoT system via wireless traffic analysis. By sniffing the encrypted wireless traffic, IoTGaze can automatically identify the sequential interaction of events between apps and devices. We discover the temporal event dependencies and generate the Wireless Context for the IoT system. Meanwhile, we extract the IoT Context, which reflects user's expectation, from IoT apps' descriptions and user interfaces. If the wireless context does not match the expected IoT context, IoTGaze reports an anomaly. Furthermore, IoTGaze can discover the vulnerabilities caused by the inter-app interaction via hidden channels, such as temperature and illuminance. We provide a proof-of-concept implementation and evaluation of our framework on the Samsung SmartThings platform. The evaluation shows that IoTGaze can effectively discover anomalies and vulnerabilities, thereby greatly enhancing the security of IoT systems. 9 pages, 11 figures, 3 tables, to appear in the IEEE International Conference on Computer Communications (IEEE INFOCOM 2020) |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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