Prof. Felix Xiaozhu Lin to use NSF grant to improve edge processing
A grant from the National Science Foundation will help ECE Prof. Felix Xiaozhu Lin do research into safeguarding Internet of Things (IoT) data during edge processing. Lin’s project, “CAREER: A Trustworthy and Verifiable Software Backplane for the Cloud Edge,” was awarded $477K over five years from the NSF’s Division of Computer and Network Systems (CNS). He says as IoT is revolutionizing modern society, the project aims toward more secure and efficient intelligence driven by IoT data.
“The project highlights the significance of “secure by design” software as we move more computation to the cloud edge,” says Lin. “With my students, I look forward to contributing new design principles and experience to the space of edge computing.”
The objective of the project is to safeguard IoT data during edge processing by establishing a trusted data path on the edge. As the data flows through the path, the proposed edge system ensures 1) data confidentiality: IoT data is only accessible to trusted parties; 2) integrity: all the data having arrived at the edge is exactly manipulated according to the planned processing; 3) verifiability: data flows and computations on the edge are verifiable to a trusted cloud backend.
In addition to the research component of the project, there is also an education and outreach plan. That includes educating students on trustworthy computing scenarios as well as stimulating the public's interests in science, technology, engineering, and math (STEM). Lin says there are plans to contribute fresh contents to curriculum; enhance student maker activities with in-situ IoT analytics; provide a summer course on IoT/Edge for local children; and, present relevant outreach at community IoT events.
The NSF’s CNS Division supports research and education activities that invent new computing and networking technologies and that explore new ways to make use of existing technologies. The Division seeks to develop a better understanding of the fundamental properties of computer and network systems and to create better abstractions and tools for designing, building, analyzing, and measuring future systems. CNS also supports the computing infrastructure that is required for experimental computer science, and it coordinates cross-divisional activities that foster the integration of research, education, and workforce development.