I-Corps: Translation Potential of Secure and Efficient Software Updates in Industrial Internet of Things Architectures

Award ID: 2521525

This I-Corps project focuses on the development of secure and energy-efficient software update mechanisms for large-scale, industrial, Internet of Things (IoT) networks. Industrial IoT networks have specific and unique operating requirements that make them highly prone to service disruption and security breaches. Moreover, these networks typically cover large geographical regions and operate in mission-critical industries such as healthcare and energy production. These challenges make software update processes highly challenging, and a top requirement by industrial IoT service providers. This solution also has the potential to decrease the threat of security breaches and attacks on mission-critical infrastructure in the energy, healthcare, and military sectors. As a result, this technology could reduce the economic costs incurred by service disruptions and any accompanying reputation loss, which can reach several millions of U.S. dollars per security incident. This I-Corps project utilizes experiential learning coupled with a first-hand investigation of the industry ecosystem to assess the translation potential of the technology. The solution is based on the development of energy-efficient cryptographic techniques to ensure the incremental updating of sensor-nodes in large-scale, industrial, Internet of Things (IoT) architectures. The technology safeguards the confidentiality, integrity, and authenticity of the software update components, and minimizes the service disruption time needed while loading, deploying, and processing the software updates. The main security engine leverages probabilistic data structures and incremental cryptographic mechanisms to reduce the energy consumption of the software update algorithms and to ensure the uninterrupted operation of the industrial IoT network during the update process. This secure software update solution could provide a safer operating environment for end users in applications relying on IoT architectures. Moreover, the energy-efficient and incremental cryptographic data structures employed in this solution increases the scalability of the overall IoT network and reduces service disruption times, lowering the overall operating costs of mission-critical industrial IoT deployments. 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.

NSF Program Director: Ruth Shuman