The Internet of Things (IoT) is emerging as a new Internet paradigm connecting an exponentially increasing number of smart IoT devices and sensors. IoT applications include smart cities, transportation systems, mobile healthcare and smart grid, to name a few. Unlocking the full power of IoT requires analyzing and processing large amounts of data collected by the IoT devices through computationally intensive algorithms that are typically run in the cloud. This leaves the IoT network, and the applications it is supporting, at the complete mercy of an adversary (enemy nations, hackers, etc.), or a natural disaster (hurricane, earthquake, etc.), that can jeopardize the IoT, or completely disconnect it from its "brain" (the cloud), with potentially catastrophic consequences. This research studies Secure Coded Computations aimed at addressing the security challenges of IoT dependence on the cloud for computations by allowing data to be processed locally by IoT-devices that collaborate together to compute.
Our approach is based on the new theory of coded computations, which studies the design of erasure and error-correcting codes to improve the performance of distributed algorithms through "smart" data redundancy. This project represents the first attempt to create a unified framework to study schemes for secure coded computations that, in addition to providing reliable and secure computations on coded data, cater to the specific challenges of IoT. The focus of the proposed research is on (i) devising secure codes and algorithms with low computational complexity that are amenable to implementation on IoT devices typically characterized by low computation power, bandwidth, battery, and storage. Our approach will be based on information theoretic security that presents a lucrative alternative to high complexity homomorphic encryption methods; (ii) developing networking algorithms and protocols to make our secure coded computation framework adaptive to the heterogeneous and dynamic nature of IoT devices; (iii) validating the feasibility of the proposed secure codes and algorithms by building a mobile healthcare monitoring framework using IoT devices. The project also incorporates educational and outreach efforts with a focus on minority groups in Science, Technology, Engineering and Mathematics (STEM). In addition, it includes opportunities for guided tours and possible internships at Rutgers WINLAB for undergraduate students, and a workshop that focuses on theoretical and systems aspects of security in IoT.
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.
