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Asim Darwaish
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2020 – today
- 2023
- [c7]Tianwei Lan, Asim Darwaish, Farid Naït-Abdesselam, Pengwenlong Gu:
Defensive Randomization Against Adversarial Attacks in Image-Based Android Malware Detection. ICC 2023: 5072-5077 - 2022
- [b1]Asim Darwaish:
Adversary-aware machine learning models for malware detection systems. (Modèles d'apprentissage robustes aux attaques pour les systèmes de détection de logiciels malveillants). Paris Cité University, France, 2022 - [c6]Farid Naït-Abdesselam, Asim Darwaish, Chafiq Titouna:
Malware Forensics: Legacy Solutions, Recent Advances, and Future Challenges. Honoring Professor Mohammad S. Obaidat 2022: 685-710 - 2021
- [c5]Asim Darwaish, Farid Naït-Abdesselam, Chafiq Titouna, Sumera Sattar:
Robustness of Image-based Android Malware Detection Under Adversarial Attacks. ICC 2021: 1-6 - 2020
- [c4]Asim Darwaish, Farid Naït-Abdesselam:
RGB-based Android Malware Detection and Classification Using Convolutional Neural Network. GLOBECOM 2020: 1-6 - [c3]Farid Naït-Abdesselam, Asim Darwaish, Chafiq Titouna:
An Intelligent Malware Detection and Classification System Using Apps-to-Images Transformations and Convolutional Neural Networks. WiMob 2020: 1-6 - [c2]Chafiq Titouna, Farid Naït-Abdesselam, Asim Darwaish:
A Data Cleansing Approach In Smart Home Environments Using Artificial Neural Networks. WiMob 2020: 1-6
2010 – 2019
- 2019
- [c1]Asim Darwaish, Medina Hadjem, Farid Naït-Abdesselam, Ashfaq Khokhar:
Predicting Cardiac Anomalies Using Probabilistic Models on Historical Electrocardiogram Data. SmartNets 2019: 1-6 - [i1]Asim Darwaish, Farid Naït-Abdesselam
, Ashfaq Khokhar:
Detection and Prediction of Cardiac Anomalies Using Wireless Body Sensors and Bayesian Belief Networks. CoRR abs/1904.07976 (2019)
Coauthor Index
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