Yixuan Wang Wins Best Student Paper at IEEE Conference
Department of Computer Science & Engineering Ph.D. student Yixuan Wang won the Best Student Paper award at the IEEE International Conference on Edge Computing and Communication (IEEE EDGE 2023) for their paper titled, “Social Quorum-Based Access Control for Open Internet of Things (IoT) Environmental (SQuBA)”. The conference is a forum that is used as a prime international forum for both researchers and industry practitioners to exchange the latest fundamental advances in the state-of-the-art practice of edge computing and provides a platform to connect with other researchers in the field. Wang is advised by Professors Abhishek Chandra and Jon Weissman.
“My research is pretty close to our daily work,” said Wang. “Imagine you are in a smart home with multiple smart devices like your camera and smartwatches. All of those smart devices are collecting private data, and those specific devices can potentially be connected and controlled by multiple people - you, your friends, visiting people, your spouse, or your child. How are you going to make sure only the right person can access and control your device? It is a crucial problem. Our research solves the problem by considering the real-world relationship - the ownership, the friendship, and the parent-child relationship. We explore the real-world social relationship, to kind of develop a community to make sure only the right person accesses the device.”
Wang’s research ensures that only the correct people - family, friends, or the owner - have access to these devices. By examining how people interact with privacy and the social relationships between users, she was able to see that these relationships that the owner has with their friends or family and trust are important when giving access to devices.
“We're not doing abstract research or theoretical research,” said Wang. “We analyze the real world and how people use and interact with their smart devices. We investigated the behavior of how people manage their devices and also investigated how their social relationships can get involved in these problems. Even the average person can recognize their social relationships and use those relationships to help protect their privacy. This is something that can be used with any type of smart device.”
For the next steps of Wang’s research, she hopes to refine the policies to make things more understandable for users to apply to their daily lives. Wang also wants to expand her research to larger platforms such as smart homes and smart cities being able to further improve privacy with loT devices.