April 8, 2013
In order to detect anomalies that might suggest a breach in cyber security, an observer must understand the intended behaviors of computer systems and programs. Once they are understood, then appropriate actions can then be taken, allowing attacks on hardware/software to be thwarted. However, complications arise because program and system behaviors are diverse and often unpredictable.
Yao’s research focus has been on this methodology development for novel, practical, and quantitative anomaly detection. Specifically, she is analyzing causal relations of events and producing instructions for detecting anomalies in computer programs, systems, and networks.
Using real-time quantified system assurance, Yao will compute what is called an accurate system assurance index. This index is the planned and systematic set of activities that assure systems engineering processes and products will conform to systems requirements for safety and reliability. It also reflects the likelihood of each system event occurring according to the intended software program behaviors.
The researcher received her undergraduate degree in chemistry from Peking University (China), in 1998, followed by a master’s degree in chemistry from Princeton University in 2000. Yao received a master’s from Indiana University in 2002 and a doctoral degree from Brown University, both in the computer science field. Prior to joining the Virginia Tech community in 2009, she was an assistant professor at Rutgers University’s computer science department for two years.