Bias Busters: Robustifying DL-based Lithographic Hotspot Detectors
Against Backdooring Attacks

Bias Busters: Robustifying DL-based Lithographic Hotspot Detectors Against Backdooring Attacks

26 April 2020

Gaurav Rajavendra Reddy

Yiorgos Makris

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Papers citing "Bias Busters: Robustifying DL-based Lithographic Hotspot Detectors Against Backdooring Attacks"

9 / 9 papers shown

Title
On Improving Hotspot Detection Through Synthetic Pattern-Based Database Enhancement Gaurav Rajavendra Reddy Constantinos Xanthopoulos Yiorgos Makris 19 8 0 12 Jul 2020
Stop-and-Go: Exploring Backdoor Attacks on Deep Reinforcement Learning-based Traffic Congestion Control Systems Yue Wang Esha Sarkar Wenqing Li Michail Maniatakos Saif Eddin Jabari AAML 127 63 0 17 Mar 2020
Defending Neural Backdoors via Generative Distribution Modeling Ximing Qiao Yukun Yang H. Li AAML 49 183 0 10 Oct 2019
Are Adversarial Perturbations a Showstopper for ML-Based CAD? A Case Study on CNN-Based Lithographic Hotspot Detection Kang Liu Haoyu Yang Yuzhe Ma Benjamin Tan Bei Yu Evangeline F. Y. Young Ramesh Karri S. Garg AAML 37 10 0 25 Jun 2019
Targeted Backdoor Attacks on Deep Learning Systems Using Data Poisoning Xinyun Chen Chang-rui Liu Yue Liu Kimberly Lu Basel Alomair AAML SILM 143 1,852 0 15 Dec 2017
Wild Patterns: Ten Years After the Rise of Adversarial Machine Learning Battista Biggio Fabio Roli AAML 130 1,410 0 08 Dec 2017
Towards Deep Learning Models Resistant to Adversarial Attacks Aleksander Madry Aleksandar Makelov Ludwig Schmidt Dimitris Tsipras Adrian Vladu SILM OOD 310 12,117 0 19 Jun 2017
Adversarial Machine Learning at Scale Alexey Kurakin Ian Goodfellow Samy Bengio AAML 472 3,147 0 04 Nov 2016
Intriguing properties of neural networks Christian Szegedy Wojciech Zaremba Ilya Sutskever Joan Bruna D. Erhan Ian Goodfellow Rob Fergus AAML 277 14,961 1 21 Dec 2013