Left to right
: Jonah Weissman, Yonghwi Kown, Bargav Jayaraman, Aihua Chen, Hannah Chen, Weilin Xu, Riley Spahn, David Evans, Fnu Suya, Yuan Tian, Mainuddin Jonas, Tu Le, Faysal Hossain, Xiao Zhang, Jack Verrier
Congratulations to Weilin Xu for successfully defending his PhD Thesis!
Weilin's Committee: Homa Alemzadeh, Yanjun Qi, Patrick McDaniel (on screen), David Evans, Vicente Ordóñez Román Improving Robustness of Machine Learning Models using Domain Knowledge Although machine learning techniques have achieved great success in many areas, such as computer vision, natural language processing, and computer security, recent studies have shown that they are not robust under attack.
UVA Group Dinner at IEEE Security and Privacy 2018
Including our newest faculty member, Yongwhi Kwon, joining UVA in Fall 2018!
Yuan Tian, Fnu Suya, Mainuddin Jonas, Yongwhi Kwon, David Evans, Weihang Wang, Aihua Chen, Weilin Xu
## Poster Session
Fnu Suya (with Yuan Tian and David Evans), Adversaries Don’t Care About Averages: Batch Attacks on Black-Box Classifiers [PDF]
Mainuddin Jonas (with David Evans), Enhancing Adversarial Example Defenses Using Internal Layers [PDF]
Weilin Xu presented Feature Squeezing: Detecting Adversarial Examples in Deep Neural Networks at the Network and Distributed System Security Symposium 2018. San Diego, CA. 21 February 2018.
Paper: Weilin Xu, David Evans, Yanjun Qi. Feature Squeezing: Detecting Adversarial Examples in Deep Neural Networks. NDSS 2018. [PDF]
Project Site: EvadeML.org