Gotta Catch Ém All: Using Honeypots to Catch Adversarial Attacks on
Neural Networks

Gotta Catch Ém All: Using Honeypots to Catch Adversarial Attacks on Neural Networks

18 April 2019

Papers citing "Gotta Catch Ém All: Using Honeypots to Catch Adversarial Attacks on Neural Networks"

19 / 19 papers shown

Title
Towards Unified Robustness Against Both Backdoor and Adversarial Attacks Zhenxing Niu Yuyao Sun Qiguang Miao Rong Jin Gang Hua AAML 46 6 0 28 May 2024
A LLM Assisted Exploitation of AI-Guardian Nicholas Carlini ELM SILM 24 15 0 20 Jul 2023
Glaze: Protecting Artists from Style Mimicry by Text-to-Image Models Shawn Shan Jenna Cryan Emily Wenger Haitao Zheng Rana Hanocka Ben Y. Zhao WIGM 17 177 0 08 Feb 2023
"Real Attackers Don't Compute Gradients": Bridging the Gap Between Adversarial ML Research and Practice Giovanni Apruzzese Hyrum S. Anderson Savino Dambra D. Freeman Fabio Pierazzi Kevin A. Roundy AAML 33 75 0 29 Dec 2022
Increasing Confidence in Adversarial Robustness Evaluations Roland S. Zimmermann Wieland Brendel Florian Tramèr Nicholas Carlini AAML 41 16 0 28 Jun 2022
Poison Forensics: Traceback of Data Poisoning Attacks in Neural Networks Shawn Shan A. Bhagoji Haitao Zheng Ben Y. Zhao AAML 94 50 0 13 Oct 2021
Multi-Trigger-Key: Towards Multi-Task Privacy Preserving In Deep Learning Ren Wang Zhe Xu Alfred Hero 32 0 0 06 Oct 2021
Quantization Backdoors to Deep Learning Commercial Frameworks Hua Ma Huming Qiu Yansong Gao Zhi-Li Zhang A. Abuadbba Minhui Xue Anmin Fu Jiliang Zhang S. Al-Sarawi Derek Abbott MQ 38 19 0 20 Aug 2021
TRAPDOOR: Repurposing backdoors to detect dataset bias in machine learning-based genomic analysis Esha Sarkar Michail Maniatakos 32 3 0 14 Aug 2021
Evaluating the Robustness of Trigger Set-Based Watermarks Embedded in Deep Neural Networks Suyoung Lee Wonho Song Suman Jana M. Cha Sooel Son AAML 27 13 0 18 Jun 2021
RBNN: Memory-Efficient Reconfigurable Deep Binary Neural Network with IP Protection for Internet of Things Huming Qiu Hua Ma Zhi-Li Zhang Yifeng Zheng Anmin Fu Pan Zhou Yansong Gao Derek Abbott S. Al-Sarawi MQ 19 9 0 09 May 2021
Hidden Backdoors in Human-Centric Language Models Shaofeng Li Hui Liu Tian Dong Benjamin Zi Hao Zhao Minhui Xue Haojin Zhu Jialiang Lu SILM 35 147 0 01 May 2021
"What's in the box?!": Deflecting Adversarial Attacks by Randomly Deploying Adversarially-Disjoint Models Sahar Abdelnabi Mario Fritz AAML 27 7 0 09 Feb 2021
Backdoor Attacks and Countermeasures on Deep Learning: A Comprehensive Review Yansong Gao Bao Gia Doan Zhi-Li Zhang Siqi Ma Jiliang Zhang Anmin Fu Surya Nepal Hyoungshick Kim AAML 36 221 0 21 Jul 2020
Backdoor Learning: A Survey Yiming Li Yong Jiang Zhifeng Li Shutao Xia AAML 45 590 0 17 Jul 2020
Hidden Trigger Backdoor Attacks Aniruddha Saha Akshayvarun Subramanya Hamed Pirsiavash 24 613 0 30 Sep 2019
Universal Litmus Patterns: Revealing Backdoor Attacks in CNNs Soheil Kolouri Aniruddha Saha Hamed Pirsiavash Heiko Hoffmann AAML 30 231 0 26 Jun 2019
Adversarial Machine Learning at Scale Alexey Kurakin Ian Goodfellow Samy Bengio AAML 298 3,113 0 04 Nov 2016
Adversarial examples in the physical world Alexey Kurakin Ian Goodfellow Samy Bengio SILM AAML 326 5,847 0 08 Jul 2016