Best Paper Awarded At CollaborateCom '10
November 4, 2010
Daphne Yao, assistant professor of computer science at Virginia Tech, holds a patent on her human-behavior driven malware detection technology. Virginia Tech Photo.
One of the serious threats to a user’s computer is a software program that might cause unwanted keystroke sequences to occur in order to hack someone’s identity. This form of an attack is increasing, infecting enterprise and personal computers, and caused by “organized malicious botnets,” said Daphne Yao, assistant professor of computer science at Virginia Tech.
To combat the “spoofing attacks,” Prof. Yao and her former student, Deian Stefan, now a graduate student in the computer science department at Stanford University, developed an authentication framework called “Telling Human and Bot Apart” (TUBA), a remote biometrics system based on keystroke-dynamics information.
Their work won a best paper award at CollaborateCom ’10, the 6th International Conference on Collaborative Computing, held in Chicago and sponsored by the Institute of Electrical and Electronic Engineers’ (IEEE) Computer Society, Create-Net, and the Institute for Computer Sciences.
The uniqueness of Yao and Stefan’s research is they studied how to identify when a computer program designed by a hacker was producing keystroke sequences “in order to spoof others,” they said. Then they created TUBA to monitor a user’s typing patterns.
In January of 2010, Prof. Yao won a $530,000 National Science Foundation (NSF) Faculty Early Career Development (CAREER) grant to develop software that differentiates human-user computer interaction from that of malware.
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