Graduation 2019

Weilin Xu, Yanjun Qi, alumni

SRG Lunch

alumni, Weilin Xu

Some photos for our lunch to celebrate the end of semester, beginning of summer, and congratulate Weilin Xu on his PhD:


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 Dr. Xu!

adversarial machine learning, Weilin Xu, alumni, PhD defense

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. A motivated adversary is often able to craft input samples that force a machine learning model to produce incorrect predictions, even if the target model achieves high accuracy on normal test inputs. This raises great concern when machine learning models are deployed for security-sensitive tasks.

Read More…

Wahoos at Oakland

alumni, pictures, posters, Yuan Tian, Fnu Suya, Mainuddin Jonas, Yongwhi Kwon, Weilin Xu

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]

Feature Squeezing at NDSS

adversarial machine learning, feature squeezing, Weilin Xu

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

All Posts by Category or Tags.