Kang Liu

Orcid: 0000-0001-7231-8315

Affiliations:
  • New York University, Brooklyn, NY, USA


According to our database1, Kang Liu authored at least 18 papers between 2013 and 2024.

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Bibliography

2024
Manipulation Attacks on Learned Image Compression.
IEEE Trans. Artif. Intell., June, 2024

CAMO: Correlation-Aware Mask Optimization with Modulated Reinforcement Learning.
Proceedings of the 61st ACM/IEEE Design Automation Conference, 2024

2023
Accelerating Persistent Hash Indexes via Reducing Negative Searches.
Proceedings of the 41st IEEE International Conference on Computer Design, 2023

2022
Denial-of-Service Attacks on Learned Image Compression.
CoRR, 2022

2021
Bias Busters: Robustifying DL-Based Lithographic Hotspot Detectors Against Backdooring Attacks.
IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2021

Training Data Poisoning in ML-CAD: Backdooring DL-Based Lithographic Hotspot Detectors.
IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2021

Can We Trust Machine Learning for Electronic Design Automation?
Proceedings of the 34th IEEE International System-on-Chip Conference, 2021

NNoculation: Catching BadNets in the Wild.
Proceedings of the AISec@CCS 2021: Proceedings of the 14th ACM Workshop on Artificial Intelligence and Security, 2021

Attacking a CNN-based Layout Hotspot Detector Using Group Gradient Method.
Proceedings of the ASPDAC '21: 26th Asia and South Pacific Design Automation Conference, 2021

Subverting Privacy-Preserving GANs: Hiding Secrets in Sanitized Images.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020
Adversarial Perturbation Attacks on ML-based CAD: A Case Study on CNN-based Lithographic Hotspot Detection.
ACM Trans. Design Autom. Electr. Syst., 2020

NNoculation: Broad Spectrum and Targeted Treatment of Backdoored DNNs.
CoRR, 2020

Poisoning the (Data) Well in ML-Based CAD: A Case Study of Hiding Lithographic Hotspots.
Proceedings of the 2020 Design, Automation & Test in Europe Conference & Exhibition, 2020

2019
Are Adversarial Perturbations a Showstopper for ML-Based CAD? A Case Study on CNN-Based Lithographic Hotspot Detection.
CoRR, 2019

BadNets: Evaluating Backdooring Attacks on Deep Neural Networks.
IEEE Access, 2019

Building Robust Machine Learning Systems: Current Progress, Research Challenges, and Opportunities.
Proceedings of the 56th Annual Design Automation Conference 2019, 2019

2018
Fine-Pruning: Defending Against Backdooring Attacks on Deep Neural Networks.
Proceedings of the Research in Attacks, Intrusions, and Defenses, 2018

2013
An Energy-Efficient Cyclic Diversionary Routing Strategy against Global Eavesdroppers in Wireless Sensor Networks.
Int. J. Distributed Sens. Networks, 2013


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