An IoT Data Communication Framework for Authenticity and Integrity

Abstract

Internet of Things has been widely applied in everyday life, ranging from transportation, healthcare, to smart homes. As most IoT devices carry constrained resources and limited storage capacity, sensing data need to be transmitted to and stored at resource-rich platforms, such as a cloud. IoT applications retrieve sensing data from the cloud for analysis and decision-making purposes. Ensuring the authenticity and integrity of the sensing data is essential for the correctness and safety of IoT applications. We summarize the new challenges of the IoT data communication framework with authenticity and integrity and argue that existing solutions cannot be easily adopted. We present two solutions, called Dynamic Tree Chaining (DTC) and Geometric Star Chaining (GSC) that provide authenticity, integrity, sampling uniformity, system efficiency, and application flexibility to IoT data communication. Extensive simulations and prototype emulation experiments driven by real IoT data show that the proposed system is more efficient than alternative solutions in terms of time and space.