NeTS: Small: RUI: Towards Secure Home Networks

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The last decade has witnessed the rapid growth of residential broadband connections, home networks, smart home devices, and Internet-of-Things (IoT) systems. However, securing home networks poses a serious challenge, because many home users have little technical expertise to manage, secure and troubleshoot their networks and connected devices. A compelling solution to secure and manage home networks requires an automated and network-based solution that summarizes what is going on in home networks, explains why some observed behaviors are associated with normal or suspicious activities, and suggests how to defend against security threats and stop unexpected behaviors with simple and actionable steps. To improve understanding of the research problems and challenges in securing home networks, this project develops a built-in behavior-oriented traffic profiling system on programmable home routers to collect, analyze and make sense of incoming, outgoing and internal traffic of all Internet-capable devices in home networks.This research project will address the following research problems: i) how to automatically collect traffic data from home networks with little impact on application performance; ii) how to capture and make sense of behavior patterns of home devices via incoming, outgoing, and internal traffic; iii) how to discover network-wide activities across distributed home networks; and iv) how to leverage behavior patterns of home devices to improve security and management.The challenges in uncovering behavior patterns of home devices includes the heterogeneity of home devices, the wide diversity of traffic behavior in different home networks, and the high expectation of user privacy. This project will initiate an educational program on home networks that will engage students in solving the real-world problems. The project brings research and development opportunities for students in underrepresented groups at ASU west campus, a predominantly undergraduate institution where 37% of the applied computing majors are underrepresented minorities.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.