Protecting Your Messages


Shi Bai, Ph.D., an assistant professor in the department of mathematical sciences in the Charles E. Schmidt College of Science.

New Faculty Spotlight: Protecting Your Messages

Using Cryptography to Secure Information

Protecting private communication from the military to corporations to your text messages, requires building better cybersecurity to combat the looming threat of quantum computers and their ability to crack encrypted data.

The race is on to find something secure, using cryptography to ensure the protection, according to Shi Bai, Ph.D., assistant professor in the department of mathematical sciences in the Charles E. Schmidt College of Science. Bai is working on a mathematical method, called lattice-based cryptographic systems, which is the use of mathematical equations to protect the security of messages by disguising it, he said.

"It is crucial to search for forms of cryptography that are secure against quantum computers," said Bai, who was recently received a $500,675 National Science Foundation Early Career Award for his cutting-edge work in cryptography.

Q: What was your journey like coming to FAU?

A: Before moving to FAU, I studied and traveled across several countries and continents. I did my undergraduate degree in China and then moved to Australia for my master's and doctorate degrees. I then worked as a postdoctoral researcher in New Zealand and France, respectively. I joined the math department at FAU as an assistant professor in 2016 and have enjoyed the friendly, collaborative work environment, with great colleagues, and along with a wonderful campus.

Experiencing the new culture when moving around was tricky, but also provided me the chance to learn new skills and new opportunities. For me, one of the best tools is to always keep an open mind, both for learning the new environment and for doing my research work.

Q: Why do you consider FAU the best place to carry out your research?

A: My research interests are in the field of computational number theory and cryptography. FAU's department of mathematical sciences has a long tradition working in this area, i.e. mathematical cryptology, with a strong group. Research interests amongst our colleagues are strategically aligned and complementary. This gives me a great advantage to be able to discuss with my colleagues, stimulating new ideas and research insights.

FAU also provides excellent support for research for new faculty. As an example, when I started my position as an assistant professor, I was supported by an FAU Faculty Research Mentoring Award, with which I was able to fund a High Performance Computing or HPC for doing the computation for one of my projects.

Q: When did you develop an interest in research?

A: Computer science has always been my favorite subject. Like many others, it started with computer games, and I was curious about the underlying principles, such as how they were designed and built. I started to play around with some simple programming and algorithms, but didn't get into my current research area until I started my masters and doctorate at Australia National University.

When I started my master's degree, the research project I was working on was algorithms for factoring integers. The beauty of these algorithms from computational number theory and their natural connection to cryptography immediately captured my interests. Since then, I've expanded my research interests into post-quantum cryptography, which is the topic that I am mostly working on these days.

Q: What is the goal for your research?

A: Protect public-key cryptosystems in the quantum era; and help with the training of a more diverse workforce in cybersecurity.

Q: Any upcoming projects or new advancements in your current research?

A: With my graduate and undergraduate students, we are working on a variety of projects in constructing more efficient and effective post-quantum cryptographic schemes, a mathematical solution to perform a unique function to encrypt or decrypt, as well as looking into their application in secure machine learning. We hope some of these schemes can be turned into practical schemes deployable in today's technological ecosystem.

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