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Part-Based Models Improve Adversarial Robustness


Sep 15, 2022
Chawin Sitawarin, Kornrapat Pongmala, Yizheng Chen, Nicholas Carlini, David Wagner

* Code can be found at https://github.com/chawins/adv-part-model 

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Adversarial Examples for $k$-Nearest Neighbor Classifiers Based on Higher-Order Voronoi Diagrams


Nov 19, 2020
Chawin Sitawarin, Evgenios M. Kornaropoulos, Dawn Song, David Wagner


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Improving Adversarial Robustness Through Progressive Hardening


Mar 18, 2020
Chawin Sitawarin, Supriyo Chakraborty, David Wagner

* Preprint. Under review 

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Minimum-Norm Adversarial Examples on KNN and KNN-Based Models


Mar 14, 2020
Chawin Sitawarin, David Wagner

* 3rd Deep Learning and Security Workshop (co-located with the 41st IEEE Symposium on Security and Privacy) 

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Defending Against Adversarial Examples with K-Nearest Neighbor


Jun 23, 2019
Chawin Sitawarin, David Wagner

* Preprint 

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Better the Devil you Know: An Analysis of Evasion Attacks using Out-of-Distribution Adversarial Examples


May 05, 2019
Vikash Sehwag, Arjun Nitin Bhagoji, Liwei Song, Chawin Sitawarin, Daniel Cullina, Mung Chiang, Prateek Mittal

* 18 pages, 5 figures, 9 tables 

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On the Robustness of Deep K-Nearest Neighbors


Mar 20, 2019
Chawin Sitawarin, David Wagner

* Published at Deep Learning and Security Workshop 2019 (IEEE S&P) 

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DARTS: Deceiving Autonomous Cars with Toxic Signs


May 31, 2018
Chawin Sitawarin, Arjun Nitin Bhagoji, Arsalan Mosenia, Mung Chiang, Prateek Mittal

* Submitted to ACM CCS 2018; Extended version of [1801.02780] Rogue Signs: Deceiving Traffic Sign Recognition with Malicious Ads and Logos 

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Rogue Signs: Deceiving Traffic Sign Recognition with Malicious Ads and Logos


Mar 26, 2018
Chawin Sitawarin, Arjun Nitin Bhagoji, Arsalan Mosenia, Prateek Mittal, Mung Chiang

* Extended abstract accepted for the 1st Deep Learning and Security Workshop; 5 pages, 4 figures 

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Beyond Grand Theft Auto V for Training, Testing and Enhancing Deep Learning in Self Driving Cars


Dec 04, 2017
Mark Martinez, Chawin Sitawarin, Kevin Finch, Lennart Meincke, Alex Yablonski, Alain Kornhauser

* 15 pages, 4 figures, under review by TRB 2018 Annual Meeting 

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