Daniel Gibert
Orcid: 0000-0002-2448-1297
According to our database1,
Daniel Gibert
authored at least 26 papers
between 2017 and 2024.
Collaborative distances:
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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
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
Comput. Secur., 2021
Proceedings of the Artificial Intelligence Research and Development, 2021
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
Comput. Secur., 2020
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
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
Proceedings of the Recent Advances in Artificial Intelligence Research and Development, 2017