no code implementations • 16 May 2023 • Siyuan Wang, Jianming Zheng, Xuejun Hu, Fei Cai, Chengyu Song, Xueshan Luo
Event detection (ED) is aimed to identify the key trigger words in unstructured text and predict the event types accordingly.
no code implementations • 20 Sep 2022 • Abhishek Aich, Calvin-Khang Ta, Akash Gupta, Chengyu Song, Srikanth V. Krishnamurthy, M. Salman Asif, Amit K. Roy-Chowdhury
Using the joint image-text features to train the generator, we show that GAMA can craft potent transferable perturbations in order to fool victim classifiers in various attack settings.
no code implementations • 20 Sep 2022 • Abhishek Aich, Shasha Li, Chengyu Song, M. Salman Asif, Srikanth V. Krishnamurthy, Amit K. Roy-Chowdhury
Our goal is to design an attack strategy that can learn from such natural scenes by leveraging the local patch differences that occur inherently in such images (e. g. difference between the local patch on the object `person' and the object `bike' in a traffic scene).
1 code implementation • 7 Aug 2022 • Zikui Cai, Chengyu Song, Srikanth Krishnamurthy, Amit Roy-Chowdhury, M. Salman Asif
We also show that the perturbations generated by our proposed method are highly transferable and can be adopted for hard-label blackbox attacks.
no code implementations • CVPR 2022 • Zikui Cai, Shantanu Rane, Alejandro E. Brito, Chengyu Song, Srikanth V. Krishnamurthy, Amit K. Roy-Chowdhury, M. Salman Asif
We compare our zero-query attack against a few-query scheme that repeatedly checks if the victim system is fooled.
no code implementations • 6 Dec 2021 • Zikui Cai, Xinxin Xie, Shasha Li, Mingjun Yin, Chengyu Song, Srikanth V. Krishnamurthy, Amit K. Roy-Chowdhury, M. Salman Asif
In this paper, we present a new approach to generate context-aware attacks for object detectors.
no code implementations • 24 Oct 2021 • Mingjun Yin, Shasha Li, Chengyu Song, M. Salman Asif, Amit K. Roy-Chowdhury, Srikanth V. Krishnamurthy
A very recent defense strategy for detecting adversarial examples, that has been shown to be robust to current attacks, is to check for intrinsic context consistencies in the input data, where context refers to various relationships (e. g., object-to-object co-occurrence relationships) in images.
1 code implementation • NeurIPS 2021 • Shasha Li, Abhishek Aich, Shitong Zhu, M. Salman Asif, Chengyu Song, Amit K. Roy-Chowdhury, Srikanth V. Krishnamurthy
When compared to the image classification models, black-box adversarial attacks against video classification models have been largely understudied.
no code implementations • ICCV 2021 • Mingjun Yin, Shasha Li, Zikui Cai, Chengyu Song, M. Salman Asif, Amit K. Roy-Chowdhury, Srikanth V. Krishnamurthy
Vision systems that deploy Deep Neural Networks (DNNs) are known to be vulnerable to adversarial examples.
no code implementations • 26 Aug 2020 • Shasha Li, Karim Khalil, Rameswar Panda, Chengyu Song, Srikanth V. Krishnamurthy, Amit K. Roy-Chowdhury, Ananthram Swami
The emergence of Internet of Things (IoT) brings about new security challenges at the intersection of cyber and physical spaces.
no code implementations • ECCV 2020 • Shasha Li, Shitong Zhu, Sudipta Paul, Amit Roy-Chowdhury, Chengyu Song, Srikanth Krishnamurthy, Ananthram Swami, Kevin S. Chan
There has been a recent surge in research on adversarial perturbations that defeat Deep Neural Networks (DNNs) in machine vision; most of these perturbation-based attacks target object classifiers.
no code implementations • 23 May 2019 • Wookhyun Han, Md Lutfor Rahman, Yuxuan Chen, Chengyu Song, Byoungyoung Lee, Insik Shin
Then it uses oracle-guided program synthesis to reconstruct the symbolic expression based on input-output pairs.
Cryptography and Security
1 code implementation • 22 Oct 2018 • Dang Tu Nguyen, Chengyu Song, Zhiyun Qian, Srikanth V. Krishnamurthy, Edward J. M. Colbert, Patrick McDaniel
In this paper, we design IoTSan, a novel practical system that uses model checking as a building block to reveal "interaction-level" flaws by identifying events that can lead the system to unsafe states.
Cryptography and Security
1 code implementation • 20 Jul 2018 • Esmaeil Mohammadian Koruyeh, Khaled Khasawneh, Chengyu Song, Nael Abu-Ghazaleh
In particular, on Core-i7 Skylake and newer processors (but not on Intel's Xeon processor line), a patch called RSB refilling is used to address a vulnerability when the RSB underfills; this defense interferes with SpectreRSB's ability to launch attacks that switch into the kernel.
Cryptography and Security
1 code implementation • 2 Jul 2018 • Shasha Li, Ajaya Neupane, Sujoy Paul, Chengyu Song, Srikanth V. Krishnamurthy, Amit K. Roy Chowdhury, Ananthram Swami
We exploit recent advances in generative adversarial network (GAN) architectures to account for temporal correlations and generate adversarial samples that can cause misclassification rates of over 80% for targeted activities.