Abstract
The growth of the Internet of Things (IoT) is contributing to the rise in cyber attacks on the Internet. Unfortunately, the resource-constrained IoT devices and their networks make many traditional security systems less effective or inapplicable. We present TWINKLE, a framework for smart home environments that considers the unique properties of IoT networks. TWINKLE utilizes a two-mode adaptive security model that allows an IoT device to be in regular mode for most of the time which incurs a low resource consumption rate and only when suspicious behavior is detected, switch to vigilant mode which potentially incurs a higher overhead. We show the efficacy of TWINKLE in two case studies that address two types of attacks: distributed denial-of-service (DDoS) and sinkhole attacks. We examine two existing intrusion detection and prevention systems and transform both into new, improved systems using TWINKLE. Our evaluations show that TWINKLE is not only friendly to resource-constrained devices, but can also successfully detect and prevent the two types of attacks, with a significantly lower overhead and detection latency than the existing systems.
This project is in part the result of funding provided by the Science and Technology Directorate of the United States Department of Homeland Security under contract number D15PC00204. The views and conclusions contained herein are those of the authors and should not be interpreted necessarily representing the official policies or endorsements, either expressed or implied, of the Department of Homeland Security or the US Government.
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Sisodia, D., Mergendahl, S., Li, J., Cam, H. (2018). Securing the Smart Home via a Two-Mode Security Framework. In: Beyah, R., Chang, B., Li, Y., Zhu, S. (eds) Security and Privacy in Communication Networks. SecureComm 2018. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 254. Springer, Cham. https://doi.org/10.1007/978-3-030-01701-9_2
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