Daniel Gibert

Orcid: 0000-0002-2448-1297

According to our database1, Daniel Gibert authored at least 26 papers between 2017 and 2024.

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

Timeline

Legend:

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Online presence:

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Bibliography

2024
Assessing the Impact of Packing on Machine Learning-Based Malware Detection and Classification Systems.
CoRR, 2024

Certified Adversarial Robustness of Machine Learning-based Malware Detectors via (De)Randomized Smoothing.
CoRR, 2024

Machine Learning for Windows Malware Detection and Classification: Methods, Challenges and Ongoing Research.
CoRR, 2024

A Robust Defense against Adversarial Attacks on Deep Learning-based Malware Detectors via (De)Randomized Smoothing.
CoRR, 2024

Adversarial Robustness of Deep Learning-Based Malware Detectors via (De)Randomized Smoothing.
IEEE Access, 2024

2023
Query-Free Evasion Attacks Against Machine Learning-Based Malware Detectors with Generative Adversarial Networks.
CoRR, 2023

A Wolf in Sheep's Clothing: Query-Free Evasion Attacks Against Machine Learning-Based Malware Detectors with Generative Adversarial Networks.
Proceedings of the IEEE European Symposium on Security and Privacy, 2023

Towards a Practical Defense Against Adversarial Attacks on Deep Learning-Based Malware Detectors via Randomized Smoothing.
Proceedings of the Computer Security. ESORICS 2023 International Workshops, 2023

Certified Robustness of Static Deep Learning-based Malware Detectors against Patch and Append Attacks.
Proceedings of the 16th ACM Workshop on Artificial Intelligence and Security, 2023

2022
PE Parser: A Python package for Portable Executable files processing.
Softw. Impacts, 2022

Argumentation Reasoning with Graph Isomorphism Networks for Reddit Conversation Analysis.
Int. J. Comput. Intell. Syst., 2022

Fusing feature engineering and deep learning: A case study for malware classification.
Expert Syst. Appl., 2022

Enhancing the insertion of NOP instructions to obfuscate malware via deep reinforcement learning.
Comput. Secur., 2022

2021
Auditing static machine learning anti-Malware tools against metamorphic attacks.
Comput. Secur., 2021

Anomaly Detection for Diagnosing Failures in a Centrifugal Compressor Train.
Proceedings of the Artificial Intelligence Research and Development, 2021

Argumentation Reasoning with Graph Neural Networks for Reddit Conversation Analysis.
Proceedings of the Artificial Intelligence Research and Development, 2021

2020
Going Deep into the Cat and the Mouse Game: Deep Learning for Malware Classification.
PhD thesis, 2020

The rise of machine learning for detection and classification of malware: Research developments, trends and challenges.
J. Netw. Comput. Appl., 2020

HYDRA: A multimodal deep learning framework for malware classification.
Comput. Secur., 2020

Orthrus: A Bimodal Learning Architecture for Malware Classification.
Proceedings of the 2020 International Joint Conference on Neural Networks, 2020

2019
Using convolutional neural networks for classification of malware represented as images.
J. Comput. Virol. Hacking Tech., 2019

A Hierarchical Convolutional Neural Network for Malware Classification.
Proceedings of the International Joint Conference on Neural Networks, 2019

An Android Malware Detection Framework Using Graph Embeddings and Convolutional Neural Networks.
Proceedings of the Artificial Intelligence Research and Development, 2019

2018
An End-to-End Deep Learning Architecture for Classification of Malware's Binary Content.
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2018, 2018

Classification of Malware by Using Structural Entropy on Convolutional Neural Networks.
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017
Convolutional Neural Networks for Classification of Malware Assembly Code.
Proceedings of the Recent Advances in Artificial Intelligence Research and Development, 2017


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