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Kenneth Co, Ph.D.
Kenneth Co, Ph.D.
Assistant Professor, Asian Institute of Management
Verified email at aim.edu - Homepage
Title
Cited by
Cited by
Year
Byzantine-robust Federated Machine Learning Through Adaptive Model Averaging
L Muñoz-González, KT Co, EC Lupu
arXiv preprint arXiv:1909.05125, 2019
1802019
Procedural Noise Adversarial Examples for Black-Box Attacks on Deep Convolutional Networks
KT Co, L Munoz Gonzalez, S De Maupeou, E Lupu
26th ACM SIGSAC Conference on Computer and Communications Security (CCS 2019), 2019
532019
Object Removal Attacks on LiDAR-based 3D Object Detectors
Z Hau, KT Co, S Demetriou, EC Lupu
NDSS 2021: Automotive and Autonomous Vehicle Security (AutoSec), 2021
302021
Universal Adversarial Robustness of Texture and Shape-Biased Models
KT Co, L Muñoz-González, L Kanthan, B Glocker, EC Lupu
28th IEEE International Conference on Image Processing (ICIP 2021), 2019
112019
Robustness and Transferability of Universal Attacks on Compressed Models
AG Matachana, KT Co, L Muñoz-González, D Martinez, EC Lupu
AAAI 2021: Towards Robust, Secure, and Efficient Machine Learning, 2020
82020
Bayesian Optimization for Black-Box Evasion of Machine Learning Systems
KT Co
Imperial College London, 2017
8*2017
Jacobian regularization for mitigating universal adversarial perturbations
KT Co, DM Rego, EC Lupu
International Conference on Artificial Neural Networks, 202-213, 2021
62021
Byzantine-robust federated machine learning through adaptive model averaging. arXiv 2019
L Muñoz-González, KT Co, EC Lupu
arXiv preprint arXiv:1909.05125, 0
6
Challenges and Advances in Adversarial Machine Learning
L Muñoz-González, J Carnerero-Cano, KT Co, EC Lupu
Resilience and Hybrid Threats: Security and Integrity for the Digital World …, 2019
52019
Sensitivity of Deep Convolutional Networks to Gabor Noise
KT Co, L Muñoz-González, EC Lupu
ICML 2019: On Identifying and Understanding Deep Learning Phenomena, 2019
52019
HA-Grid: Security Aware Hazard Analysis for Smart Grids
L Castiglione, Z Hau, P Ge, K Co, L Munoz Gonzalez, F Teng, E Lupu
13th IEEE International Conference on Communications, Control, and Computing …, 2022
32022
Real-time detection of practical universal adversarial perturbations
KT Co, L Muñoz-González, L Kanthan, EC Lupu
arXiv preprint arXiv:2105.07334, 2021
3*2021
Universal Adversarial perturbations to understand robustness of texture vs. shape-biased training
KT Co, L Munoz-González, L Kanthan, B Glocker, EC Lupu
arXiv preprint arXiv:1911.10364, 2019
32019
Jacobian Ensembles Improve Robustness Trade-Offs to Adversarial Attacks
KT Co, D Martinez-Rego, Z Hau, EC Lupu
International Conference on Artificial Neural Networks, 680-691, 2022
12022
Understanding and Mitigating Universal Adversarial Perturbations for Computer Vision Neural Networks
KT Co
Imperial College London, 2023
2023
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