A Kansas State University engineer is developing advanced cybersecurity tools for artificial intelligence applications in bioinformatics with an automated framework to ensure both accuracy and security of data.
Xiaolong Guo, an assistant professor in the Mike Wiegers Department of Electrical and Computer Engineering, has received nearly $560,000 from the National Science Foundation to boost AI security for antimicrobial peptide (AMP) research. This grant supports the development of an automated framework designed to ensure the accuracy and security of AMP data, reducing reliance on costly and time-consuming lab experiments.
The three-year project, titled “CICI: UCSS: Safeguarding AI in Bioinformatics: Enhancing Cybersecurity in Biological Data Infrastructure,” is funded by the NSF’s Office of Advanced Cyberinfrastructure. Co-principal investigators include Yonghui Li and Kaichen Yang. The project aims to create a secure, open-source dataset and an online platform to evaluate AMP data security, fostering a security-conscious culture and ensuring reliable computational predictions.
