SpecEES: Towards Secure Decision Making in Spectrum and Energy Efficient IoT Systems

University Of California-Davis, Davis CA

Investigators

Abstract

The Internet-of-Things (IoT) has recently emerged as a powerful new paradigm for future generations of wireless networks. In IoT, a wide variety of devices, such as body sensors, implants, animal biochip transponders, electric clams in coastal waters, vehicular sensors, sensors for environmental/food/pathogen monitoring, and devices in disaster relief operations, are connected to the Internet via wireless interfaces. Connecting this myriad of mobile devices to the Internet could potentially lead to a broad range of innovative network applications. However, unique technical challenges for IoT, such as massive connectivity, security vulnerability and energy sustainability, among others, need to be addressed before such potentials can be fully fulfilled. This project aims to develop a robust and secure framework for wireless function computing to specifically address challenges in IoT applications. The enabling characteristic of this framework is that in many IoT applications, instead of recovering the full data collected by various devices and transmitted over the network, the goal of the networked functional computing is to assist certain decision making, for which the decision makers only need to compute a function of these distributed data. The main idea of this project is to develop secure and spectrum/energy efficient protocols that enable the decision maker to compute functions of interest without first recovering the full data from sensing devices. Thus, instead of acting as mere data pipes, wireless links become an integral part of the smart decision process in IoT applications. Successful execution of this project will make substantial contributions to both practical applications and theory development. On the application level, this project has the potential to substantially improve the spectrum efficiency, energy efficiency and robustness to active attacks for future IoT networks. On the theory side, this project will develop low-complexity efficient and robust function computing algorithms that enable IoT applications to make timely and accurate decisions. 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.