Xintao Wu Awarded Two NSF Grants
Dr. Xintao Wu, Professor and Charles D. Morgan/Acxiom Graduate Research Chair in Computer Science and Computer Engineering, has received two NSF awards to conduct research and build the education framework for genetic privacy protection. The era of personal genomics, where genetic information is ubiquitously available for research, clinical practice or personal curiosity, is quickly approaching. At the same time, there is a growing concern of genetic privacy as genotype data with attached traits (e.g., diseases) are very sensitive.
The first project, which is funded by the NSF Smart and Connected Health Program, aims to address genetic privacy protection in two research arenas: genome wide association studies (GWAS) and expression quantitative trait loci (eQTL) mapping. The released GWAS/eQTL statistics or results from analytical methods, which are important to biological research, do not completely conceal participant identity, incurring serious privacy concerns. The proposed research will develop differential privacy and Bayesian network based attack modeling techniques and investigate whether and to what extent the released genomic statistics and analytical results can be exploited by an attacker to learn private traits of regular individuals in addition to human genomic study participants. A primary outcome of this research will be a suite of novel tools and technologies and a Web-portal for privacy preserving analysis of genomic data, which will help researchers in their endeavor to meet growing expectations in protecting privacy and provide privacy assurance when regular individuals share their genetic profiles.
The second project, which is funded by the NSF Secure and Trustworthy CyberspaceProgram, aims to enhance education in genetic privacy in Computer Science, Bioinformatics and Genomics. The existing educational resources are focused mostly on legal, regulatory or ethical issues in personal genomics. There is a substantial gap in educating genetic privacy and this project includes three key thrusts: (1) build the education framework for genetic privacy protection that is integrated with interdisciplinary research in the areas of data privacy and genetics/genomics; (2) design genetic privacy course modules, including topics on genomic data analysis, genetic privacy breaching techniques, ethics, regulations, laws and pertinent techniques about genetic privacy protection; and (3) develop hands-on projects on privacy infringement and protection that can be customized for the audience with different backgrounds.
These two projects expect to advance theoretical understanding of fundamental issues related to privacy preserving genomic data analysis, improve the design and implementation of practical techniques to effectively protect privacy, and develop and propagate open standards, technical guidelines, and education opportunities to promote the share and openness of genomic data for social good. The two projects are collaborated with Prof. Xinghua Shi from the Department of Bioinformatics and Genomics at the University of North Carolina at Charlotte.
Dr. Wu and his team at the University of Arkansas are developing novel privacy preservation solutions to protect privacy of human subjects in mining tabular data, social network data, healthcare data and genetic data. They are also working actively on the development of innovative analytical methods to address big data challenges of 4V’s (volume, velocity, variety, and veracity) and social challenges of privacy preservation, anti-discrimination learning, and fraud detection in cyber networks.