Luis Muñoz-González

  • Imperial College London, UK

According to our database1, Luis Muñoz-González authored at least 36 papers between 2011 and 2022.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.



In proceedings 
PhD thesis 


Online presence:



HA-Grid: Security Aware Hazard Analysis for Smart Grids.
Proceedings of the IEEE International Conference on Communications, 2022

Privacy-Preserving Technologies for Trusted Data Spaces.
Proceedings of the Technologies and Applications for Big Data Value, 2022

FedRAD: Federated Robust Adaptive Distillation.
CoRR, 2021

Regularization Can Help Mitigate Poisoning Attacks... with the Right Hyperparameters.
CoRR, 2021

Real-time Detection of Practical Universal Adversarial Perturbations.
CoRR, 2021

Universal Adversarial Perturbations for Malware.
CoRR, 2021

Non-IID data re-balancing at IoT edge with peer-to-peer federated learning for anomaly detection.
Proceedings of the WiSec '21: 14th ACM Conference on Security and Privacy in Wireless and Mobile Networks, Abu Dhabi, United Arab Emirates, 28 June, 2021

Universal Adversarial Robustness of Texture and Shape-Biased Models.
Proceedings of the 2021 IEEE International Conference on Image Processing, 2021

Shadow-Catcher: Looking into Shadows to Detect Ghost Objects in Autonomous Vehicle 3D Sensing.
Proceedings of the Computer Security - ESORICS 2021, 2021

Robustness and Transferability of Universal Attacks on Compressed Models.
CoRR, 2020

Robust Aggregation for Adaptive Privacy Preserving Federated Learning in Healthcare.
CoRR, 2020

GhostBuster: Looking Into Shadows to Detect Ghost Objects in Autonomous Vehicle 3D Sensing.
CoRR, 2020

Regularisation Can Mitigate Poisoning Attacks: A Novel Analysis Based on Multiobjective Bilevel Optimisation.
CoRR, 2020

Exact Inference Techniques for the Analysis of Bayesian Attack Graphs.
IEEE Trans. Dependable Secur. Comput., 2019

Universal Adversarial Perturbations to Understand Robustness of Texture vs. Shape-biased Training.
CoRR, 2019

Byzantine-Robust Federated Machine Learning through Adaptive Model Averaging.
CoRR, 2019

Poisoning Attacks with Generative Adversarial Nets.
CoRR, 2019

Sensitivity of Deep Convolutional Networks to Gabor Noise.
CoRR, 2019

Defending against poisoning attacks in online learning settings.
Proceedings of the 27th European Symposium on Artificial Neural Networks, 2019

Procedural Noise Adversarial Examples for Black-Box Attacks on Deep Convolutional Networks.
Proceedings of the 2019 ACM SIGSAC Conference on Computer and Communications Security, 2019

Efficient Attack Countermeasure Selection Accounting for Recovery and Action Costs.
Proceedings of the 14th International Conference on Availability, Reliability and Security, 2019

Determining Resilience Gains From Anomaly Detection for Event Integrity in Wireless Sensor Networks.
ACM Trans. Sens. Networks, 2018

Procedural Noise Adversarial Examples for Black-Box Attacks on Deep Neural Networks.
CoRR, 2018

Mitigation of Adversarial Attacks through Embedded Feature Selection.
CoRR, 2018

Approaches to Enhancing Cyber Resilience: Report of the North Atlantic Treaty Organization (NATO) Workshop IST-153.
CoRR, 2018

Detection of Adversarial Training Examples in Poisoning Attacks through Anomaly Detection.
CoRR, 2018

Label Sanitization Against Label Flipping Poisoning Attacks.
Proceedings of the ECML PKDD 2018 Workshops, 2018

Efficient Attack Graph Analysis through Approximate Inference.
ACM Trans. Priv. Secur., 2017

Don't fool Me!: Detection, Characterisation and Diagnosis of Spoofed and Masked Events in Wireless Sensor Networks.
IEEE Trans. Dependable Secur. Comput., 2017

Towards Poisoning of Deep Learning Algorithms with Back-gradient Optimization.
Proceedings of the 10th ACM Workshop on Artificial Intelligence and Security, 2017

Laplace Approximation for Divisive Gaussian Processes for Nonstationary Regression.
IEEE Trans. Pattern Anal. Mach. Intell., 2016

Automated Dynamic Analysis of Ransomware: Benefits, Limitations and use for Detection.
CoRR, 2016

Exact Inference Techniques for the Dynamic Analysis of Attack Graphs.
CoRR, 2015

Divisive Gaussian Processes for Nonstationary Regression.
IEEE Trans. Neural Networks Learn. Syst., 2014

Laplace approximation with Gaussian Processes for volatility forecasting.
Proceedings of the 4th International Workshop on Cognitive Information Processing, 2014

Heteroscedastic Gaussian process regression using expectation propagation.
Proceedings of the 2011 IEEE International Workshop on Machine Learning for Signal Processing, 2011