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2020 – today
- 2024
[j9]Daniel Gibert
, Giulio Zizzo, Quan Le, Jordi Planes:
Adversarial Robustness of Deep Learning-Based Malware Detectors via (De)Randomized Smoothing. IEEE Access 12: 61152-61162 (2024)- [i7]Daniel Gibert, Giulio Zizzo, Quan Le, Jordi Planes:
A Robust Defense against Adversarial Attacks on Deep Learning-based Malware Detectors via (De)Randomized Smoothing. CoRR abs/2402.15267 (2024) - [i6]Daniel Gibert:
Machine Learning for Windows Malware Detection and Classification: Methods, Challenges and Ongoing Research. CoRR abs/2404.18541 (2024) - [i5]Daniel Gibert, Luca Demetrio, Giulio Zizzo, Quan Le, Jordi Planes, Battista Biggio:
Certified Adversarial Robustness of Machine Learning-based Malware Detectors via (De)Randomized Smoothing. CoRR abs/2405.00392 (2024) - 2023
- [c11]Daniel Gibert, Giulio Zizzo, Quan Le:
Certified Robustness of Static Deep Learning-based Malware Detectors against Patch and Append Attacks. AISec@CCS 2023: 173-184 - [c10]Daniel Gibert, Giulio Zizzo, Quan Le:
Towards a Practical Defense Against Adversarial Attacks on Deep Learning-Based Malware Detectors via Randomized Smoothing. ESORICS Workshops (2) 2023: 683-699 - [c9]Daniel Gibert, Jordi Planes, Quan Le, Giulio Zizzo:
A Wolf in Sheep's Clothing: Query-Free Evasion Attacks Against Machine Learning-Based Malware Detectors with Generative Adversarial Networks. EuroS&P Workshops 2023: 415-426 - [i4]Daniel Gibert, Jordi Planes, Quan Le, Giulio Zizzo:
Query-Free Evasion Attacks Against Machine Learning-Based Malware Detectors with Generative Adversarial Networks. CoRR abs/2306.09925 (2023) - [i3]Daniel Gibert, Giulio Zizzo, Quan Le:
Towards a Practical Defense against Adversarial Attacks on Deep Learning-based Malware Detectors via Randomized Smoothing. CoRR abs/2308.08906 (2023) - 2022
- [j8]Daniel Gibert, Matt Fredrikson, Carles Mateu, Jordi Planes, Quan Le:
Enhancing the insertion of NOP instructions to obfuscate malware via deep reinforcement learning. Comput. Secur. 113: 102543 (2022) - [j7]Daniel Gibert, Jordi Planes, Carles Mateu, Quan Le:
Fusing feature engineering and deep learning: A case study for malware classification. Expert Syst. Appl. 207: 117957 (2022) - [j6]Teresa Alsinet, Josep Argelich, Ramón Béjar, Daniel Gibert, Jordi Planes:
Argumentation Reasoning with Graph Isomorphism Networks for Reddit Conversation Analysis. Int. J. Comput. Intell. Syst. 15(1): 86 (2022) - [j5]Daniel Gibert:
PE Parser: A Python package for Portable Executable files processing. Softw. Impacts 13: 100365 (2022) - [i2]Daniel Gibert, Carles Mateu, Jordi Planes, Quan Le:
Fusing Feature Engineering and Deep Learning: A Case Study for Malware Classification. CoRR abs/2206.05735 (2022) - 2021
- [j4]Daniel Gibert, Carles Mateu, Jordi Planes, João Marques-Silva:
Auditing static machine learning anti-Malware tools against metamorphic attacks. Comput. Secur. 102: 102159 (2021) - [c8]Teresa Alsinet, Josep Argelich, Ramón Béjar, Daniel Gibert, Jordi Planes, Nil Torrent:
Argumentation Reasoning with Graph Neural Networks for Reddit Conversation Analysis. CCIA 2021: 123-131 - [c7]Ian Palacín, Daniel Gibert, Jordi Planes, Simone Arena, Pier Francesco Orrù, Maurizio Melis, Marco Annis:
Anomaly Detection for Diagnosing Failures in a Centrifugal Compressor Train. CCIA 2021: 217-220 - [i1]Daniel Gibert, Matt Fredrikson, Carles Mateu, Jordi Planes, Quan Le:
Enhancing the Insertion of NOP Instructions to Obfuscate Malware via Deep Reinforcement Learning. CoRR abs/2111.09626 (2021) - 2020
- [b1]Daniel Gibert:
Going Deep into the Cat and the Mouse Game: Deep Learning for Malware Classification. University of Lleida, Spain, 2020 - [j3]Daniel Gibert, Carles Mateu, Jordi Planes:
HYDRA: A multimodal deep learning framework for malware classification. Comput. Secur. 95: 101873 (2020) - [j2]Daniel Gibert, Carles Mateu, Jordi Planes:
The rise of machine learning for detection and classification of malware: Research developments, trends and challenges. J. Netw. Comput. Appl. 153: 102526 (2020) - [c6]Daniel Gibert, Carles Mateu, Jordi Planes:
Orthrus: A Bimodal Learning Architecture for Malware Classification. IJCNN 2020: 1-8
2010 – 2019
- 2019
- [j1]Daniel Gibert, Carles Mateu, Jordi Planes, Ramon Vicens:
Using convolutional neural networks for classification of malware represented as images. J. Comput. Virol. Hacking Tech. 15(1): 15-28 (2019) - [c5]Daniel Gibert, Alba Lamas, Ruben Martins, Carles Mateu, Jordi Planes:
An Android Malware Detection Framework Using Graph Embeddings and Convolutional Neural Networks. CCIA 2019: 45-53 - [c4]Daniel Gibert, Carles Mateu, Jordi Planes:
A Hierarchical Convolutional Neural Network for Malware Classification. IJCNN 2019: 1-8 - 2018
- [c3]Daniel Gibert, Carles Mateu, Jordi Planes, Ramon Vicens:
Classification of Malware by Using Structural Entropy on Convolutional Neural Networks. AAAI 2018: 7759-7764 - [c2]Daniel Gibert, Carles Mateu, Jordi Planes:
An End-to-End Deep Learning Architecture for Classification of Malware's Binary Content. ICANN (3) 2018: 383-391 - 2017
- [c1]Daniel Gibert, Javier Béjar, Carles Mateu, Jordi Planes, Daniel Solis, Ramon Vicens:
Convolutional Neural Networks for Classification of Malware Assembly Code. CCIA 2017: 221-226
Coauthor Index
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