Renovating location-based routing for integrated communication privacy and efficiency in IoT
Tao Shu, Shuguang Robert Cui · 2017
This paper presents HC-LBR routing, the first location-based routing (LBR) mechanism that simultaneously retains high communication efficiency and privacy for Internet of Things (IoT). Existing LBR schemes were originally designed for wireless sensor networks (WSNs). Although they offer attractive efficiency and scalability, their privacy performance presents a vulnerability when being used in IoT. This is because, unlike a conventional WSN where all nodes are owned by the same user, an IoT network has an open architecture in which nodes owned by different users are mixed and work together. Therefore, when LBR is directly used in an IoT network, the sharing of location information among alien nodes allows one user to peek into the communication privacy of other users. HC-LBR overcomes this privacy weakness by computing efficient geographic routes directly based on Hilbert-Curve-encrypted location information. HC-LBR consists of two components: A Kademlia-tree-based routing algorithm that supports efficient geographic routing in HC encrypted space, and Rand-Mix, a lightweight traffic mixer that uses multiple traffic flows to enhance the privacy of HC routing. Our simulation-based evaluation verifies the high efficiency and privacy of the proposed methods.