publications

publications by categories in reversed chronological order.

2022

  1. ICML
    Demystifying the Adversarial Robustness of Random Transformation Defenses
    Sitawarin, Chawin, Golan-Strieb, Zachary, and Wagner, David
    In Proceedings of the 39th International Conference on Machine Learning (Short Presentation), AAAI-2022 Workshop on Adversarial Machine Learning and Beyond (Best Paper), 2022

2021

  1. Workshop
    Improving the Accuracy-Robustness Trade-off for Dual-Domain Adversarial Training
    Sitawarin, Chawin, Sridhar, Arvind P, and Wagner, David
    In Workshop on Uncertainty and Robustness in Deep Learning, 2021
  2. Workshop
    Mitigating Adversarial Training Instability with Batch Normalization
    Sridhar, Arvind P,  Sitawarin, Chawin, and Wagner, David
    In Security and Safety in Machine Learning Systems Workshop, 2021
  3. AISec
    SAT: Improving Adversarial Training via Curriculum-Based Loss Smoothing
    Sitawarin, Chawin, Chakraborty, Supriyo, and Wagner, David
    In Proceedings of the 14th ACM Workshop on Artificial Intelligence and Security, 2021
  4. NeurIPS
    Adversarial Examples for k-Nearest Neighbor Classifiers Based on Higher-Order Voronoi Diagrams
    Sitawarin, Chawin, Kornaropoulos, Evgenios M, Song, Dawn, and Wagner, David
    In Advances in Neural Information Processing Systems, 2021

2020

  1. DLS
    Minimum-Norm Adversarial Examples on KNN and KNN Based Models
    Sitawarin, Chawin, and Wagner, David
    In 2020 IEEE Security and Privacy Workshops (SPW), 2020

2019

  1. AISec
    Analyzing the Robustness of Open-World Machine Learning
    Sehwag, Vikash, Bhagoji, Arjun Nitin, Song, Liwei,  Sitawarin, Chawin, Cullina, Daniel, Chiang, Mung, and Mittal, Prateek
    In Proceedings of the 12th ACM Workshop on Artificial Intelligence and Security, 2019
  2. Preprint
    Defending against Adversarial Examples with K-Nearest Neighbor
    Sitawarin, Chawin, and Wagner, David
    arXiv:1906.09525 [cs], 2019
  3. DLS
    On the Robustness of Deep K-Nearest Neighbors
    Sitawarin, Chawin, and Wagner, David
    In 2019 IEEE Security and Privacy Workshops (SPW), 2019

2018

  1. CISS
    Enhancing Robustness of Machine Learning Systems via Data Transformations
    Bhagoji, Arjun Nitin, Cullina, Daniel,  Sitawarin, Chawin, and Mittal, Prateek
    In 52nd Annual Conference on Information Sciences and Systems (CISS), 2018
  2. Photon. Res.
    Inverse-designed photonic fibers and metasurfaces for nonlinear frequency conversion (Invited)
    Sitawarin, Chawin, Jin, Weiliang, Lin, Zin, and Rodriguez, Alejandro W.
    Photon. Res., 2018
  3. DLS
    Rogue Signs: Deceiving Traffic Sign Recognition with Malicious Ads and Logos
    Sitawarin, Chawin, Bhagoji, Arjun Nitin, Mosenia, Arsalan, Mittal, Prateek, and Chiang, Mung
    arXiv:1801.02780 [cs], 2018
  4. CCS
    Not All Pixels Are Born Equal: An Analysis of Evasion Attacks under Locality Constraints
    Sehwag, Vikash,  Sitawarin, Chawin, Bhagoji, Arjun Nitin, Mosenia, Arsalan, Chiang, Mung, and Mittal, Prateek
    In Proceedings of the 2018 ACM SIGSAC Conference on Computer and Communications Security, 2018
  5. Preprint
    DARTS: Deceiving Autonomous Cars with Toxic Signs
    Sitawarin, Chawin, Bhagoji, Arjun Nitin, Mosenia, Arsalan, Chiang, Mung, and Mittal, Prateek
    arXiv:1802.06430 [cs], 2018

2017

  1. Preprint
    Beyond Grand Theft Auto v for Training, Testing and Enhancing Deep Learning in Self Driving Cars
    Martinez, Mark Anthony,  Sitawarin, Chawin, Finch, Kevin, Meincke, Lennart, Yablonski, Alexander, and Kornhauser, Alain
    arXiv:1712.01397 [cs], 2017

2016

  1. CLEO
    Inverse-Designed Nonlinear Nanophotonic Structures: Enhanced Frequency Conversion at the Nano Scale
    Lin, Zin,  Sitawarin, Chawin, Loncar, Marko, and Rodriguez, Alejandro W.
    In 2016 Conference on Lasers and Electro-Optics, CLEO 2016, 2016